Soon, Georgia Tech students will be investigating these questions and more. A new initiative from the School of Biological Sciences is transforming Georgia Tech’s campus into a living laboratory for urban biodiversity research, with students at its center.
Using tiny Bluetooth-enabled trackers, students will tag and track butterflies, lizards, and birds. They’ll use the same groundbreaking new technology being employed by conservation biologists worldwide, including Benjamin Freeman and James Stroud, who are bringing their experience with large-scale wildlife tracking to the new campus initiative. Both Stroud and Freeman are Elizabeth Smithgall Watts Early Career Assistant Professors in the School of Biological Sciences and co-leads of the new project.
“Recording animal behavior in the wild is one of the final frontiers in ecology and evolution research,” says Stroud. “This new tracking technology will allow students to design and conduct research projects and learn data collection, spatial analysis, statistical modeling, and scientific communication — all while investigating real conservation questions about urban wildlife corridors, migration patterns, and habitat use.”
The program aims to involve more than 800 students each year across multiple programs and degree paths. “The big idea is to connect Georgia Tech undergraduates with cutting-edge science on campus, and to get them involved with all facets of this research,” Freeman says. Beyond ecology and biology, students will learn to engineer sensor technology, build data visualization tools using computer science, and analyze urban planning decisions through a public policy lens.
“Over the next year, undergraduates will begin deploying these tracking systems and conducting preliminary data analysis, but what’s really exciting is how this project can build on itself,” Freeman adds. “In five years, the Georgia Tech community will have built a dynamic campus biodiversity map — one that anyone can access to see hundreds of tagged birds, lizards, and butterflies moving across campus.”
There’s no shortage of animals on Georgia Tech’s campus — the Stroud Lab recently surveyed a population of green anole lizards in the Kendeda Building EcoCommons area, counting about 50 individuals. That presents a unique opportunity to tag and track each individual, he says, allowing students to study behavioral and ecological questions at the population level.
Freeman will help students tag northern mockingbirds, northern cardinals, eastern bluebirds, and eastern towhees, in addition to migratory birds that pass through campus in the spring and fall. “We’ll also tag monarch butterflies and gulf fritillary butterflies as they migrate through the EcoCommons in fall,” he says.
Both Freeman and Stroud have deep experience with the technology. For more than a decade, Stroud has pioneered one of the longest-running evolutionary studies of its kind: catching, documenting, and releasing each of the roughly 1,000 lizards living on “Lizard Island.” In 2025, he was awarded a Packard Fellowship to equip each lizard on the island with tiny sensor backpacks to document their behaviors and movements in real time.
In Ecuador, Freeman is building a similar project with support from a Packard Fellowship — a living laboratory spanning thousands of meters along the flanks of “Tech Mountain,” from lowland rainforest to cloud forest. Leveraging the same technology Georgia Tech students will use on campus, he is tagging and monitoring the daily movements of tropical birds and mapping their movements against microclimate sensors placed on the mountain’s slopes. It’s the first project of its kind.
“One of the most exciting things is how accessible this new technology is,” he says. “When it’s deployed on Georgia Tech’s campus, students will get to play a role in every single stage of the research.”
At Georgia Tech, that research will build on the living laboratory already centered in the Kendeda Building EcoCommons, where environmental conditions like wind, temperature, humidity, and soil quality are monitored by a variety of sensors. Students are already monitoring environmental data through the popular Living Building Science Vertically Integrated Program (VIP) course.
Considering climate information alongside animal movement patterns will offer a unique window into how animals respond to changing conditions, Stroud explains. “How do these environmental factors affect animals, and how can we use that information to support wildlife as our campus continues to develop?” he asks. “With this new data, students can lead projects to answer these questions and more.”
Freeman and Stroud also hope that the Kendeda Building’s accessible location will make the research a visible part of campus life, giving community members and visitors the opportunity to encounter the project firsthand.
“This work can have a meaningful impact far beyond the classroom,” Freeman says. “By understanding how wildlife uses the spaces around us, we can better support it in a changing world, all while training and empowering the next generation of scientists and leaders.”
]]>Now, new work from Georgia Tech School of Biological Sciences Assistant Professor Abigail Lind is looking beyond bacteria by investigating a common gut protist called Blastocystis.
In support of her research, Lind has received a prestigious Maximizing Investigators’ Research Award (MIRA) from the National Institutes of Health (NIH). The MIRA program provides investigators with five years of flexible funding, allowing them to pursue ambitious research in promising new directions.
Protists have long been understudied, Lind says, because until recently, these organisms were considered possible pathogens. “Recently, studies have found that they are actually correlated with many different positive health markers, like reduced inflammation and positive cardiovascular outcomes,” she explains. “But we still know very little about these organisms.”
“With this research, we want to lay a foundation to accelerate future work,” Lind adds. “We want to understand what these protists do, how they interact with microbial partners, and how that might ultimately impact their human hosts.”
The protists are notoriously tricky to work with. They swell up and “pop” if they’re exposed to oxygen, and nobody is quite sure what they eat. “We’ve developed new techniques to work with them in the lab, which is why we’re able to do this research now,” Lind says.
While decades of work have gone into cultivating gut bacteria in the lab, cultivating Blastocystis is a different story. “Many of the techniques developed to cultivate bacteria kill this protist,” Lind says, “so we had to be creative.”
Postdoctoral scholar Fredrick Leon tested combinations of nutrients ranging from store-bought protein powders to boiled wheatgrass solutions, eventually settling on the formula they use today. But it still is unclear what exactly the organism is eating — and how.
“We know the strategies that bacteria use to break down and utilize food, but these protists don't have the same genes,” she says. “Do they eat something completely different? Do they eat the same things but with a different strategy? And how does that impact the microbial community and human host? These are the questions that we're answering.”
Lind also aims to develop genetic tools for studying Blastocystis. Those tools could help researchers uncover which genes are responsible for specific functions, providing a clear map of what the protist does and how it does it.
By establishing new ways to grow, manipulate, and study Blastocystis, Lind hopes the project will provide answers about this organism while creating new tools to advance protist research more broadly.
“Our goal is to make Blastocystis a system that researchers can really begin to understand,” Lind says. “What we learn from this one organism could give us a foundation for studying many other protists and, ultimately, a more complete picture of the human gut microbiome.”
]]>The study, Evaluating Large Language Models for Accuracy Incentivizes Hallucinations, was recently published in Nature.
Understanding why hallucinations arise is a key factor in mitigating them, says Georgia Tech Regents’ Professor Santosh Vempala, who co-authored the paper. “We’ve seen models hallucinate everything from references to simple facts, and this can be a real problem when users take that information as true,” he adds. “It’s important to determine to what extent this is unavoidable and to what extent it’s an issue of what we're focusing on and not prioritizing.”
Vempala is the Frederick Storey II Chair of Computing in the College of Computing, an adjunct professor in the H. Milton Stewart School of Industrial and Systems Engineering, and an adjunct professor in the School of Mathematics, where he specializes in studying algorithms and high-dimensional geometry. He is also director of the Algorithms, Combinatorics and Optimization Ph.D. program.
As LLM usage becomes increasingly prevalent, Vempala aims to use his expertise to increase AI safety. “We need to identify and understand the dangers, but we also need to form principles around them,” he explains. “That’s a key goal of my work now.”
“Intuition is helpful and important, but rigorous principles emerge only when you write them down mathematically,” he adds. “We need a model that's precise and scientific, that mathematically quantifies principles that could increase AI performance while keeping risk under control.”
Vempala sees this work on hallucinations as a small first step toward increased AI safety. “Hallucinations are inevitable because LLMs are calibrated to a limited dataset,” he explains. “Until a model sees every piece of information in the world, and assuming every piece of information that it sees is correct, there is a chance it will have to guess the answer to some questions — and that could lead to hallucinations.”
This idea builds on previous research published in 2024 by Vempala and Adam Kalai, then a research scientist at OpenAI and now the cofounder of the Institute for Responsible Superintelligence (RESI), an AI safety nonprofit. The work showed that hallucinations are statistically unavoidable in trained AI models for certain types of data.
Instead of changing the training dataset that an LLM absorbs, the new research focuses on post-training, when the LLM is tested on how well it can answer questions and align with the developer’s goals. During these tests, almost always, the AI model is penalized for saying “I don’t know.” That penalty is the same as if the AI gave a wrong answer.
Just like a student taking a multiple choice test, the model is incentivized to guess when it doesn’t know the correct answer. “This issue is industry-wide,” Vempala says. “The benchmarks and methods being used for evaluation encourage this type of guessing behavior.”
By uncovering the mechanism driving hallucinations, the study provided developers with an easy-to-implement method to mitigate hallucinations in post-training. Specifically, they propose open rubrics, which clearly specify the scoring mechanism for LLM responses.
But hallucinations are just the tip of the iceberg. Now, Vempala is collaborating with psychologists, philosophers, and other experts to see what can be done to ensure that AI behaves in a way that aligns with ethical standards.
For example, many people use LLMs with the model in a specific role: teacher, nurse, tax advisor. Vempala is interested in how to enable role-based abstention. “If the AI is playing a role, like a doctor, how do we ensure that it continues to behave in an ethical way within the scope of that role?” he says. “How can we ensure it’s giving accurate, credible, and ethical information to people, and how can we make sure it declines to answer inappropriate questions?”
Another issue Vempala is working on is called reward hacking, which happens when models try to maximize their “score” results through any means necessary.
In one recent example of this, an OpenAI model was being tested and realized that the answers were available on another website. Rather than do better on the tests, it deployed hundreds of agents to try and steal the test answers.
What do we do to prevent this? How do we understand the possibilities of reward hacking and how do we guard against it? “Some of this comes down to ensuring AIs behave in a way that ethically aligns with our guidelines,” Vempala says. “But it’s also impossible to write down rules to cover every scenario, so it’s vital that we begin to understand what leads to behaviors like reward hacking and how to avoid them.”
Now, AIs are at an important inflection point: they are developing themselves. “Until just a few months ago, humans were deciding what to do next in AI development,” Vempala explains. “Now the AI is self-improving, which makes it even more important to discover and implement these safety protocols.”
The work is not a traditional math problem, he says — it’s a problem for society as a whole. “We can’t just work individually or in small groups on this issue. Everybody needs to pay attention and contribute,” he adds. “Whether you’re working in theoretical mathematics, or ethics, or psychology, developing the principles of AI safety will involve all of us in different ways. There is a real need for people from all walks of life to be involved in this journey.”
DOI: https://doi.org/10.1038/s41586-026-10549-w
Funding: Santosh Vempala was supported in part by the National Science Foundation (NSF) and the Simons Foundation.
]]>“We’re not computers, right?” said Woon Ju Park, a Georgia Tech neuroscientist and assistant professor of psychology.
Park uses the handwriting analogy to explain something about hearing. Listen to the same note again and again, and you may hear or judge it a little differently each time. The sound hasn't changed. Your response to it has.
In a study published in The Journal of Neuroscience, Park and her colleagues Jasmine Awad and Ione Fine tested nine adults who had been blind since birth or before age 2 and 18 sighted adults of similar ages and musical backgrounds.
Volunteers listened to pairs of notes and pressed a button to indicate whether the second was higher or lower. The adults who grew up blind were better at telling the notes apart. But in another test, the groups performed about the same when asked to identify which of two bursts of noise contained a faint tone.
Park suspected the pitch advantage came from more finely tuned hearing, allowing people to pick up smaller differences between notes. But when the researchers used computer models to test possible explanations, they found stronger support for something else: internal noise.
It isn't static or background sound. Internal noise refers to the small variations Park described with her handwritten A's. The models suggested that adults who grew up blind had less of that variation when hearing or judging pitch, which could explain why they were better at telling similar notes apart.
“We really didn't expect internal noise to play a role,” Park said. “We were surprised and wanted to make sure we weren't seeing something that wasn't really there.” The researchers drew that conclusion from the volunteers' answers, not measurements of their brains. They still don't know exactly where the variation arises.
Musical experience showed a similar pattern. Among both blind and sighted volunteers, people with more years of musical training tended to have lower internal noise in the models. But musical training alone couldn't explain the difference between the groups.
Park wants to know whether the same advantage appears in everyday listening, from following conversations in noisy places to recognizing what's happening through sound. She also wants to understand whether experience and practice can change how reliably people distinguish sounds.
“The brain is working really hard to tune its responses to the world that matters to us,” she said.
Park is affiliated with the Institute for Neuroscience, Neurotechnology, and Society. Her research was supported by the National Institutes of Health and Georgia Tech's Smithgall-Watts Early Career Award.
]]>
• Nine adults blind since birth or before age 2 outperformed 18 sighted adults at distinguishing similar notes, while both groups performed similarly when detecting faint tones in noise.
• Computer models linked the pitch advantage to less response variation, not necessarily more finely tuned hearing; musical training showed a similar pattern but did not explain group differences.
• Researchers based the conclusion on behavioral responses and plan to study whether the advantage extends to everyday listening and can change through practice.
]]>Write the letter A 100 times, and no two will look exactly alike. Georgia Tech neuroscientist Woon Ju Park uses this variation to explain “internal noise,” subtle differences in how we perceive or judge the same sound. Her research suggests that people who grew up blind may experience less of this variation, helping them distinguish pitches more accurately.
Karthikeyan Sundaresan is tackling that challenge through Project OMNISCIENT, a three-year effort supported by a $4.8 million award through the National Science Foundation’s Verticals-enabling Intelligent Network Systems (VINES) program.
The project will develop an intelligent wireless network that can adapt as drones move, gather information, and take on different roles.
“The goal is to move beyond thinking about one pilot and one drone,” Sundaresan, a professor in the School of Electrical and Computer Engineering, said. “We want the focus to be on the mission while the drones and the network figure out how to work together.”
Two papers co-authored by Georgia Tech researchers have received the 2026 ACM Internet Measurement Conference (IMC) Test of Time Award, recognizing research with a lasting impact on the field. Among them is The Matter of Heartbleed, a 2014 study co-authored by SCP Professor Michael Bailey and Associate Professor Frank Li.
The paper examined how the internet responded to the Heartbleed vulnerability, one of the most serious security flaws of its time. But its impact extended beyond documenting the incident. A collaboration between researchers at the University of California, Berkeley, and the University of Michigan produced a broad analysis of the security crisis and helped shape a line of research that would influence Li's academic career.
In April 2014, Heartbleed took the internet by surprise. The flaw in OpenSSL, a widely used software library for securing internet communications, allowed attackers to trick vulnerable servers into revealing portions of their memory, potentially exposing passwords, session tokens, and private cryptographic keys.
With just one month before the IMC paper deadline, researchers at Berkeley and Michigan began investigating the vulnerability. They initially pursued separate efforts before learning about each other's work and deciding to combine forces.
Li, then a first-year Ph.D. student at UC Berkeley working with his advisor Vern Paxson, led the Berkeley team. Zakir Durumeric, now at Stanford University, led the Michigan team.
Joining forces enabled the researchers to examine the vulnerability from several angles. They tracked vulnerable servers across the internet, studied the replacement of digital certificates that might have been compromised, and investigated attempts to exploit the flaw.
“We heard about each other’s efforts, talked, and decided to join forces,” Li said. “As a result, our final work was far more comprehensive than what any of us could have done individually.”
One part of the study produced a particularly surprising result. The researchers wanted to know whether directly notifying system operators about vulnerable servers would encourage them to fix the problem. Because Heartbleed had received widespread media attention, the team initially expected the notifications to have little effect.
Instead, operators who received notifications patched vulnerable systems at a rate 47% higher than those who had not yet been notified. Many operators already knew about Heartbleed but had overlooked some servers or had not completed remediation correctly. The researchers found that specific, actionable information could make a difference.
The experiment also led Li down an unexpected research path. He continued studying how security notifications could help organizations address vulnerabilities, including web misconfigurations and compromised websites. He also investigated whether security patches introduced new bugs and examined the human and organizational factors that affect how system administrators handle security updates.
Together, that work formed the foundation of his doctoral thesis and faculty job talk, both focused on internet-scale vulnerability remediation.
“Research paths are highly dynamic, especially for early researchers,” Li said. “Jump on opportunities when they present themselves.”
That lesson has stayed with Li throughout his career. At Georgia Tech, he continues to study how internet operators handle security and privacy, while expanding into areas such as online authentication and AI agent abuse.
For Li, the award is a reminder that an unexpected opportunity early in his career helped shape his research and his career path.
“It’s an honor to get this recognition for the work, which goes all the way back to the start of my academic career,” he said. “I feel fortunate to have been involved in such a fun, interesting, and ultimately impactful project, especially early in my career.”
The Heartbleed paper was not the only Georgia Tech-connected research recognized this year. The conference also honored Analysis of Country-wide Internet Outages Caused by Censorship, a 2011 paper co-authored by Alberto Dainotti, a Georgia Tech professor in the School of Computer Science and adjunct professor at SCP.
The paper examined internet disruptions in Egypt and Libya in 2011, using large-scale internet measurements to understand how governments can disrupt communications across entire countries.
Photos of Frank Li, Michael Bailey, and Alberto Dainotti by Terence Rushin and Kevin Beasley/College of Computing
]]>• The 2014 Heartbleed study found that direct, actionable notifications led operators to patch vulnerable systems at a rate 47% higher than those not yet notified.
• The research launched Frank Li’s career-long work on vulnerability remediation, security notifications, system administration, authentication, and AI agent abuse.
• A second honored paper analyzed internet outages caused by censorship in Egypt and Libya, using large-scale measurements to study government disruption of communications.
Communications Officer at the School of the Cybersecurity and Privacy
]]>The Marcus Center of Excellence for Cell Biomanufacturing recently hosted its inaugural Marcus Center Distinguished Lecture, welcoming more than 160 attendees in person and virtually.
The lecture featured Dr. Marcela Maus, Professor of Medicine at Harvard Medical School and Director of the Cellular Immunotherapy Program at Mass General Brigham Cancer Institute. In her presentation, “Designing the Next Generation of CAR-T Cells,” Dr. Maus shared the evolution of chimeric antigen receptor (CAR) T cell therapies and their growing impact on cancer treatment.
“Dr. Maus is a true leader in bringing innovations in CAR-T therapies to patients through her outstanding work leading to several first-in-human trials. We were honored and excited to welcome her to the Marcus Center for Cell Biomanufacturing at Georgia Tech for this inaugural lecture,” stated Dr. Johnna Temenoff, Marcus Center Director.
Drawing on her pioneering work in translation of cellular immunotherapies, Dr. Maus discussed how engineered T cells have become a standard treatment for certain blood cancers, including lymphoma and multiple myeloma. She presented innovative CAR designs, including strategies to enhance T cell function and persistence. Dr. Maus also shared ongoing efforts to overcome challenges such as treatment resistance and tumor targeting.
Following the lecture, attendees had the opportunity to continue discussions during a community lunch and poster session, supporting collaboration and networking among members of the Atlanta cell biomanufacturing and immunotherapy community.
The Marcus Center of Excellence for Cell Biomanufacturing recently hosted its inaugural Marcus Center Distinguished Lecture, welcoming more than 160 attendees in person and virtually. The lecture featured Dr. Marcela Maus, Professor of Medicine at Harvard Medical School and Director of the Cellular Immunotherapy Program at Mass General Brigham Cancer Institute.
]]>Media Contact:
Ashlie Bowman | Communications Manager
Parker H. Petit Institute for Bioengineering and Bioscience
]]>Now, Nick Housley is exploring whether another bodily system could be recruited in the fight against cancer: the nervous system.
“From first principles, the nervous system is involved in every aspect of normal development and bodily maintenance,” says Housley, an assistant professor in the School of Biological Sciences and faculty director of Innovation for the Institute for Neuroscience, Neurotechnology, and Society. “When these normal processes go awry, the nervous system is not just a bystander. It is actively driving changes and/or responding to disease.”
With a new five-year, $3 million Stephen I. Katz Award from the National Institutes of Health, Housley aims to uncover how cancer interacts with the body’s neural circuitry and whether those connections could ultimately reveal new ways to fight the disease.
The idea that cancer and the nervous system interact isn’t entirely new. Scientists have known for more than a century that many solid tumors are connected to nerves. More recently, studies of brain cancer have revealed that tumors can form circuits with neurons that affect cancer growth, invasion, and resistance to treatment. But exactly how cancers elsewhere in the body connect with and potentially exploit the nervous system is largely a mystery.
Housley is starting with the ovary, an organ especially reliant on cues from the nervous system for normal function. Ovarian cancer is also one of the leading causes of cancer death among women, making the need for new approaches especially urgent.
“Ovarian cancer is tricky because it disproportionately lacks clear early symptoms,” says Housley. Without reliable symptoms or an effective early screening method, the disease is often not detected until later stages, when it is more difficult to treat. “We are very interested in understanding how the tumor innervates and integrates into the host nervous system to modulate activity patterns and remain hidden.”
Yet even the baseline for understanding those connections is missing. Scientists don’t yet have a complete map of the neural circuitry of a healthy ovary, much less an understanding of how that circuitry changes when cancer develops.
That kind of knowledge gap is precisely what the National Institutes of Health’s Stephen I. Katz Award is designed to address. It empowers early-career scientists like Housley to make bold research pivots into new scientific fields without requiring preliminary data.
With the Katz Award, Housley will start by creating the missing neural map of the ovarian system, comparing neural connections in healthy and cancerous ovaries and tracing them from local networks to the spinal cord and brain.
“We’re trying to figure out who’s connected to whom and whether those structural connections are functional,” he said.
From there, his team will examine how ovarian cancer cells and neurons communicate and how those interactions affect both cell types. Finally, they will manipulate specific populations of neurons to test how neural activity affects tumor development, progression, and response to cancer treatments.
“Where we are right now with cancer neuroscience is very similar to where immunotherapy was several decades ago,” Housley said. “Our blue-sky goal is to develop enough foundational knowledge about how the nervous system interfaces with ovarian cancer that we can exploit it — suppressing pro-tumoral signals and enhancing tumor suppressors to improve patient outcomes.”
The committee, convened through the National Academies' project Future of Battery Technology Options for Defense Applications, will identify the strengths and weaknesses of future battery technologies, including an examination of performance, safety, and manufacturability across technology and manufacturing readiness levels. The committee will also identify gaps where research investments could potentially improve battery capabilities across technology and manufacturing readiness levels, creating opportunities to leverage commercially available technologies.
With a joint appointment in MSE and the George W. Woodruff School of Mechanical Engineering, McDowell is internationally recognized for his research on batteries and energy storage materials. His work focuses on understanding how materials change during battery operation and using that knowledge to develop safer, more efficient, and more sustainable energy storage systems. McDowell is also co-director of the Georgia Tech Advanced Battery Center. He leads research spanning solid-state batteries, lithium-ion and sodium-ion technologies, and next-generation energy storage materials. “I am very thankful to be selected, and I look forward to working with colleagues on developing recommendations to advance battery technologies in support of our country," said McDowell.
Read Full Story on the MSE Newspage
]]>The committee, convened through the National Academies' project Future of Battery Technology Options for Defense Applications, will identify the strengths and weaknesses of future battery technologies, including an examination of performance, safety, and manufacturability across technology and manufacturing readiness levels. The committee will also identify gaps where research investments could potentially improve battery capabilities across technology and manufacturing readiness levels, creating opportunities to leverage commercially available technologies.
With a joint appointment in MSE and the George W. Woodruff School of Mechanical Engineering, McDowell is internationally recognized for his research on batteries and energy storage materials. His work focuses on understanding how materials change during battery operation and using that knowledge to develop safer, more efficient, and more sustainable energy storage systems. McDowell is also co-director of the Georgia Tech Advanced Battery Center.
]]>“Her outstanding research accomplishments and contributions to the School and Georgia Tech led to this selection,” said Professor Christopher W. Jones, the John F. Brock III School Chair in ChBE@GT.
The $20,000 in discretionary funding from this one-year fellowship will support Jamali’s research activities focused on developing new tools for in situ liquid-phase transmission electron microscopy, stochastic thermodynamics, and nanoscience-based platforms.
The Spencers established the endowment from which the term fellowship funding comes in 2017. This endowment will eventually lead to the establishment of a professorship in ChBE@GT.
“Bob Spencer is a successful alumnus who has remained connected to our chemical engineering program,” according to Jones. “His family’s gift will allow ChBE@GT to support an early career professor at a critical stage of their development—the crucial years just before their promotion and tenure review. We are grateful for their support and generosity.”
Read Full Story on the ChBE Newspage
]]>“Her outstanding research accomplishments and contributions to the School and Georgia Tech led to this selection,” said Professor Christopher W. Jones, the John F. Brock III School Chair in ChBE@GT.
The $20,000 in discretionary funding from this one-year fellowship will support Jamali’s research activities focused on developing new tools for in situ liquid-phase transmission electron microscopy, stochastic thermodynamics, and nanoscience-based platforms.
]]>Hosted by the Strategic Energy Institute (SEI), the event brought together stakeholders from across the hydrogen value chain to address opportunities and challenges related to infrastructure, market development, technology deployment, and regional collaboration.
The program began Oct. 7 with a networking reception and hydrogen research poster session, sponsored by the Southeast Hydrogen Energy Alliance (SHEA). Researchers, industry leaders, policymakers, and students gathered for collaboration and discussion.
On Oct. 8, Yuanzhi Tang, SEI’s executive director and Georgia Power Professor, delivered opening remarks, followed by Tricia Chastain, executive vice president for administration and finance and chief business officer at Georgia Tech, who offered an institutional perspective.
“Georgia Tech is uniquely positioned to help advance hydrogen because we bring together expertise across engineering, transportation, manufacturing, policy, economics, and sustainability,” Chastain said. “Our strength lies not only in those disciplines, but in our ability to connect them, collaborate with partners, and move innovations from research into real-world applications.”
Frank Wolak, president and CEO of the Fuel Cell and Hydrogen Energy Association, delivered a keynote address on the state of hydrogen in the United States. He discussed national trends, policy developments, and market opportunities that could influence hydrogen adoption and create opportunities for the Southeast.
“Convening this forum on World Hydrogen Day highlights both the growing global momentum behind hydrogen technologies and the Southeast’s unique opportunity to help shape their development, deployment, and long-term impact,” Wolak said.
A leadership panel brought together Quinta Warren, airport senior director of sustainability at Hartsfield-Jackson Atlanta International Airport; Dan Raudebaugh, executive director of the Center for Transportation and the Environment; Erin Lane, vice president of public affairs at Plug Power; Costas Simoglou, director of Energy Technology at the Georgia Center of Innovation; and John Knox Porter Jr., CEO of Capital Development Partners.
Panelists discussed hydrogen's potential to strengthen industrial competitiveness and energy security, support transportation decarbonization, and contribute to regional economic growth.
“One of the most important questions facing the hydrogen sector is how we work together to address the challenges ahead,” said Tang. “At Georgia Tech and the Strategic Energy Institute, our role is to bring the ecosystem together. We not only advance research and innovation, but also connect people, technologies, and partnerships that can turn ideas into real-world solutions.”
Developing a Regional Hydrogen Road Map
The event’s centerpiece was the Southeast Hydrogen Roadmapping Forum, organized and led by Scott McWhorter, director of the National Laboratory Partnership Program and Federal Energy Initiatives at the Strategic Energy Institute. McWhorter also serves as chairman of the SHEA Board of Directors.
Participants worked through facilitated discussions across three strategic focus areas:
The discussions identified technology gaps, infrastructure priorities, workforce needs, demonstration opportunities, and pathways for future investment.
"The goal of this forum was to move beyond discussion and identify tangible opportunities for collaboration,” said McWhorter. “By bringing together leaders from transportation, energy, industry, economic development, and research, we are able to develop a road map that highlights priority projects, infrastructure needs, and next steps for growing a hydrogen economy that serves the Southeast."
The road-mapping sessions concluded with a cross-track synthesis focused on identifying priority projects and defining next steps toward a coordinated regional hydrogen strategy.
Showcasing Georgia Tech Hydrogen Research
Attendees also connected with Georgia Tech researchers through a hydrogen research showcase organized by Comas Haynes, Georgia Tech's hydrogen initiative lead and a principal research engineer at the Georgia Tech Research Institute. The showcase included guided tours of the North Avenue Research Area and the Ben T. Zinn Combustion Laboratory. Participants got an up-close look at hydrogen research underway across the Institute.
The tour highlighted Georgia Tech's growing hydrogen research portfolio and the Institute's capacity to support industry, federal agencies, and regional partners working to advance next-generation energy technologies.
“By convening the forum on World Hydrogen Day, Georgia Tech underscored both the global momentum behind hydrogen technologies and the region's opportunity to shape their future deployment,” said Haynes.
The event’s outcomes will inform a regional hydrogen road map and white paper intended to support future collaboration, investment, and deployment efforts across the Southeast.
“This is only the beginning,” said McWhorter. “The road map will help guide the partnerships and projects needed to advance hydrogen infrastructure and strengthen the region's energy future.”
]]>Hosted by the Strategic Energy Institute (SEI), the event brought together stakeholders from across the hydrogen value chain to address opportunities and challenges related to infrastructure, market development, technology deployment, and regional collaboration.
]]>Through a donation from IBM, Georgia Tech’s Center for Scientific Software Engineering (CSSE) and Open Source Program Office (OSPO) held a fellowship competition for students to work with mentors at CSSE and OSPO to create the tool. Master’s students Adrian Lozada and Di Wu were selected as fellows to work on the project.
The Mellea Legal Requirements Checker (Mellea-LRC) can quickly identify and accurately verify case law citations, specifically checking for citations that are hallucinated by artificial intelligence (AI). One fellowship goal was to give lawyers and others in the legal field a tool to easily verify legal citations. Mella-LRC does this by using both LLMs and IBM’s Mellea open-source framework to verify and repair LLM prompts.
The team tested the tool on 26 public court-filing documents containing falsified citations. Mellea-LRC can process a document in about eight minutes. The tool first extracts the case law citations from the legal document. It then verifies that each citation is authentic and supports the document's content.
“IBM’s Mellea framework was the foundation we built it on. Mellea’s job is to make model calls predictable: you write the rules the output must satisfy as ordinary code, and the framework retries until LLM output meets them. Our job was to leverage the framework to build the legal application from end to end,” Wu said.
An important aspect of the project was ensuring the tool’s code was open source. The team supported this goal by also creating and releasing a new test and validation dataset on Hugging Face – a popular open-source AI development community – for future benchmarking studies.
“Agentic AI is growing quickly, and much of the growth happens in open-source projects, where anyone can read, use, and improve the work,” Lozada said.
OSPO Director and Principal Research Scientist Jeff Young noted that IBM’s Mellea framework was critical to this work in that its “instruct, verify, repair” paradigm allows for the creation of reliable LLM loops as well as the use of small language models (SLMs), such as IBM’s Granite, which can be run on a laptop.
“This project demonstrates the power of open-source models like IBM Granite as well as the importance of using novel software engineering and algorithmic techniques from the Mellea project to improve the reliability of our existing LLMs and SLMs.
“Mellea-LRC provides a compelling example of AI’s potential to evolve from a source of error in the legal profession into a trusted ally by helping lawyers work faster and cite precedents more accurately,” Young said.
]]>Through a donation from IBM, Georgia Tech’s Center for Scientific Software Engineering (CSSE) and Open Source Program Office (OSPO) held a fellowship competition for students to work with mentors at CSSE and OSPO to create the tool. Master’s students Adrian Lozada and Di Wu were selected as fellows to work on the project.
The Mellea Legal Requirements Checker (Mellea-LRC) can quickly identify and accurately verify case law citations, specifically checking for citations that are hallucinated by artificial intelligence (AI). One fellowship goal was to give lawyers and others in the legal field a tool to easily verify legal citations. Mella-LRC does this by using both LLMs and IBM’s Mellea open-source framework to verify and repair LLM prompts.
U.S. Commerce Secretary Howard Lutnick said, “Hurricane Helene left Georgia growers with damaged timber and exposed weaknesses in their supply chains. With this federal funding, backed by $24 million in private investment, Georgia Tech is exploring how to turn that timber into valuable ag-nutrients and testing ways to keep supply chains moving even when storms hit.”
The ReGEN Ag project funding is part of a larger initiative, the EDA Fiscal Year 2025 Disaster Supplemental Grant Program. The ReGEN Ag award supports two initiatives that will be implemented over an 18-month period.
Resilient Routes, headed by SCL, will incorporate modeling with live mapping of critical infrastructure and routes to create cooperative logistics hubs. “For decades, SCL has led applied supply chain research that solves real problems for industry,” said SCL Managing Director Chris Gaffney. “Partnering with RBI on ReGEN Ag lets us put that experience to work for Georgia's forestry sector, building cooperative logistics that connect South Georgia's timber to new, higher-value products and markets.”
ReWOOD, led by the RBI-associated Center for a Renewables-Based Economy From Wood (ReWOOD) aims to turn low-grade timber and wood waste into value-added chemicals and bioproducts. “The ReWOOD initiative builds on RBI’s tremendous strength in wood-based products to create additional revenue sources for Georgia’s forestry industry by developing processes and products to benefit human and animal health and well-being, including new materials, animal feed, care products, and many other applications,” said Andreas Bommarius, ReWOOD co-director.
Timber and its related industries play a significant role in Georgia’s economy. According to the Georgia Forestry Association, the sector contributes $41.3 billion a year to the state’s economy and supports nearly 144,000 direct and indirect jobs.
EI² Vice President David Bridges said the ReGEN Ag project complements the unit’s broader commitment to supporting socioeconomic development across the entirety of Georgia.
“When EI² conducted a listening tour of the state, we heard specifically from timber industry owners and companies in South Georgia about the need for finding and developing value-added products,” Bridges said. “This funding provides a chance to explore some of those pathways, while building resilience and boosting prosperity in the southern part of the state.”
The award also allows Georgia Tech to work closely with two of its educational partners, South Georgia State College and Wiregrass Georgia Technical College, to build workforce opportunities in forestry, agriculture, biomanufacturing, and supply chain management.
“EDA’s investment, along with significant private industry and local partner commitments, gives us a real opportunity to help rural communities recover from storms and grow stronger,” said Betsy McGriff, EI² program manager. “We’re grateful to EDA and to the partners across South Georgia who came together to make this possible, and we’re excited to get started.”
]]>The U.S. Department of Commerce’s Economic Development Administration (EDA) is awarding $7.4 million in disaster supplemental funding to the Resilient Growth Through Enabling Next Generation Agriculture (ReGEN Ag) coalition.
]]>Unlike traditional AI backdoors, which manipulate a model's learned parameters, architectural backdoors hide malicious instructions directly in the code that defines how the model operates.
However, everyday image-processing operations, such as cropping, adjusting contrast, or adding noise, can change a trigger pattern and prevent an attack from working, according to new research from Georgia Tech.
The findings challenge assumptions about how practical these attacks are. Although previous research showed that architectural backdoors could work under controlled conditions, the Georgia Tech team found that existing approaches struggle to remain effective and difficult to detect when AI systems process images under realistic conditions.
“The biggest misconception is that demonstrating an architectural backdoor under controlled conditions means it will actually work in the real world,” said David Oygenblik, Ph.D. student and lead author of the study.
The study details the development of FAULT, a framework for evaluating architectural backdoors under realistic conditions.
The findings reveal a tradeoff. Attackers can make a backdoor more sensitive, so it recognizes its trigger after an image has been changed. But that also increases the chance that ordinary images will accidentally activate the backdoor, potentially hurting the AI system’s performance.
“For the architectural backdoors we study, this tradeoff is fundamental,” Oygenblik said.
The team found that this problem persisted across five methods of implementing architectural backdoors. Even when attackers knew how the system would process images, they struggled to make their attacks both reliable and difficult to detect.
The research did not test attacks against real vehicles or other production systems, nor did it demonstrate outcomes such as crashes or ransomware. Instead, it examined whether existing architectural backdoors could reliably activate under different image-processing conditions.
However, the findings highlight a potential risk in the AI software supply chain. If an attacker inserted malicious code into an AI model used in a real system, the backdoor could potentially cause incorrect predictions when its trigger was detected. The consequences would depend on how the system used the model’s output.
Because architectural backdoors hide in code, examining a model’s learned parameters or retraining it may not be enough to uncover or remove the threat.
Oygenblik said developers should test AI systems under realistic conditions, watch for unexpected drops in accuracy, and examine model code for suspicious trigger-detection logic.
Finding FAULTs in Architectural Backdoors: Why Trigger Detection Fails Under Real-World Conditions, was accepted to the ACM Conference on Computer and Communications Security. The authors will present the paper in The Hague in November.
Oygenblik conducted the research with undergraduate students Teja Akella and Tanmay Gupta, Ph.D. student Yizhi Huang, and Associate Professor Brendan Saltaformaggio of Georgia Tech’s Cyber Forensics Innovation Laboratory. The lab is a collaboration between the School of Cybersecurity and Privacy and the School of Electrical and Computer Engineering.
]]>• Cropping, contrast changes, and similar transformations can disrupt visual triggers across five backdoor methods.
• Increasing trigger sensitivity improves reliability but also raises accidental activations and may reduce system performance.
• The study warns that parameter inspection or retraining may miss code-based threats, urging realistic testing and code reviews for suspicious trigger logic.
Communications Officer for the School of Cybersecurity and Privacy
]]>Jiayun (Peter) Wang began his tenure-track career on Oct. 15 as an assistant professor in the School of Computational Science and Engineering (CSE).
At Georgia Tech, Wang will develop new AI tools to help doctors make better use of complex medical data. His research aims to transform information from medical images, clinical measurements, and patient records into clearer insights that improve diagnosis, treatment, and patient care.
“I’m excited to build a lab at Georgia Tech, and to work with students and collaborators on new ideas,” Wang said. “I hope our research can connect fundamental advances in AI with real challenges in healthcare and science.”
Before starting at Georgia Tech, Wang conducted postdoctoral research at Caltech and worked as a senior research scientist at Accenture. He earned his Ph.D. in 2023 from the University of California, Berkeley.
Much of Wang’s healthcare research builds on computer vision, which enables machines to interpret images and videos.
For example, lung ultrasound is a fast, portable, and radiation-free way to check breathing problems. However, a drawback is that images can be hard to read.
Wang led the development of LUNA, an AI method that converts raw ultrasound signals into maps showing how air is distributed in the lungs. This approach makes bedside lung exams more consistent and easier to interpret.
Wang has also used AI to improve another common type of medical imaging: MRI.
MRI scans can take time to complete, and analyzing the results can take even longer. Patients may find it uncomfortable to lie still in a scanner and waiting for results can add stress during an already difficult time. Long scans and reviews can also make it harder for doctors to schedule procedures and consult specialists.
To overcome this shortfall, Wang worked on a team that built a single, flexible AI model that reconstructs high-quality MRI images from fewer measurements across different scanning settings. Along with enabling faster scans, the approach preserves the details doctors need to make informed decisions.
Surgeon training is another way Wang has helped doctors using computer vision techniques.
During robot-assisted surgery, trainees receive guidance from experienced surgeons. However, it is difficult to know what advice improves techniques. A surgical-training study that Wang co-authored combined video and spoken feedback to assess trainee learning.
Wang has used less serious clinical conditions to improve quality of life through AI. Dry eye is one of the most common reasons people visit eye clinics, yet the condition is difficult to assess.
Working with collaborators at UC Berkeley, Wang studied AI methods to analyze patient information alongside images of tiny glands in the eyelids. This work contributed to AI tools that assist in diagnosing ocular surface diseases and predicting dry eye onset based on lifestyle factors.
Beyond healthcare, Wang also works to make AI easier to train and use. His research helps models learn from images without extensive human labeling and build strong systems that require less computing power.
“Medical measurements are often noisy, incomplete, or difficult to interpret. Yet they can carry information that matters for doctors and patients,” said Wang.
“I’m motivated by the opportunity to combine what we know about the physical world with new learning methods to build AI systems that are more reliable and useful.”
Looking ahead, Wang is building the SWI Lab (science, world models, and intelligence) at Georgia Tech.
The lab develops AI “world models” that learn how physical and biological systems behave, predict how they change, and help researchers draw insights from incomplete measurements. This work connects fundamental AI advances with challenges in medicine and science.
Ph.D. students Xinsong Feng and Wentao Zhou joined SWI Lab this fall as its inaugural members. The lab welcomes prospective students, research interns, and visitors interested in world models and Wang’s work.
“The opportunity to work across computing, engineering, and science attracted me most to Georgia Tech,” Wang said.
“The most interesting problems often require both new AI ideas and deep knowledge of their applications. I look forward to studying those problems through new relationships and collaborations.”
]]>Jiayun (Peter) Wang began his tenure-track career on Oct. 15 as an assistant professor in the School of Computational Science and Engineering (CSE).
At Georgia Tech, Wang will develop new AI tools to help doctors make better use of complex medical data. His research aims to transform information from medical images, clinical measurements, and patient records into clearer insights that improve diagnosis, treatment, and patient care.
]]>The proof uses mathematical techniques developed by Alexander Dunn, the Richard A. Duke Assistant Professor in the School of Mathematics, and Maksym Radziwiłł, professor of mathematics at New York University. Dunn and Radziwiłł developed the tools while working to resolve a different problem in number theory.
“Seeing our tools used in OpenAI’s proof was unexpected,” says Dunn.
He believes OpenAI’s so-called “11/12 manuscript” is correct and is working alongside other mathematicians to review the proof and its sources.
“We are seeking to understand what makes the model’s arguments work and how far its method can go,” says Dunn. “But it is too early to say whether it will help resolve the full Riemann hypothesis.”
Proposed by 19th-century mathematician Bernhard Riemann, the full Riemann hypothesis has remained unsolved for more than 160 years, and is one of the most prominent problems in theoretical mathematics, according to Michael Wolf, chair of the School of Mathematics.
Even if OpenAI’s method does not resolve the full hypothesis, the 11/12 manuscript may still have broader implications for mathematics.
“The present work by OpenAI, while not the whole problem, is both remarkable progress and deeply impactful; the entire mathematical community is buzzing about this development,” says Wolf. “Years ago, Alex decided to chart a novel course in his research — a brave move for a young researcher. It is so gratifying to see his boldness yield such strong results. We are thrilled that he is part of our Georgia Tech mathematical community.”
]]>OpenAI’s proof draws on techniques developed by mathematicians, including Georgia Tech’s Alexander Dunn.
]]>Led by Thomas, HEAL brings together scientists, clinicians, and research institutions across the United States, as well as partners in Finland and Australia, to develop new approaches for treating lymphatic diseases.
]]>George W. Woodruff School of Mechanical Engineering
]]>Andrei Fedorov and his team have found a way to take some of the guesswork out of mass spectrometry imaging (MSI), potentially giving scientists better tools to explore the molecules that influence our health.
A small sample of human tissue can hold a remarkable amount of information.
Researchers can use it to search for molecular clues associated with cancer, investigate the chemical landscape of the brain, or determine where a drug travels after it enters the body. Mass spectrometry imaging, or MSI, helps answer those questions by mapping where different molecules are located within tissue.
But there's a catch. Despite MSI's sophisticated capabilities, finding the right conditions to get useful results can still require a considerable amount of trial and error. Georgia Tech professor Andrei Fedorov and Ph.D. student John Sentmanat are working to change that.
“Mass spectrometry imaging is probably the most powerful tool to enable new discoveries in cell biology and protein biochemistry. It helps provide a direct insight not only to how the body works but also the underlying cause of disease,” said Fedorov, Associate Chair for Graduate Studies and Rae S. and Frank H. Neely Chair in the George W. Woodruff School of Mechanical Engineering. “But the techniques for using it were evolving in a very empirical manner guided by experience and intuition. It’s like shooting arrows in the dark.”
In response to this barrier, the team has developed what Fedorov likens to a recipe, a framework designed to help researchers understand how different ingredients and conditions work together to produce the molecular information they want. Published in Analytical Chemistry, the approach could make MSI more predictable and give scientists a better starting point for developing new ways to study the molecular workings of the human body.
“This paper provides a very simple recipe that everyone can read and use. You don’t need to be a chef, or in this case, be able to write complicated equations,” Fedorov said. “It even allows you to come up with a new recipe using our model as the base.”
Though the framework was designed to be accessible to researchers across the field, Fedorov and Sentmanat didn’t set out to solve a problem for the scientific community — they were trying to solve one in their own lab.
In 2020, Fedorov, who is also a faculty member in the Parker H. Petit Institute for Bioengineering and Bioscience, was awarded $1.2 million from the National Institutes of Health (NIH) for the development of a new imaging instrument that could change the study of tumor growth, disease progression, and cell function.
The technology, called BeamMap, has continued to develop with additional support from the National Science Foundation Engineering Research Center for Cell Manufacturing Technologies (CMaT), led in part by Georgia Tech. By bringing together multiple imaging techniques, including MSI, BeamMap allows researchers to study both the physical surface of a biological sample and its molecular makeup.
While developing the instrument, Fedorov and Sentmanat encountered the same challenge that has made MSI difficult to optimize: Under some conditions, they successfully extracted the molecules they wanted to study. Under others, they damaged a sample without getting the information they needed. Rather than continue relying on trial and error, the team decided they needed a theory that could point them toward the right conditions.
“As we continued developing the instrument, we realized we needed to develop a theory to identify the optimal operating conditions,” Sentmanat said. “What began as an effort to fine-tune our own technology led to a broader theory that can be applied to a wide range of other approaches.”
To build the recipe, the team returned to the basic physics that determines when molecules leave a sample and become available for detection. They distilled those complex interactions into a simpler framework, then compared its predictions with experimental data from previously published studies. When the framework held up across different MSI approaches, the researchers realized the recipe could be useful well beyond their own lab.
“It's all measurable data that any scientist in this field would be able to use,” Fedorov said. “It’s like having a magic tool that allows you, all of a sudden, not to be blind.”
Fedorov sees the new framework as one step toward making MSI easier to understand and use. By giving researchers a better starting point for choosing how to operate an MSI system, the recipe could help them spend less time searching for the right conditions and more time using the technology to answer biological questions.
That could become increasingly important as medicine moves toward understanding disease and treatment at the molecular level.
“More and more, physicians base their diagnoses on much more specific molecular information,” Fedorov said. “The drugs of the future will not be this little pill that you will be given; they will be your own immune cells. Your diagnostic tools have to match that future.”
For now, the framework is intended primarily as a tool for researchers. But by helping scientists make better use of technologies like MSI, Fedorov hopes the work can contribute to discoveries that ultimately improve how diseases are understood, detected, and treated.
Like any recipe, the framework leaves room for adjustment. The team deliberately simplified some of the complex physics behind MSI to make the framework practical for other researchers, which means it is designed to point them toward promising conditions rather than predict exactly what will happen in every experiment.
“The theory provides a recipe that researchers can adapt by adding their own flavors,” Sentmanat said. “Rather than prescribing an exact solution, it offers a framework for identifying the right ingredients and refining the conditions to achieve the best results.”
Researchers can adapt that starting point to their own instruments, samples, and questions. What began as an effort to improve BeamMap could ultimately help others refine existing MSI technologies or develop new approaches of their own.
“It’s kind of empowering.”
Researchers can use a small sample of human tissue to search for molecular clues associated with cancer, investigate the chemical landscape of the brain, or determine where a drug travels after it enters the body. Mass spectrometry imaging, or MSI, helps answer those questions by mapping where different molecules are located within tissue. But there's a catch. Despite MSI's sophisticated capabilities, finding the right conditions to get useful results can still require a considerable amount of trial and error. Georgia Tech professor Andrei Fedorov and Ph.D. student John Sentmanat are working to change that.
]]>Parker H. Petit Institute for Bioengineering and Bioscience
]]>Georgia Tech researchers have developed a tool that can recover deleted conversations from AI assistants running on Android phones. The tool, called ORISA, can also rebuild the recovered information into a working AI session.
The findings show that deleting an AI conversation on a phone does not necessarily mean it removes every trace.
The research could give digital investigators a new way to recover information from phones. It also raises privacy concerns for people who use AI assistants that run locally on their devices.
Local AI assistants run directly on a phone rather than sending conversations to a cloud service. While the local assistant is running, information from conversations can remain in the phone’s working memory even after it is deleted.
ORISA searches this memory for pieces of deleted conversations.
In one experiment, researchers created a fictional AI assistant called “Project Note Keeper” using the ChatterUI Android app. They gave it 100 fictional facts about a project, then deleted the conversation.
ORISA recovered information from the deleted conversation and used it to create a new working session. When researchers asked the restored assistant to list the project notes it had been given, it returned 26 facts. The original session could access only 14 facts because the rest had fallen outside its active memory.
The experiment showed that researchers could recover information the AI had already stopped actively using.
“It can help establish what information someone shared with an AI assistant and what assistance they received,” said Ph.D. student Ken Xu, lead author of the study.
The researchers tested ORISA with 10 Android apps and three AI models. Across 60 test configurations, the tool recovered conversation information that remained in the phone’s memory.
The researchers say the information becomes harder to recover as the phone’s memory is overwritten by other activity.
The research was presented at the 2026 IEEE Symposium on Security and Privacy. The paper, titled Recovering and Rehosting Mobile Local LLM Conversations and Contexts via Memory Forensics, was authored by Ph.D. students Xu, David Oygenblik, Runze Zhang, and Mingxuan Yao; Research Scientist Muhammad Ibrahim; and Associate Professor Brendan Saltaformaggio. The work was done in Georgia Tech's Cyber Forensics Innovation Laboratory, a collaboration between the School of Cybersecurity and Privacy and the School of Electrical and Computer Engineering.
]]>In a study accepted for the 2026 ACM Conference on Computer and Communications Security, Georgia Tech researchers interviewed 20 military sailors about their cybersecurity experiences, training, and responses to hypothetical scenarios. Their findings point to a gap between how mariners are trained to handle emergencies and how cyberattacks can compromise the systems they depend on.
The study found several gaps in how crews prepare for cyber threats:
These gaps matter because cyberattacks can compromise a system without causing it to stop working. For example, an attacker could manipulate navigation data, leaving a crew to make decisions based on false information.
“I’d assume it was anything but cyber at first. It would probably take me quite some time to get to that conclusion,” one participant told the researchers.
The team examined three hypothetical scenarios: GPS spoofing, loss of propulsion control in a high-traffic area, and failure of electronic navigation systems in a congested channel at night.
In each scenario, mariners would first focus on keeping the vessel safe, using established procedures to stabilize the ship and troubleshoot its systems. While this response is essential during an emergency, it could delay recognition of an attack if crews do not consider that the system or its data may have been compromised.
For example, a ship navigating a narrow channel depends on accurate location information, but what happens when its navigation systems appear to work normally while a hacker manipulates that data?
An attacker could use GPS spoofing to falsify a vessel’s reported position. If the false position is close enough to the ship’s actual location, a mariner might not notice anything wrong. The vessel could gradually head toward shallow water or another obstacle without triggering an obvious error or alarm.
“By the time the mariner realizes something is wrong, the ship’s size and limited maneuverability could make it too late to avoid a grounding or collision,” said Anna Raymaker, a Georgia Tech Ph.D. student who studies maritime security.
The scenario illustrates a central challenge in maritime cybersecurity: An equipment failure may be easy to recognize, but a cyberattack that provides false information can be much harder to detect.
Batten the Hatches: Cybersecurity with Military Mariners was written by master’s student Ryan Von Brock, Raymaker, Research Scientist Animesh Chhotaray, Associate Professors Frank Li and Saman Zonouz, and Provost & Executive Vice President for Academic Affairs Raheem Beyah.
The research was conducted in Georgia Tech’s Cyber-Physical Security Lab, a collaboration between the School of Cybersecurity and Privacy and the School of Electrical and Computer Engineering.
Photos by Terence Rushin/College of Computing
]]>New research from Georgia Tech suggests that a simple change to a chatbot’s instructions could reduce that risk. The work was accepted to the ACM AI Letters publication.
Researchers Lorenzo de la Loza and Vijay Madisetti tested eight AI models in 1,280 experiments involving simulated conversations about delusional beliefs. They found that instructions designed to discourage excessive agreement reduced the models’ confirmation of those beliefs by 73.8%. Adding a self-reflection step increased the reduction to 77%.
“We think that this paper will help AI providers and solution creators better understand how best to protect and safeguard their users from harming themselves,” Madisetti said. “This may make AI safer for all of us.”
AI chatbots are designed to be helpful and supportive. But that behavior can become risky when a chatbot agrees with a user’s beliefs without questioning whether they reflect reality. Researchers call this behavior sycophancy.
Courtney Crooks, a principal research scientist at the Georgia Tech Research Institute and adjunct faculty member in Georgia Tech’s School of Cybersecurity and Privacy, said chatbot conversations can have both positive and negative effects.
People may feel more comfortable discussing difficult thoughts with a chatbot than with another person. But if the chatbot always agrees, users may miss opportunities to question their beliefs or consider other points of view.
The same behavior that makes a chatbot feel supportive, Crooks explained, can also encourage harmful patterns of thinking.
The researchers tested instructions that told AI models not to reinforce users’ beliefs simply to be agreeable. The team evaluated the models using 16 clinically derived scenarios involving delusional beliefs.
The team also tested other safety tools, including systems designed to flag potentially harmful content. The results suggest that changing a chatbot’s instructions can be an effective way to reduce excessive agreement in the scenarios tested.
Crooks called the findings a promising direction for future research combining psychology and AI safety.
The study did not test people in clinical settings or prove that the approach prevents real-world harm. However, it offers developers a potential way to make chatbots more careful when responding to vulnerable users without building an entirely new AI model.
]]>Communications Officer for the School of Cybersecurity and Privacy
]]>A team of computer scientists and doctors led by Georgia Tech aims to change that. Using a system of artificial intelligence (AI) models, the team can help clinicians deliver the right intervention to the right patient at the right time.
Their system uses Restless Multi-Armed Bandit (RMAB) models. While the name is technical, the idea is simple. The RMAB framework helps decision-makers choose the best actions over time when conditions are complex and constantly changing.
This project will tackle Type 2 Diabetes (T2D), building on previous experience expanding RMAB models to support maternal health care in India. Success on this front could lead to treating other chronic illnesses, like hypertension, heart disease, kidney disease, and mental health.
Recognizing the RMAB system’s potential, the National Institutes of Health (NIH) awarded the group an R01 grant. The award will fund the project with $1.2 million through 2029.
“Our goal is to address the immense challenge of allocating limited health intervention resources in optimal ways,” said Kai Wang, an assistant professor in the School of Computational Science and Engineering (CSE).
“By leveraging rich contextual data and accounting for social determinants, we envision RMAB models that empower health centers to customize interventions to individual patient profiles. Ultimately, this advances precision medicine and ensures equitable healthcare access for diverse populations.”
T2D is a diabetes condition where the body resists insulin or doesn’t produce enough to regulate blood sugar levels. Left unmanaged, high blood sugar leads to severe health problems like heart disease and stroke, damage to organs like eyes and kidneys, nerve damage, infections, and ulcers.
T2D is challenging to treat because patients have different ages, genetics, lifestyles, and body composition, all of which affect the progress of the disease. Social factors, like transportation and family support, matter just as much as biology to treat the disease.
For these reasons, patients who get the same medications may get very different results. While treatment plans now incorporate new GLP-1 drugs, they remain expensive and difficult to distribute equitably.
“Diabetes is a great example of a complicated, multi-faceted problem. It is a natural playground for the kind of high-dimensional machine learning algorithms we want to build and deploy,” said School of CSE Professor B. Aditya Prakash.
“As a chronic disease, diabetes also creates opportunities for sequential decision-making. Providers are not making just one decision to treat the condition, but rather a series of decisions over time.”
True to its multi-armed name, the team’s framework applies RMAB models across three different thrusts.
Contextual RMABs use patient histories, biomarkers, demographics, and other data to predict how each individual will respond to an intervention. These models directly provide personalized, data-driven treatments.
By incorporating patient-specific information, contextual RMAB models can help healthcare providers prioritize the most timely interventions. The goal is to improve patient outcomes while making more efficient use of limited healthcare resources.
Next, the group wants to understand social life and community influence in public health. Families and social networks shape how people manage chronic health conditions.
Network RMABs study and account for the role of social factors in health interventions. For example, the models can recognize when one patient responds better to treatment than others through benefits of their social circle.
More broadly, hospitals, clinics, government agencies, and nonprofit organizations often share responsibility for the same population in an area. Sometimes, they even compete for the same medications or funding.
Multi-agent RMABs are the third glass of models aimed at decentralized health systems to make fairer decisions. These tools examine how to coordinate resources and decisions between stakeholders. This in turn leads to policies that encourage cooperation and equitable resource distribution.
“I feel extremely confident in RMABs because we have already seen these frameworks deliver real-world impact,” Wang said.
“Prior success has proven the value of data-driven decision-making under resource constraints, giving us a strong blueprint to effectively address the nuances and complexities of diabetes.”
Wang previously built RMAB models to expand maternal healthcare for women in India. Working in conjunction with the non-profit organization ARMMAN, the models used healthcare information to identify and reach the most vulnerable populations.
By integrating RMAB models into ARMMAN mobile health technology, the partnership has reached over 350,000 mothers. This further led to a 31% improvement in engagement with health information.
Compared to maternal healthcare, diabetes is a more nuanced disease with differing causes, symptoms, and treatments. This requires a team effort spanning institutions and backgrounds.
Dr. Sara Cromer is an endocrinologist at Massachusetts General Hospital (MGH). Experienced diagnosing and treating diabetes, she has studied how social issues and equity influences the disease. MGH will provide much of the patient data to train the RMAB models.
Associate Professor Jian Li studies reinforcement learning at Stony Brook University. His expertise in applying reinforcement learning for resource allocation plays a key part tailoring models for the T2D problem. Wang and Li have previously worked together on RMAB research.
Prakash is an expert in computational epidemiology at Georgia Tech. He has led substantial contributions to the use of AI for networks to predict outbreaks and track disease spread. This experience has led to collaborations with NIH, the Centers for Disease Control and Prevention (CDC), National Science Foundation, and others.
“This project speaks to the interdisciplinary problem-solving we try to achieve in CSE. Despite having different backgrounds, our interest in applying our strengths to real-world healthcare problems unites us together,” Prakash said.
“These problems require experts from all sides. Without computational scientists, we can’t take advantage of available data. We lean on clinical experts to provide the data and expertise needed to guide our methods and make sense of results. Ultimately, these approaches need to be clinically validated if we want to make real-world progress.”
]]>A team of computer scientists and doctors led by Georgia Tech aims to change that. Using a system of artificial intelligence (AI) models, the team can help clinicians deliver the right intervention to the right patient at the right time.
Their system uses Restless Multi-Armed Bandit (RMAB) models. While the name is technical, the idea is simple. The RMAB framework helps decision-makers choose the best actions over time when conditions are complex and constantly changing.
This project will tackle Type 2 Diabetes (T2D), building on previous experience expanding RMAB models to support maternal health care in India. Success on this front could lead to treating other chronic illnesses, like hypertension, heart disease, kidney disease, and mental health.
]]>Charles Woods, a privacy rhetoric expert in Georgia Tech's School of Literature, Media, and Communication at the Ivan Allen College of Liberal Arts, shares four major concerns.
Researchers at Georgia Tech's Center for Advanced Communications Policy will use the funding to help older adults access assistive technologies that support independent living.
Principal research scientist Nathan Moon and a team of colleagues at the Center for Advanced Communications Policy (CACP) in Georgia Tech’s Ivan Allen College of Liberal Arts were awarded a three-year, $1.5 million grant from the National Institute on Disability, Independent Living, and Rehabilitation Research. The project is in collaboration with the Center for Inclusive Design and Innovation (CIDI) in the College of Design.
The funding will support the ACCESS for Aging Well with Assistive Technology (AT) 2.0 project, which builds on the researchers’ previous work to help older adults live independently.
“As Americans continue to age and we're growing older as a society, we want to ensure that people can continue to live independently and participate in the communities of their choice,” Moon said. “The tools that we have developed here are intended to do that.”
According to AARP, 75% of adults over 50 want to age in their homes. However, Retirement Living reports only 10% of homes are appropriately equipped to do so. Assistive technologies can help older adults live independently longer, but finding the right solutions and learning how to access them can be difficult.
ACCESS for Aging Well with AT 2.0 addresses those challenges by using machine learning, predictive analytics, and community partnerships to connect people with the tools and resources they need.
The researchers will use the funding to integrate the existing ACCESS for Aging Well website and assistive technology catalog into a single platform that provides assessments, recommendations, and solutions for older adults via machine learning, predictive analytics, expert insight, and state assistive technology program data.
It will foster an active community through online discussion forums, social media, product reviews, and informational articles. The team will also analyze community discussions with AI-based tools to refine recommendations and identify new or innovative ways people may be using assistive technology.
Finally, the funding will help the researchers connect with organizations such as senior centers, rehabilitation centers, and state aging agencies to expand access to assistive technologies and meet older Americans where they are.
The project also supports a significant return on investment.
“For every $1 spent on assistive technology, people save $9,” Moon said. “Assisted living is terribly expensive. We will never replace assisted living or nursing homes, but we do want to give people the choice to age successfully in their communities of choice.”
Using technology to improve lives is a central mission of the Ivan Allen College and Georgia Tech, and researchers at CACP and CIDI collaborate across disciplines to do just that.
“We're using AI and harnessing the cutting edge of technology to make better recommendations based on what we know, but it’s not just technology for technology’s sake. We put the people first and technology follows. It's there to be a support.”
Sivakumar currently serves as Georgia Tech’s vice president of Commercialization and chief commercialization officer, leading the Office of Commercialization. The office serves as the Institute’s central hub for student entrepreneurship, research translation and commercialization, and venture development and scaling, enabling faculty and students to bring new technologies to market. Sivakumar previously served as the founding director of CREATE-X, a Georgia Tech initiative that fosters entrepreneurial confidence and helps students launch real startups. He has also founded and co-founded multiple technology companies and held technical roles in industry.
In addition to his administrative leadership, Sivakumar is the Wayne J. Holman Chair and professor in the School of Electrical and Computer Engineering (ECE). His research focuses on wireless networking and mobile computing.
Sivakumar joined ECE in 2000 as an assistant professor. He earned his bachelor’s degree in computer science from Anna University in Chennai, India, and his master’s and doctoral degrees in computer science from the University of Illinois Urbana-Champaign. He is a Fellow of the Institute of Electrical and Electronics Engineers.
]]>Georgia Tech contributors included corresponding author Christopher E. Carr, an assistant professor in the School of Earth and Atmospheric Sciences and the Daniel Guggenheim School of Aerospace Engineering, and Research Scientist José L. Ramírez-Colón.
The technique the team developed focuses on the handedness, or chirality, of amino acids. Biotic processes largely use one form of amino acid, whereas nonliving processes produce both forms in roughly the same amounts. As a result, the ratio of amino acid forms present can be used as a potential indicator of life.
To detect these ratios, the researchers harnessed recent developments in nanotechnology: passing molecules through a gap between two gold nanowires. The resulting technique distinguished between amino acid forms with over 80% accuracy.
The team hopes their work could lead to compact instruments capable of analyzing samples and identifying biosignatures.
This story is adapted from an article originally published by the University of Osaka. Read the full story in the University of Osaka newsroom.
DOI: 10.1038/s41467-026-77947-6
Funding: Japan Science and Technology Agency, NASA PICASSO
]]>For more than eight years, MRI, manufacturer of the BoldVu rugged outdoor displays, has supported graduate research in the Microelectronics and Emerging Technologies Thermal Lab (METTL), led by Yogendra Joshi, John M. McKenney and Warren D. Shiver Distinguished Chair in Building Mechanical Systems. The partnership has funded multiple student thesis projects, produced several published papers, and supported engineering improvements incorporated into MRI’s products.
“It’s been a great collaboration,” Joshi said. “Multiple master’s students have completed their thesis projects on different challenges facing the same product line, and they’ve gone on to jobs at premier companies.”
Ready the full story on the George W. Woodruff School of Mechanical Engineering website
]]>For more than eight years, MRI, manufacturer of the BoldVu rugged outdoor displays, has supported graduate research in the Microelectronics and Emerging Technologies Thermal Lab (METTL), led by Yogendra Joshi, John M. McKenney and Warren D. Shiver Distinguished Chair in Building Mechanical Systems. The partnership has funded multiple student thesis projects, produced several published papers, and supported engineering improvements incorporated into MRI’s products.
]]>Communications Officer
George W. Woodruff School of Mechanical Engineering
Hosted by Georgia Tech's Strategic Energy Institute (SEI), the annual summit brought together representatives from academia, industry, government, national laboratories, and nonprofits to discuss strengthening energy systems and preparing for a changing energy future. Topics focused on collaboration, workforce development, and strategies for building resilience amid the challenges in the energy sector.
"Energy resilience requires more than technological innovation. It depends on strong partnerships across universities, industry, government, and national laboratories," said SEI Executive Director Yuanzhi Tang, who delivered the summit’s opening remarks. "The UEILC Summit serves as an important forum to exchange ideas, identify shared challenges, and build collaborations among energy institutes across the country. These efforts are essential to strengthening energy systems and preparing the workforce that will support them."
Following Tang, Tim Lieuwen, Georgia Tech's interim president and executive vice president for Research, delivered a keynote address on academia's role in advancing a resilient energy future. Lieuwen emphasized the unique role of universities as trusted conveners and honest brokers, bringing together stakeholders with diverse perspectives to navigate an evolving energy ecosystem.
A fireside chat featuring Mike Caravaggio of EPRI, Stephanie Gossman of Georgia Power, and Tang explored how artificial intelligence, data center expansion, and rising electricity demand are reshaping the energy landscape. The speakers also discussed how their organizations are working to strengthen grid reliability, expand infrastructure, and support a reliable energy future.
Founded with support from the Alfred P. Sloan Foundation to strengthen collaboration among university energy institutes, the University Energy Institute Leadership Collaborative provides a forum for advancing energy research, education, and engagement.
“A systems approach to today’s energy challenges — where academia, industry, and government collaborate to provide many perspectives on a problem — can only happen if there is a venue and a community where these discussions can safely take place,” says Daniel Tkacik, executive director of Carnegie Mellon’s Scott Institute for Energy Innovation as well as the principal investigator of the Sloan Foundation grant that supports the UEILC. “This summit continues to provide that valuable venue for collaboration, and we are grateful to our generous hosts at Georgia Tech.”
The summit theme, Expanding Collaborations for Resilient Energy Futures, framed discussions on regional energy resilience, grid vulnerabilities, geopolitical influences on energy planning, the growth of data centers, and workforce education.
"The UEILC annual summit provides an excellent opportunity for energy institute leaders from across the nation to come together and share perspectives, strengthen partnerships, and advance solutions that can help shape more resilient energy futures," said Christine Conwell, director of planning and operations at SEI. "The conversations over the course of the summit reinforced the importance of cross-sector partnerships in creating new opportunities for innovation."
Conversations and networking opportunities provided a broader understanding of how different regions are strengthening energy resilience, addressing emerging threats to power infrastructure, adapting to geopolitical and economic shifts, and preparing for increased electricity demand driven by artificial intelligence and data centers.
"It was exciting to see so many diverse perspectives united by a common goal of building more resilient energy systems," said Jordann Britt, SEI program manager and a UEILC Bridge-Builder Fellow.
Britt helped organize the summit as part of the UEILC Bridge-Builder Fellows Program, which supports emerging leaders in the university energy community.
]]>Hosted by Georgia Tech's Strategic Energy Institute (SEI), the annual summit brought together representatives from academia, industry, government, national laboratories, and nonprofits to discuss strengthening energy systems and preparing for a changing energy future. Topics focused on collaboration, workforce development, and strategies for building resilience amid the challenges in the energy sector.
]]>After a grueling, world-class competition, the team won the $4 million first-place prize in August 2025.
The team has since disbanded. Some members have moved into the corporate world, while others continue in academia. Despite these varied paths, Team Atlanta’s search for breakthrough AI cybersecurity solutions continues.
Team Atlanta lead Taesoo Kim, principal security researcher Dongkwan Kim, and three other former team members joined Microsoft Security after the competition, where they continue to work on AI and cybersecurity in the Frontier Offensive Research & Generative Exploitation (FORGE) Lab.
The move has given the researchers an opportunity to apply concepts from AIxCC to real-world software. It has also exposed them to challenges that are difficult to replicate in a competition or research lab.
Dongkwan Kim said that team members continue to share what they learned through research papers, reports, software, and benchmarks. At Microsoft, these lessons are tested against real customer code.
This work led to MDASH, Microsoft's multi-agent, multi-model system for vulnerability discovery and remediation. The system uses more than 100 AI agents to search for vulnerabilities, validate potential findings, and help develop fixes.
Rather than asking a single AI model if a piece of code contains a vulnerability, MDASH can examine a problem using multiple agents. The system can also try to create an exploit to determine whether a potential vulnerability is real and reachable.
For Dongkwan Kim and the other former Team Atlanta members at Microsoft, moving from AIxCC to MDASH showed how research can look different when applied to real software.
“AIxCC was not an endpoint for Team Atlanta,” he said. “We continue sharing what we learned through technical reports, papers, open artifacts, and benchmarks for vulnerability discovery and patching.”
Working with customer code introduced new challenges for the Microsoft team. The researchers had to consider security boundaries, existing development processes, how findings would be reviewed, and how vulnerabilities would be prioritized for action.
These challenges created a new feedback loop between research and product development. The team took ideas from AIxCC, test them on real software, learn where they worked and where they fell short, and use those lessons to improve the system.
The experience also showed that AI does not replace the need for cybersecurity experts. Human researchers are still needed to provide context, decide how to break down difficult problems, validate findings, understand attack paths, and determine the potential impact of a vulnerability.
Taesoo Kim, a professor in the School of Cybersecurity and Privacy and vice president of security research at Microsoft, said the competition continues to influence the Microsoft team's work.
“Every single activity that we’ve done at Microsoft was influenced by AIxCC,” he said in a 2026 interview with Microsoft.
The work has continued to grow. In 2026, Microsoft introduced MAI-Cyber-1-Flash, an AI model built specifically for cybersecurity and designed to work with MDASH.
The model is designed to handle many of MDASH's tasks while allowing larger AI models to focus on harder problems. Microsoft reported that replacing 80% of the models used by MDASH with MAI-Cyber-1-Flash increased its performance on the CyberGym benchmark from 88.4% to 95.95%.
The benchmark includes more than 1,500 examples from 188 software projects. Microsoft also reported that the new setup can achieve similar performance at half the cost of the previous MDASH configuration.
“AIxCC has sparked cybersecurity innovation across the globe, from frontier AI companies to small academic labs,” said Taesoo Kim. “It is an incredibly exciting time to be working in AI-driven security engineering and research, as we see AI fundamentally reshape how we find and fix vulnerabilities at scale.”
The AIxCC experience also continues to shape cybersecurity research at Georgia Tech.
Jiho Kim, a Georgia Tech Ph.D. student who was part of Team Atlanta's research efforts, said one of the biggest lessons he’s brought back to campus was learning how AI and traditional security tools can work together.
One of these tools is fuzzing. Fuzzing tests software with large numbers of inputs to detect unexpected behavior or security problems. Large language models (LLMs), meanwhile, can reason about code and help guide the search.
During the AIxCC competition, the Team Atlanta combined these ideas in CtxFuzz, a system that uses an LLM to help guide fuzzing toward parts of software that may contain vulnerabilities.
The research was submitted to the ACM/IEEE International Conference on Automated Software Engineering, where it received the ACM Distinguished Paper Award.
“Since AIxCC, we’ve continued building on some of the core findings from our two-year journey with Team Atlanta,” Jiho Kim said.
“One of the biggest lessons for us was understanding how LLMs and traditional fuzzing can work together in a mutually beneficial way, using each to overcome the limitations of the other and ultimately find more and deeper vulnerabilities.”
The researchers also wanted to make the lessons from AIxCC useful to other cybersecurity researchers.
They created an Open-Source Cyber Reasoning System Framework (OSS-CRS) and CRSBench, which provides researchers and security professionals with ways to use, test, and build on technology developed through AIxCC.
“We’ve also been focused on making the results of AIxCC useful to the broader security community,” Kim said. “We created OSS-CRS and CRSBench so that researchers and practitioners can more easily use, reproduce, and build upon the capabilities and lessons from our AIxCC work.”
The team's research has also moved beyond identifying vulnerabilities. Researchers are studying how well AI models can understand and reason about computer code.
Jiho Kim and his lab mates in the Systems Software & Security Lab developed COIN, a benchmark designed to test how well LLMs can reason about code. The work has been accepted to the 2026 Conference on Empirical Methods in Natural Language Processing.
The Georgia Tech researchers are also developing additional benchmarks to study the various types of reasoning required for cybersecurity. They are using what they learn to create new datasets and methods for training AI models focused on cybersecurity.
“We’re using what we learn from these benchmarks to train cybersecurity-focused models through new datasets and training methodologies,” Jiho Kim said.
Photos by John Popham/College of Computing
]]>Communications Officer at the School of Cybersecurity and Privacy
]]>Francis Halzen, principal investigator of the NSF IceCube Neutrino Observatory and a professor at the University of Wisconsin-Madison, was honored by the Royal Swedish Academy of Sciences for his “decisive contributions to IceCube and the discovery of high-energy neutrinos of astrophysical origin.”
“Francis proposed building a neutrino telescope in Antarctic ice, and along with his collaborators, he proved that it is possible to detect neutrinos in this challenging environment,” says Ignacio Taboada, professor in the School of Physics and former spokesperson for the IceCube Collaboration. “IceCube was a technological tour de force, and its success is now recognized by this Nobel Prize. The award energizes the nascent field of neutrino astronomy.”
A. Nepomuk Otte, professor in the School of Physics, describes the impact of IceCube’s results as “breathtaking.”
“What we are witnessing is the opening of an entirely new window into the universe, providing us with a unique view of the most violent astrophysical objects and allowing us to study the elusive nature of neutrinos,” says Otte. “I am extremely excited about the prospects of pushing to even higher energies and deeper into the universe with the next generation of neutrino experiments planned at Georgia Tech and around the world.”
IceCube is a giant neutrino telescope located at the South Pole. Envisioned by Halzen in the late 1980s and completed in 2011, the instrument detects neutrinos, tiny high-energy particles that travel through the universe and rarely interact with matter. Scientists study neutrinos to better understand phenomena such as supermassive black holes and exploding stars.
Georgia Tech has been a member of the IceCube Collaboration since 2008. The collaboration includes more than 400 physicists from 58 institutions in 14 countries.
Georgia Tech researchers continue to shape neutrino astronomy by contributing to next-generation observatories. Taboada leads the design of the trigger system for the Pacific Ocean Neutrino Experiment (P-ONE) Observatory, and Otte is the principal investigator of the NSF-funded Trinity Neutrino Observatory in Utah.
]]>New research from Georgia Tech shows that the contexts in which genes act — lifestyle and environmental factors — are also important in understanding how genes express themselves, and how genetic risk may lead to disease.
In a new study published in Nature Genetics, Pervasive Interactions Between Exposures and Polygenic Risk Can Inform More Effective Clinical and Behavioral Interventions, researchers analyzed the genetic data, health outcomes, and lifestyle factors of over 400,000 individuals.
“Genetic risk is often seen as something that can’t be controlled, but that approach assumes a determinism that does not reflect reality,” says the study’s corresponding author Greg Gibson, Regents’ Professor, Tom and Marie Patton Chair in the School of Biological Sciences, and director of the Center for Integrative Genomics at Georgia Tech. “Our research shows that people with low genetic risk who live in disadvantaged environments face disease risks similar to those with high genetic risk living in more resourced circumstances.”
The findings suggest that people at highest genetic risk may also be the individuals who benefit the most from targeted interventions — paving the way for more informed genetic counseling and social policy.
Gibson began his career studying the genetics of Drosophila fruit flies before turning his attention to human genetics when he joined Georgia Tech in the late 2000s, soon after the Human Genome Project successfully delivered the first complete sequence of the human genome. “It transformed the way we do this type of research,” he recalls. “Suddenly it was possible to analyze genetics across large groups of people.”
Because the effects of genetics can be small in an individual, large datasets are key to understanding genetics and disease at scale. “If we need to study 200,000 people to see a genetic effect, it takes even more than that to see how those genes interact with the environment,” Gibson says.
The team, which included first author Sini Nagpal, formerly a postdoctoral fellow at the Georgia Tech Center for Integrative Genomics, leveraged the UK Biobank, a program that collects genetic information from half a million volunteers in the United Kingdom to understand who falls ill and why. Started in 2006, the UK Biobank is home to the world’s largest single set of genetic sequencing data — along with the world’s largest whole-body imaging and long-term health tracking. This type of data is critical, Gibson says, to the advancement of genetic research, and is in large part what has made this new research possible.
“Our research shows that we do have a way to capture situations where a person’s lifestyle and environment interacts with genetics in interesting ways,” he explains. “These genotype-environment interactions matter. They are important, but they can't be captured one variant at a time. An integrated approach — utilizing information in the thousands of genes influencing each disease — is much more powerful.”
The team is now interested in expanding their research outside of the British database. Nagpal is now an assistant professor at the Koita Centre for Digital Health at IIT Bombay, where she is investigating translational genetics in India, including research into diabetes, cardiovascular disease and asthma. Gibson is interested in translating the research to more broadly apply to the United States, with a focus on rural and disadvantaged communities.
“Ultimately, if we can quantify which people are at highest risk, we believe we can suggest therapeutic and environmental interventions that could help mitigate their risk, reducing the prevalence of disease in the first place,” he says.
“We want to dig deeply in ways that reveal disease pathways and begin to unearth the mechanisms behind disease,” Gibson says. “It's not just our ancestry that determines health; it's also culture and environment. We want to incorporate those factors into treatment of individuals and at scale.”
These themes are also present in Gibson’s newly published book, Natural Virtue: Genetics, Anti-Eugenics, and Moral Philosophy, which explores how nature and nurture impact social issues like educational and gender disparities.
Gibson adds that the message is hopeful. “The genetic differences between different socioeconomic groups aren’t meaningful,” he explains. “Our genetics do not predetermine our health outcomes. If we can create more equitable environments, we can improve outcomes across the board.”
]]>Designed for industry professionals, policymakers, educators, students, community leaders, and members of the public, the lunchtime webinar series provided an accessible introduction to the key issues influencing the nuclear energy sector at a time of growing interest in nuclear power as part of the global energy transition.
The series began on Aug. 20 with The New Nuclear, presented by Steven Biegalski, chair of the Nuclear and Radiological Engineering and Medical Physics program. The session examined the evolution of nuclear reactor technology, from today's operating fleet and the AP1000 reactors at Plant Vogtle to emerging small modular reactors and advanced reactor designs.
The second webinar, held Sept. 3, focused on the economics and policy landscape of nuclear power. Laura Taylor, director of EPIcenter and professor of economics at Georgia Tech, joined Stephen Comello, executive vice president and executive director of the Nuclear Scaling Initiative at the EFI Foundation, to discuss the economic drivers, policy considerations, and opportunities influencing nuclear energy development in the United States.
The series concluded on Sept. 17 with a discussion of nuclear fuel, security, and geopolitics. Anna Erickson, Woodruff Professor of Nuclear Engineering, and Rachel Whitlark, associate professor in the Sam Nunn School of International Affairs, explored global nuclear energy growth, fuel supply chains, and the policies needed to support the safe, secure deployment of nuclear technologies worldwide.
Recordings and presentation materials from all three sessions are available on the webinar series webpage. Those who were unable to attend can watch the presentations and access the accompanying slides to learn more about the technologies, policies, and global trends shaping the future of nuclear energy.
View webinar recordings and presentation slides on the EPIcenter website.
]]>
"The most meaningful breakthroughs happen when intelligent hardware and thoughtful software come together to genuinely help people,” said Tapas Roy, vice president of Device Software and Services at Amazon. “Georgia Tech's world-class expertise in robotics and engineering, paired with Amazon's work in on-device intelligence and artificial intelligence, will accelerate our understanding of systems that can both respond to prompts and anticipate customer needs. I'm excited to see how this collaboration advances the science of how humans and intelligent machines work together.”
The Hub’s initial focus areas will explore challenges in autonomous systems, next-generation logistics infrastructure, and low-Earth-orbit communications, drawing on Georgia Tech’s well-known interdisciplinary research approach.
Georgia Tech is also joining the Fauna Robotics' ecosystem, using the Sprout research platform to study how humans and robots can live, work, and play side by side. This collaboration opens new ways to study mobility, perception, manipulation, and human-robot interaction. Leadership and alumni recently celebrated the launch at Lab 126, with guest appearances from Sprout and Buzz, the Georgia Tech mascot.
The Hub will support:
• Joint research projects between Georgia Tech faculty and Amazon scientists across scientific disciplines
• Regular symposia and workshops to foster collaboration between researchers from both institutions and the broader Atlanta tech community
• Community outreach programs designed to broaden participation from interdisciplinary scholars and innovators
“Georgia Tech and Amazon have worked together for years across research, technology, and student development," said Tim Lieuwen, Georgia Tech executive vice president for Research. "This new hub puts our partnership to work for Georgia. It connects research, education, and industry in ways that will strengthen our state’s innovation economy and create new opportunities for our students.”
About Georgia Tech
Georgia Institute of Technology is one of the nation’s top public research universities, preparing leaders who advance technology and improve the human condition. The Institute serves more than 56,000 students from all 50 states and over 146 countries and drives innovation and economic growth through research that benefits Georgia, the nation, and the world.
About Amazon in Georgia
Since 2010, Amazon has invested more than $30 billion in Georgia, supporting more than 30,000 full- and part-time jobs. Amazon’s research and technology teams in the Atlanta area work on challenges spanning supply chain optimization, logistics technology, and cloud computing. The establishment of the Georgia Tech–Amazon Science Hub further deepens Amazon’s engagement with one of the nation’s leading research institutions.
About Fauna Robotics
Fauna Robotics builds Sprout, a development platform designed to put advanced robotics capabilities into the hands of researchers and developers. Sprout gives builders hands-on access to study mobility, perception, motor control, and manipulation with the ambition to deploy robots into human-centric spaces.
Their system means devices can work together like never before, sensing in one part of the body and triggering a therapeutic response elsewhere — perhaps releasing medicine or stimulating a nerve.
Described Sept. 24 in the journal Science, their communication method is expandable to include multiple interconnected devices across the body, even deep inside the stomach.
Read the full story on the College of Engineering website.
]]>Those conversations led Raymaker to focus her research on maritime security, including vulnerabilities in the Automatic Identification System (AIS), which ships use to broadcast their location, speed, and course.
This summer, Raymaker brought this research to Massachusetts Institute of Technology (MIT) Lincoln Laboratory, where she built a test bed to study AIS security in a controlled environment. The experience has also led to new research questions, from the security of shipboard Starlink connections to autonomous vessels and other maritime technologies.
We spoke with Raymaker about her research, her experience at Lincoln Laboratory, and what she hopes to investigate next.
After submitting our paper based on this summer’s work to a cybersecurity conference, we are continuing our collaboration and starting a new project to identify critical infrastructure that uses unique protocols. The project is still in the early stages of planning and design, but I’m excited to continue working with the team.
The biggest challenge was getting equipment designed to be installed and operated on a boat to function properly in a lab setting. That meant using a Faraday cage so that our AIS transmissions and security experiments wouldn’t accidentally broadcast to nearby ships or interfere with real maritime traffic. I also had to simulate GPS signals and set up additional hardware to trick the AIS transponders into thinking they were operating on a real vessel. Putting all those pieces together into a safe, realistic test bed was challenging, but it ultimately let us study the equipment in a controlled environment.
Working with Hamed Okhravi, a senior staff member at Lincoln Laboratory, was an amazing experience. He was my mentor and consistently went out of his way to connect me with people who could help me find datasets, access equipment, or get the lab space I needed for my work. For example, when I realized I needed a Faraday cage for my experiments, he connected me with the Mobile Device Lab and helped me get access very quickly. The lab manager was also immediately willing to let me use the space and equipment. That experience really reflected the culture I saw throughout Lincoln Laboratory. Everyone genuinely wanted to help each other get what they needed to move their research forward.
My experience at Georgia Tech was instrumental in preparing me for my work at Lincoln Laboratory. The way I was taught to think through difficult research problems and work independently toward solutions translated well to a large research lab. I was able to hit the ground running and take ownership of a project because Georgia Tech had prepared me to lead research independently. The internship also gave me valuable experience in a research environment outside academia, which broadened my perspective on how I could pursue research in the future.
Next, I’d love to look at Starlink connectivity for ships or for autonomous shipping. Mariners we’ve spoken with have raised concerns about both. With Starlink and increasingly autonomous vessels, they worry that greater remote connectivity could give attackers new ways to access onboard systems and disrupt ship operations. I think those concerns are worth investigating.
We recently had a paper accepted at CCS that examines exposed solar distributed energy resources, and I think applying a similar perspective to exposed maritime equipment could be very interesting. That paper is available here.
We also recently had a paper on measuring GPS spoofing of ships accepted at IEEE S&P. The full paper isn’t online yet, but the project was directly motivated by mariners telling us that they were struggling with GPS spoofing. That made me want to find a way to systematically measure where spoofing was occurring.
Ultimately, the goal is to turn that kind of research into something useful for mariners, such as warning them when they are entering an area experiencing spoofing or when their own vessel may be affected and they should no longer trust their GPS. That is the kind of research I’d like to continue doing: listening to the problems mariners are actually experiencing and finding ways to investigate and address them.
Photos by Kevin Beasley and Terence Rushin/College of Computing
]]>Communications Officer for the School of Cybersecurity and Privacy
]]>Through a major investment from the U.S. Department of Energy (DOE), Georgia Tech is helping accelerate the development of domestic critical minerals from unconventional and secondary resources. The $7.5 million award positions the Institute to advance supply chain solutions that span resource discovery, processing, recycling, and circular materials management.
Selected by DOE’s Office of Critical Minerals and Energy Innovation, Georgia Tech will lead the Critical Minerals in the Atlantic Seaboard Plain (CM-MAP) project. The regional effort builds on DOE’s Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) initiative and will examine potential resources across the Atlantic coastal plain.
The CM-MAP project will focus on sedimentary deposits, including kaolin, bauxite, heavy mineral sands, and phosphates, as well as legacy mining residues, coal combustion byproducts, and other unconventional and secondary resources that could support future recycling and circular economy opportunities.
Drawing on existing infrastructure, regional assets, industry bases, and scientific expertise, CM-MAP will establish a regional innovation ecosystem that supports domestic critical mineral production, recycling, and advanced manufacturing, while fostering new economic opportunities throughout the Southeast.
“This is a powerful example of how Georgia Tech brings together leading research capabilities and partnerships from industry, government, nonprofits, and national labs to address complex national challenges,” said Tim Lieuwen, executive vice president for Research. “By identifying and domestically sourcing critical minerals, we are helping secure essential supply chains, while enabling the next generation of energy and materials technologies.”
The DOE award builds on a growing network of research, industry, regional, and international partnerships led by Georgia Tech to translate scientific discovery into real-world supply chain solutions, including:
As part of CM-MAP, researchers will analyze materials collected from natural deposits and industrial sites throughout the Southeast to identify their critical mineral content. The resulting large datasets will be combined with artificial intelligence and machine learning approaches to better understand and predict where resources exist, optimize extraction pathways, and inform future recovery and recycling strategies.
“This project brings together a highly collaborative team from Georgia Tech, national labs, industry partners, and research institutions across the region,” said Yuanzhi Tang, the principal investigator and Georgia Power Professor in the School of Earth and Atmospheric Sciences, with a courtesy appointment in the School of Civil and Environmental Engineering.
Tang is also the founding director of the Center for Critical Mineral Solutions and executive director of the Strategic Energy Institute.
“Through this award, we are working to build secure and resilient critical materials supply chains, from resource discovery and characterization to processing, recovery, recycling, and advanced manufacturing, while also developing the skilled workforce needed to support these emerging industries,” Tang said. “Our vision is to create a regional innovation ecosystem that embraces both unconventional resources and circular economy approaches to maximize the value of materials already in use.”
Learn more about critical materials research and workforce development efforts at Georgia Tech by visiting the Center for Critical Mineral Solutions webpage.
]]>Few neuroscientists would dispute that the brain relies on prediction. From houseflies evading swatters to humans catching baseballs, living things are constantly anticipating what comes next. Understanding how the brain generates those predictions could help explain one of neuroscience's most enduring questions: how the brain builds internal models of the world that allow us to learn, adapt, and anticipate what comes next.
“Without actively predicting the world, we cannot survive,” says Farzaneh Najafi, an assistant professor in the School of Biological Sciences and a faculty affiliate of Georgia Tech's Institute for Neuroscience, Neurotechnology, and Society. “There is quite some sensory-motor delay in the processing. We can’t just sit there, wait for the brain to process our environment, and then react.”
Part of the puzzle may lie in signals known as neural ramps. Almost like a drumroll leading up to a big reveal, neurons in some areas of the brain have shown gradual increases in activity immediately before a stimulus appears. For decades, researchers have interpreted this ramping activity as a neural signature of prediction, reflecting anticipation of an upcoming event.
Recently published in Science Advances, a new study from Najafi’s lab reveals these signals may not be “predictions” at all, but instead a way neurons track elapsed time.
“Surprisingly,” says Najafi, “the very first study from my lab called the Predictive Processing Lab showed that no, these are not prediction signals.”
The finding challenges a long-standing interpretation of one of neuroscience's most studied signals and reveals that the search for predictive neurons may lead to different circuits — or require different experiments to uncover.
There is a challenge in separating simple time tracking from active prediction. Just because numbers on a stopwatch are increasing doesn’t mean it’s counting up to a specific event.
To tease the problem apart, the team designed a series of experiments that progressively stripped prediction out of the equation.
Working with mice, the researchers presented audio and visual cues at carefully controlled intervals. Some appeared at regular, hence predictable, times, while others arrived unpredictably. If neurons are making predictions, their activity should look different when events are predictable versus when they are not.
But that’s not what they found. Even when the researchers introduced errors into those predictable patterns, activity remained largely the same.
“It was in the first year of collecting data in my newly established lab that my student, Yicong Huang, started showing me the data and I was shocked: how come we are not seeing a difference between the expected case and the unexpected case?” Najafi recalls. “Because the entire theory is that there is a difference.”
The team found even more definitive evidence by monitoring “naive” mice that had never seen the stimuli before. The brain must learn a pattern before it can anticipate it, yet they found that these neural ramps were present even in the first few trials.
If these signals aren’t predictions, then what’s happening?
“What we are seeing are pure sensory signals,” she says. “They are not about predicting the timing of the upcoming stimulus. They're about encoding the time that is elapsed.”
Najafi thinks that what neuroscientists have long interpreted as an anticipatory “buildup” to a future event is actually a “relaxation” from the past. Rather than a drummer rolling up to a specific event, imagine one who is always rolling. Each stimulus briefly interrupts the performance before the rhythm gradually returns.
But they found that not every neuron behaves like a drummer. While “drummers” recover their interrupted rhythm after a stimulus, other neurons operate more like a reverberating gong, firing strongly after a stimulus before gradually quieting down.
“The beautiful part of this story is that neurons don't all do the same thing,” Najafi says. “One neuron ramps up quickly, another more slowly, another with a completely different time course. When you put that heterogeneous population together, you get a very robust readout of time.”
The finding may also have implications for how neuroscientists think the brain represents time itself.
“Our findings support the theory that time representation in the brain is an intrinsic property of neurons,” says Najafi. Because the signals appeared even in naïve mice and in sensory brain regions, the results suggest that timing may emerge from the properties of neurons themselves, rather than from a specialized timing system elsewhere in the brain.
For Najafi, the study doesn't close the case on predictive processing. Time, after all, is an important variable to track if you want to make predictions. Instead, it opens more questions about when and where those signals emerge.
“Maybe we didn't find them because this was a passive perception task, meaning mice just passively received stimuli without being instructed to attend to them. Maybe we need active perception or an active movement task, and that's when we can extract these predictive signals from the brain. Alternatively, we may need to search other brain areas to find neural signatures of temporal predictions.”
“Do I believe now that the brain is not doing predictive processing? Absolutely not,” Najafi says. “But before we say we've found evidence for a theory, we really need to do multiple carefully designed experiments. We need to attack this from many different angles.”
Funding: This research was supported by the Whitehall Foundation, the Research Corporation for Science Advancement, the Chan Zuckerberg Initiative, and the Georgia Institute of Technology.
DOI: 10.1126/sciadv.aed6417
As many organizations and businesses are turning to AI to improve workplace efficiency, risk remains high. Between overlooked footnotes and misread graphics, small mistakes can have expensive consequences.
To address this challenge, researchers from Georgia Tech and J.P. Morgan developed SlideAgent. The new framework helps large language models (LLMs) better understand complex visual documents like presentation slide decks, brochures, and reports.
SlideAgent works by breaking documents into multiple levels, allowing the model to analyze both the big picture and the fine details. This human-inspired approach leads to more accurate and reliable interpretation than existing systems.
Beyond improving workplace tools, SlideAgent also points to a broader shift in AI. Instead of building only larger and more powerful models, the work shows how smarter design and more efficient reasoning can improve performance.
“Multimodal LLMs such as GPT, Gemini, and Claude, can save people time and reduce the mental effort required to understand these documents, but they remain imperfect,” said Yiqiao (Ahren) Jin, a Ph.D. candidate in Georgia Tech’s School of Computational Science and Engineering (CSE).
“In high-stakes fields such as finance, for example, misreading a number, overlooking a footnote, or making an incorrect comparison across pages could affect reporting, risk assessment, or strategic decisions.”
The researchers tested SlideAgent on a wide range of real-world documents, including financial presentations, technical slides, and visual question-answering datasets.
The system consistently outperformed leading commercial models and open-source tools throughout the evaluation. In some cases, it improved accuracy by up to 10%. The gains were especially strong on more complex tasks, such as comparing information across slides or understanding how visuals relate to each other on a page.
“We found the results very encouraging. SlideAgent reaches an improvement of 7.9% over its proprietary base model and 9.8% over the evaluated open-source base models,” said Jin, the project’s lead researcher.
“These are meaningful gains given the strength of the underlying multimodal models and the difficulty of the tasks.”
Current multimodal AI systems often process entire pages at once. This approach can lead to mistakes, such as miscounting items in a chart or overlooking important details in dense visuals.
SlideAgent addresses this by mimicking how people read documents. Instead of treating each page as a single unit, the system looks at information at three levels: the full document, individual pages, and specific elements like charts, tables, and text blocks.
A network of agents, each specialized for a specific level, divides and coordinates analysis. Then, SlideAgent combines outputs to build a structured understanding of the overall document. This allows it to answer questions more accurately and reason across multiple pages.
“The central inspiration was how people naturally read a long presentation,” Jin said.
“We first develop an understanding of the overall narrative, then identify the relevant pages or sections, and finally zoom in on individual charts, tables, or text blocks when precise evidence is needed.”
The work highlights a growing challenge with AI. As systems become more popular and more powerful, users increasingly discover the technology’s limitations. This is especially true for real-world tasks that require structured reasoning and contextual understanding.
SlideAgent shows that better performance does not always come from building bigger models. Instead, it points to smarter ways of organizing how AI processes information that can lead to improvement.
The Association for Computational Linguistics (ACL) accepted SlideAgent for presentation at its annual meeting. The 64th ACL 2026 meeting took place July 2-7 in San Diego.
ACL is a scientific and professional organization for researchers in natural language processing (NLP). Its namesake conference is one of the world’s leading venues for presenting NLP research.
ACL 2026 followed a year after Jin completed an internship at J.P. Morgan AI Research, where he worked on SlideAgent. He interned under Rachneet Kaur, Zhen Zeng, and Sumitra Ganesh, all co-authors of the paper. School of CSE Associate Professor Srijan Kumar advises Jin at Georgia Tech.
Along with SlideAgent, Jin authored two other papers accepted at ACL 2026.
“Conferences such as ACL are valuable not only for sharing results, but also for refining future project ideas with the broader community. Discussions across institutions and research areas can reveal limitations, suggest new evaluations, and spark collaborations that are difficult to develop in isolation,” Jin said.
“For SlideAgent, I was particularly interested in feedback on how we can make the framework more computationally efficient without sacrificing accuracy or interpretability.”
]]>As many organizations and businesses are turning to AI to improve workplace efficiency, risk remains high. Between overlooked footnotes and misread graphics, small mistakes can have expensive consequences.
To address this challenge, researchers from Georgia Tech and J.P. Morgan developed SlideAgent. The new framework helps large language models (LLMs) better understand complex visual documents like presentation slide decks, brochures, and reports.
SlideAgent works by breaking documents into multiple levels, allowing the model to analyze both the big picture and the fine details. This human-inspired approach leads to more accurate and reliable interpretation than existing systems.
Beyond improving workplace tools, SlideAgent also points to a broader shift in AI. Instead of building only larger and more powerful models, the work shows how smarter design and more efficient reasoning can improve performance.
]]>The team also found that the new standard's core rules for sending messages and handling errors retain every known security weakness of older versions.
The vulnerabilities could allow an attacker who has already gained access to a vehicle's internal computer network to change or intercept messages, take individual vehicle computers offline, send different information to different systems, or disrupt network communication.
CAN Extra Long (CAN XL), the latest version of the controller area network (CAN), is designed for future cars and other vehicles that need to move large amounts of data between onboard computers. The technology is not yet widely deployed in production vehicles, giving manufacturers an opportunity to address security concerns before it becomes more common.
“Because it isn't widely deployed yet, we have a narrow window to get its security right,” said Associate Professor Saman Zonouz of the School of Cybersecurity and Privacy and the School of Electrical and Computer Engineering, one of the researchers on the project.
“Fixing a standard now is far easier than fixing it once it's built into the hardware of millions of cars that stay on the road for a decade or more.”
Zonouz said CAN XL is expected to become the primary version of CAN, the network that enables computers inside a vehicle to communicate. It is also expected to serve as the main network for driver-assistance systems in future vehicles.
The researchers confirmed the seven vulnerabilities in commercial CAN XL hardware and demonstrated attacks using a physical test setup that mimics a vehicle network.
Modern vehicles can have dozens of electronic control units that manage systems such as sensors, brakes, steering, and entertainment. These computers need to communicate quickly and reliably.
For decades, many vehicles have used CAN for this communication. However, the original version, known as classic CAN, was not designed to handle the volume of data generated by newer vehicle technologies.
CAN XL was developed to provide faster communication, larger messages, and new security features, but the researchers wanted to know whether the new standard’s basic rules were secure. Their testing revealed that they weren’t. They discovered that an attacker who controls one computer on the network could intercept and replace messages or take a targeted computer offline.
“These flaws are in the standard itself, so every device built to follow it inherits them,” Zonouz said. “With CAN XL, there's still time to fix these problems before they reach the road.”
The attacks would require an attacker to first gain control of a computer connected to the vehicle's internal network. The research does not show that CAN XL itself provides a means to break into a vehicle. Instead, it shows what an attacker could do after gaining access.
Several attacks were also faster and harder to detect than similar attacks against classic CAN, according to the authors.
The researchers proposed changes to the CAN XL rules to prevent several of the attacks. They also recommended additional security measures, including message authentication and systems that can detect unusual activity.
The team reported the vulnerabilities and informed the manufacturers of the commercial devices it tested about the bugs it found. One company has already released a fix. The researchers hope their findings will help manufacturers address security weaknesses before the technology becomes more widely used.
A Formal Security Analysis of CAN XL was published in the Proceedings of the 35th USENIX Security Symposium, held Aug. 12-14 in Baltimore, MD. The paper was also named a runner-up for a distinguished paper award.
The study was conducted by Georgia Tech Ph.D. student ZhaozhouTang, Professor Vijay Ganesh, Zonouz, and Provost and Executive Vice President for Academic Affairs Raheem Beyah, along with Khaled Serag of the Qatar Computing Research Institute and Z. Berkay Celik of Purdue University.
The paper and its findings result from projects sponsored by the Hyundai America Technical Center, the Georgia Department of Transportation, and the $7 million CHORUS Center through the National Science Foundation’s Cyber-Physical System Frontier Program.
]]>The CHORUS (Community Hubs for Optimizing Resilience) project will collaborate with coastal communities in Georgia and New York and will be split into two pieces: technology development and community engagement.
“We’re not just building a simulator and hoping it fits the needs of coastal residents,” explains Alex Robel, project leader and Jean “Chris” Purvis Associate Professor in the School of Earth and Atmospheric Sciences. "By collaborating with community partners from the very beginning, we can ensure that what we ultimately develop will be effective because the people who will be using it are helping design it.”
The technology development component will include faculty from the College of Sciences and the College of Computing. The College of Sciences team will develop an AI-based flood simulator and the College of Computing team led by Josiah Hester, associate professor and Catherine M. and James E. Allchin Early Career Professor, will create a web platform that allows users to visualize potential flood impacts.
Traditional flood models can take hours or days to generate results and often require specialized expertise and expensive computing resources. The CHORUS platform will be designed to provide easy-to-understand results in seconds, producing building-scale flood maps that show how water moves through streets, yards, and structures during a range of flooding scenarios. Researchers will use the model to test how specific interventions, such as seawalls, restored marshes, or improved stormwater infrastructure, could affect flooding.
Eventually, users will be able to test their own scenarios through the browser-based tool, enabling them to explore how different decisions could change flood impacts in their communities:
“Users will be able to go into a web browser and indicate where a sea wall could go or change a parking lot into a porous vegetated landscape, then click simulate. Within a few seconds, they’ll have a new flood map showing the impacts of these interventions,” says Robel.
A collaborative effort with the New York Climate Exchange, the project will be funded by Georgia Sea Grant and IBM, with support from Georgia Tech for Georgia’s Tomorrow (GT2), Georgia Tech’s Coastal Equity and Resilience (CEAR) Hub, and the National Sea Grant College Program. The CHORUS project is an initiative of the New York Climate Exchange, where Georgia Tech is a core partner institution.
Community engagement in Georgia is being led by CEAR and the Pin Point Betterment Association, which represents descendants of the historic Gullah Geechee community near Savannah. In New York, the project team is partnering with the New York Climate Exchange and the Waterfront Alliance to work with communities surrounding Jamaica Bay.
“What makes this partnership meaningful is that it puts community voices at the center,” says Jasmine Smith, president of the Pin Point Betterment Association. “Too often, decisions are made to ‘better’ communities without actually involving the people who live there. We hope this partnership can serve as a blueprint for how communities are included in future sustainability projects from the very beginning.”
The project includes community advisory boards and technical advisory boards in both locations. Community members will help identify priority assets, select flood scenarios for analysis, and shape the design of the web-based tool. They’ll also test and offer feedback. Technical advisory boards made up of local officials, planners, and other experts will help evaluate the feasibility of proposed solutions.
“The aim is to blend information from both groups without allowing the technical perspective to override community priorities,” says Robel.
According to Robel, giving communities direct access to flood modeling tools can help close the gap between public input and infrastructure planning.
“We are putting decision making in the hands of the community. With a tool like this, the community can say: ‘We want to prevent flooding at this community center, this school, or this road,’” says Robel. “They can run the model, produce data, and present it to local governments or the Army Corps of Engineers — advocating for potential solutions themselves rather than relying on outside experts.”
Robel sees this project as just the beginning:
“Funded by two-year grants, CHORUS is meant to be a pilot for how this kind of community-centered project can be done. Once we understand some of the challenges and opportunities involved, it will hopefully make it easier for us to scale this work to additional community partners.”
Georgia Tech is actively working to foster more projects that foster community engagement. Collaborative groups at Georgia Tech involved in the CHORUS project include:
The agreement was signed during a Sept. 14 visit by PNNL leadership to Georgia Tech’s Advanced Manufacturing Pilot Facility. It builds on years of successful collaboration between researchers at the two institutions.
The enhanced collaboration has three primary goals: solving big problems through multidisciplinary, multi-institutional research; sustaining and engaging human capital by creating opportunities for students, faculty, researchers, and interns to work on complex real-world challenges; and accelerating technology adoption by taking scientific discoveries and innovations into industry and the federal marketplace.
"Strengthening our partnerships with national laboratories is a strategic priority for Georgia Tech,” said Tim Lieuwen, executive vice president for Research at Georgia Tech. "PNNL is an outstanding partner, and we look forward to deepening connections among our researchers and students, expanding opportunities and access to world-class capabilities and facilities, and advancing discovery, innovation, and national impact together."
PNNL is a U.S. Department of Energy national laboratory that advances scientific discovery and innovations that support reliable energy, national security, and economic competitiveness. Georgia Tech is one of the nation's leading research universities, conducting more than $1.5 billion in research annually and pursuing a mission to develop leaders who advance technology and improve the human condition.
"PNNL and Georgia Tech have a long history of working together," said Deb Gracio, laboratory director of Pacific Northwest National Laboratory. “This agreement provides the foundation to take on difficult research challenges and to leverage our complementary expertise and investments in the years ahead.”
The Strategic Energy Institute (SEI) has played a central role in advancing Georgia Tech's engagement with the national laboratory system and connecting researchers with partnership opportunities.
"As SEI takes on a greater role in coordinating Georgia Tech's national laboratory partnerships, this agreement with PNNL demonstrates how we are building stronger pathways for faculty, researchers, and students to engage with world-class national lab capabilities," said Yuanzhi Tang, SEI executive director.
The National Laboratory Partnership Program supports engagement between Georgia Tech and the U.S. national laboratories. SEI now leads the program, with ongoing support from Georgia Tech’s Office of the Vice President for Interdisciplinary Research. The agreement with PNNL is the first formal agreement established through the program since its transition to SEI.
"This MOU formalizes and strengthens relationships that have been growing for many years," said Scott McWhorter, SEI director of national laboratory partnerships. “It leverages the unique strengths of Georgia Tech and PNNL and provides a framework for expanding engagement across areas of mutual interest.”
Georgia Tech and PNNL bring complementary strengths in energy and environmental systems, electric grid resilience, cybersecurity of critical infrastructure, alternative fuels and advanced materials, biofuels, radiation detection, data science and visual analytics, nuclear nonproliferation, and national security. These capabilities will be brough together through two upcoming Genesis Mission projects.
Bill Pike, PNNL's deputy director for Science and Technology, who joined the laboratory’s leadership delegation for the MOU signing, said the projects reflect the growing partnership and expanding collaboration between the two institutions.
About Georgia Tech
The Georgia Institute of Technology is one of the nation's leading research universities, with strengths spanning engineering, computing, science, business, design, and the liberal arts. With more than $1.5 billion annually in research awards across its Colleges and the Georgia Tech Research Institute, Georgia Tech is among the nation's most research-intensive universities. The Institute's mission is to develop leaders who advance technology and improve the human condition.
About Pacific Northwest National Laboratory
Pacific Northwest National Laboratory draws on its distinguishing strengths in chemistry, Earth sciences, biology and data science to advance scientific knowledge and address challenges in energy resiliency and national security. Founded in 1965, PNNL is operated by Battelle and supported by the Office of Science of the U.S. Department of Energy. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time.
The agreement was signed during a Sept. 14 visit by PNNL leadership to Georgia Tech’s Advanced Manufacturing Pilot Facility . It builds on years of successful collaboration between researchers at the two institutions.
]]>Before a promising new therapy can reach a patient, researchers need to answer a deceptively simple question: Will it work?
For decades, part of the answer has come from animal testing. Animal models have helped scientists make countless medical advances and understand how potential treatments behave in a living system. But they also present scientific and ethical challenges, including one unavoidable limitation: A mouse isn't a human. This limitation is one reason many promising drug candidates fail during human clinical trials.
Now, Georgia Tech is launching a new Institute-wide initiative focused on technologies that help researchers close that gap by studying human health and disease in ways that more closely reflect human biology. This interdisciplinary venture, called Emerging Technologies for Human-Oriented Systems (ETHOS), will advance human-centered research technologies, including new approach methodologies (NAMs) that improve prediction of human responses and support the development of safer, more effective therapies.
“ETHOS reflects Georgia Tech's commitment to advancing innovative approaches to some of society's most pressing health challenges,” said Executive Vice President for Research Tim Lieuwen. “By bringing together expertise from across the Institute and investing in technologies that more closely reflect human biology, we have an opportunity to accelerate discovery, strengthen translation, and help shape the future of biomedical research."
Supported by the Office of the Executive Vice President for Research, ETHOS is built on an interdisciplinary framework that connects researchers across Georgia Tech and with clinical and translational partners. The initiative draws on expertise in bioengineering, materials science, device engineering, computing, and data science. It will be led jointly by the Parker H. Petit Institute for Bioengineering and Bioscience (IBB) and the Institute for Data Engineering and Science (IDEaS).
“What sets Georgia Tech apart is our ability to unify deep expertise in foundational life sciences, bioengineering, and materials science with artificial intelligence and data science,” said Vice President for Interdisciplinary Research Julia Kubanek. “ETHOS creates a framework for connecting those strengths, fostering new collaborations, and enabling researchers to tackle complex health challenges in ways that no single discipline could accomplish alone.”
Ankur Singh, Carl Ring Family Professor in the George W. Woodruff School of Mechanical Engineering and Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University (BME), will lead ETHOS in his new administrative role as deputy director of IBB. Although ETHOS is a new initiative, Georgia Tech researchers have already begun building a NAMs community through an institutional task force and other collaborative efforts. That momentum will continue with the 2027 Suddath Symposium, which will focus on NAMs and bring researchers together across disciplines.
“Georgia Tech has expertise across the full spectrum of these approaches, from AI and computational modeling to engineered tissues and experimental systems,” said JC Gumbart, Dunn Family Professor in the School of Physics. “ETHOS gives us a framework to connect those strengths and accelerate human-centered biomedical research.”
Gumbart co-led the NAMs task force and is co-organizing the symposium with Shuichi Takayama, a Georgia Research Alliance Eminent Scholar and chair of regenerative engineering medicine within BME.
What are new approach methodologies, or NAMs, and how can they help researchers address human health challenges?
NAMs include both physical models, such as organoids and organ-on-chip technologies, and computational models that use artificial intelligence. Each approach has its own advantages and limitations.
Organoids and organ-on-chip are living tissue systems grown in the lab that mimic key features of human biology and help researchers study how the body may respond to new drugs or treatments. These models allow researchers to observe biological responses in human tissue systems, but they are limited by the steep cost of time and resources required to create them.
Computational models take advantage of AI and supercomputing technology to rapidly explore and predict thousands of possibilities. They use existing datasets to examine complex relationships at scale and simulate how potential changes might affect a system. Though these simulations can provide a large-scale prediction of what might happen, they can’t provide evidence of how cells actually respond.
ETHOS emphasizes a bidirectional approach that combines engineered biological systems with predictive computational models. For instance, a scientist who is testing a new drug on an organoid may use AI to predict how the drug could affect a larger population with differing demographics. Conversely, a researcher using a computational model may use an organ-on-chip experiment to validate (or disprove) the computer’s prediction.
“These human platforms allow us to look broad — exploring how therapies behave across populations — and look deep, engineering precise models that reflect an individual patient’s unique health profile,” Singh said.
The adaptability of NAMs gives researchers a more human-centered way to study — and hopefully one day treat — some of humanity’s most pervasive health problems, such as cancer, cardiovascular disease, autoimmune diseases, neurological disorders, infection, and more. Therapies developed using NAMs could be broad-use solutions that impact entire populations or tailored treatments for personalized healthcare. By bringing together strengths in engineering, computing, data science, and the life sciences, ETHOS positions Georgia Tech to help shape the future of NAMs research and technology development.
“The next generation of medical research increasingly relies on models that are both more human and more intelligent. Georgia Tech's strength lies in connecting the physical and digital worlds of biology,” Singh said. “That closed loop between human biology and computation gives us a powerful advantage in developing the next generation of non-animal models for research and drug development.”
The initiative will also include the development of a platform designed to connect researchers across the Institute and help them identify complementary expertise, shared experimental systems, and collaborative funding opportunities. The digital matchmaking system, along with pilot research and technology development, AI integration, grant development, and community building, makes ETHOS a potentially groundbreaking program launching at an opportune time.
“ETHOS is an initiative of convergence. Few institutions combine strengths in advanced human tissue systems, engineering, AI, and data science at the scale of Georgia Tech. ETHOS provides a framework to unite those capabilities and accelerate biomedical discovery and translation,” Singh said.
ETHOS is designed to strengthen connections between fundamental research and real-world health applications. By developing research models that more closely reflect human biology, the initiative could help researchers identify promising therapies earlier and better understand how they may perform in people. ETHOS could also strengthen collaborations among Atlanta's academic, clinical, and industry partners, creating new opportunities for translational research and technology development.
Before a promising new therapy can reach a patient, researchers need to answer a deceptively simple question: Will it work?
For decades, part of the answer has come from animal testing. Animal models have helped scientists make countless medical advances and understand how potential treatments behave in a living system. But they also present scientific and ethical challenges, including one unavoidable limitation: A mouse isn't a human. This limitation is one reason many promising drug candidates fail during human clinical trials.
Now, Georgia Tech is launching a new Institute-wide initiative focused on technologies that help researchers close that gap by studying human health and disease in ways that more closely reflect human biology.
Parker H. Petit Institute for Bioengineering and Bioscience
]]>His paper, “Brain Speaks Louder Than Words: Neurophysiological Opinion Inference via Cognitive Dissonance Triggers,” recently received the 2026 Dr. Hermann Zemlicka Award for the most visionary paper at the NeuroIS Retreat.
Wu discusses the research, its potential applications, and the ethical and privacy considerations it raises.
Q&A With D.J.
What was your reaction when you learned your paper received the 2026 Dr. Hermann Zemlicka Award for “most visionary” research?
The Dr. Hermann Zemlicka Award is presented annually at the NeuroIS Retreat to the paper selected as the year’s “most visionary.” I was surprised and deeply honored to receive it. The recognition was especially meaningful because it affirmed our vision of bringing neuroscience and information systems research together to explore a new way of understanding human opinions.
For readers unfamiliar with your research, what problem were you trying to solve?
We wanted to find a better way to understand people’s opinions in situations where traditional methods, like surveys or tracking behavior, may be biased, intrusive, slow, or difficult to use. Our research explores whether brief brain activity measured by electroencephalography (EEG) can reveal when a statement matches or conflicts with a person’s beliefs. If so, it could provide another way to understand opinions without relying only on what people say or how they behave.
Most people are used to answering surveys, reviews, and polls. What made you wonder if there might be a better way to understand what people really think?
Surveys are extremely useful, but they depend on people actively participating. Those answers can be shaped by factors such as memory, the way a question is worded, social pressure, or a person’s ability and willingness to respond. We wondered whether brain activity could offer another way to understand people’s opinions, especially in situations where those challenges come into play. We wanted to see whether we could capture an immediate reaction before a person has to translate it into words.
The paper title, “Brain Speaks Louder Than Words,” is interesting. Can you give an example of what that means in everyday life?
Imagine someone is asked to rate the statement, “I like this product or service.” Even if they feel pressure to give a positive answer, their brain may respond differently depending on whether the statement matches their experience. Our method looks for patterns of brain activity that occur when there is a mismatch between what a person truly believes and what they are evaluating. It is not mind-reading or lie detection. Instead, it uses the brain’s response to conflicting information as one signal that may help us understand whether a statement reflects someone’s genuine opinion.
Were there any findings that surprised you or challenged what you expected going into the project?
One finding was that cognitive conflict depended on more than whether a statement contradicted someone’s opinion. When a heuristic cue, a simple signal that offers a mental shortcut, was present, the brain response to a conflicting statement became weaker. Put intuitively, some contextual cues can soften our immediate sense that “this does not match what I believe,” even when our underlying opinion remains unchanged.
Privacy is a growing concern in today's digital world. Can you compare the privacy implication of the proposed approach versus the traditional methods?
Our approach could reduce the need to store information such as browsing histories, ratings, or written survey responses. Instead of continuously tracking a person’s behavior, it focuses on collecting a specific brain response during a defined interaction with the user’s consent.
At the same time, brain activity is sensitive biometric information and could reveal more than what is needed for a particular task. Any privacy benefits therefore depend on robust safeguards, including data minimization, meaningful informed consent, clearly defined limits on data use and retention, and strong data security through offline, locally controlled processing and calibration.
Our study offers some initial guidance on these issues, but more research is needed to fully understand the privacy implications of this approach.
How could this research change the way organizations understand customers, employees, or other stakeholders in real time?
In situations where surveys may not tell the whole story, receiving feedback is difficult, or past behavioral data are unavailable, our research could eventually help organizations better understand how people are reacting in near real time. For example, it could help identify whether stakeholders' immediate responses suggest agreement or disagreement with a message, product, digital experience, or decision.
These insights would not replace surveys. Instead, they could complement them by showing where people's immediate reactions align with, or differ from, what they later report. Any use at the individual level, however, would require informed consent, a clearly defined purpose, and strong privacy safeguards.
The paper points to opportunities for helping people who may have difficulty communicating through traditional methods. What possibilities do you see for making technology more inclusive?
Brain-computer interfaces have already shown promise in helping people with severe motor or communication impairments interact with technology. Our research explores one possible way to better understand a person's opinions or preferences through brain activity during specific tasks. Over time, this type of work could contribute to technologies that are more responsive to individual needs and more accessible for people who face challenges communicating through traditional methods.
For readers who haven’t thought about neuroscience or brain-computer interfaces before, what’s the one takeaway you hope they remember from this research?
Brain signals do not provide a direct window into a person's thoughts. They reflect many different processes happening in the brain and body, which means they can be difficult to interpret.
That is why theory and experimental design matter. Rather than searching brain data for patterns without a clear explanation, our research focuses on a specific mechanism: how people respond to information that conflicts with their beliefs. By testing that idea in a controlled setting and calibrating the approach for each individual, we can make the results more meaningful and easier to interpret.
Learn More: Information Technology Management
]]>Most people would recognize that something unexpected has happened and adjust accordingly.
For machines, it’s not always that simple.
Researchers at Georgia Tech’s H. Milton Stewart School of Industrial and Systems Engineering (ISyE) are addressing this very challenge: how can autonomous systems recognize when something unexpected has happened, determine whether it matters, and decide how to respond?
In a recent paper published in the INFORMS Journal on Data Science, the research team introduced a new framework called Mutual Information Surprise, designed to help machines identify meaningful surprises in complex environments. The work could help lay the foundation for AI agents, robots, and autonomous systems that can better navigate unexpected situations, avoid costly mistakes, and make more informed decisions when faced with situations they weren’t designed or trained to handle.
"Traditional automation systems are designed to follow instructions. They do not have a sense of surprise. Machines follow a predetermined recipe and produce the expected result," said Yu Ding, the Anderson-Interface Chair and professor in ISyE, who is leading this project. " Intelligent agents, however, must do more than simply follow instructions. They need to recognize when their current understanding or reasoning process has become inadequate. Humans routinely use surprise for this purpose. An autonomous machine needs an analogous computational capability."
This research concept was jointly worked out by Xiao Liu, the David M. McKenney Family Associate Professor, as well as a former postdoctoral fellow in ISyE, Yinsong Wang, and Ph.D. student Quan Zeng.
While several methods already exist to measure surprise in machines, such as the "Shannon Surprise" and "Bayesian Surprise," the ISyE team saw limitations in both approaches.
Shannon Surprise tends to focus on the rarity of an event, while Bayesian Surprise focuses on how much a new observation changes a system's beliefs.
To illustrate the limitations of existing surprise measures, Ding pointed to the examples of someone noticing a specific type of car parked nearby or a student who consistently earns top grades but suddenly performs poorly on an exam.
Existing surprise measures don't always flag the right kinds of moments to be surprised, Ding said. To the examples given, the Shannon Surprise would flag the specific car parked nearby, although people typically wouldn’t be surprised by that event. Conversely, people would be surprised by the student performing poorly, but the Bayesian Surprise would not flag it.
"We introduce this new surprise definition because it measures the gain of knowledge and epistemic progression, thus capturing the right moments when a system should be surprised and ignoring the moments when it shouldn't," Ding added.
The framework could eventually help systems determine when to continue as planned or when to stop and reassess, whether that's an AI assistant struggling to answer a question, a robot encountering a situation it has never seen before, or an autonomous factory detecting a disruption that could affect production and require human intervention.
Looking ahead, the ISyE research team is exploring potential applications in engineering autonomous systems and is developing a proposal for federally funded programs.
]]>Since its launch in 2025, SRI has brought together researchers from across campus to advance interdisciplinary space initiatives and create new opportunities for collaboration. In their new roles, Ballantyne and Borowitz will help guide the institute's growth by strengthening both internal research connections and external partnerships across the broader space community.
“David and Mariel bring complementary strengths that will be invaluable as we continue building SRI,” said Jud Ready, executive director of SRI. “David has a deep understanding of the research enterprise at Georgia Tech and a passion for connecting people and ideas across disciplines. Mariel brings extensive experience working across government, industry, and the international space community. Together, they will help us strengthen Georgia Tech's space ecosystem and expand our impact far beyond campus.”
Since joining the Institute in 2008 as a founding faculty member of the Center for Relativistic Astrophysics, Ballantyne has helped advance both space science and academic leadership across campus.
A professor in the School of Physics, he studies the evolution of galaxies and their central black holes, as well as the physics of accretion disks around black holes and neutron stars. He has authored more than 140 peer-reviewed publications and served as associate chair of the School of Physics for nearly a decade.
As associate director, Ballantyne will focus on cultivating connections across Georgia Tech's space research community and identifying opportunities for new interdisciplinary collaborations.
“I view SRI as a catalyst — a mechanism to spark new and transformative areas of space research at Georgia Tech that will grow to national and international prominence,” Ballantyne said. “There is so much innovative space research happening across campus, and one of SRI's most important roles is helping researchers find the connections and collaborations that can spark new ideas and discoveries.”
Ballantyne says he is particularly interested in helping position Georgia Tech as a leader in understanding the opportunities and challenges presented by artificial intelligence in space systems.
“My goal is to be out in the community, learning about the breadth of space research happening across campus and identifying ways SRI can accelerate that work,” he said. “AI technologies are poised to transform space exploration, scientific discovery, national security, and commercial space operations. SRI is uniquely positioned to help Georgia Tech lead those conversations.”
As space activities become increasingly interconnected across government, industry, and academia, strong partnerships are essential to translating research into real-world impact. That collaborative spirit is central to the work of Mariel Borowitz, an associate professor in the Sam Nunn School of International Affairs.
Borowitz, who also serves as director of Georgia Tech’s Center for Space Policy and International Relations, is widely recognized for her expertise in space policy, international cooperation, and the governance of emerging space activities. Her work has connected her with space agencies, private companies, and policymakers around the world, providing a valuable perspective on opportunities for Georgia Tech to expand its engagement with the broader space community.
In her role as associate director, Borowitz will focus on growing SRI's partnerships with industry, government, and the broader space community.
“My focus as associate director will be on building partnerships between Georgia Tech and the broader space community,” Borowitz said. “Georgia Tech has tremendous expertise across science, engineering, policy, economics, and international affairs. By working across those disciplines, we can help address the complex challenges facing the future of space development while creating new opportunities for collaboration and impact.”
Borowitz sees SRI as a powerful mechanism for connecting Georgia Tech's diverse strengths and amplifying their collective impact.
“Real-world challenges and opportunities are inherently interdisciplinary,” she said. “The Space Research Institute allows us to bring together expertise from across Georgia Tech to develop more complete solutions and create new possibilities for the future of space.”
Together, Ballantyne and Borowitz will help advance SRI's mission of connecting researchers, educators, students, industry leaders, and policymakers to address the most pressing opportunities and challenges in space.
“Space exploration has always challenged us to think bigger, work across boundaries, and pursue questions that no single discipline can answer alone,” said Ready, who also serves as a principal research engineer at the Georgia Tech Research Institute. “David and Mariel embody that spirit of collaboration, and their leadership will help us create new opportunities for discovery, innovation, and impact at Georgia Tech and beyond.”
The annual U.S. News & World Report Best Colleges rankings are based on assessments from academic leaders at peer institutions nationwide.
The recognition comes at a time of significant momentum for ISyE. This fall, the school moved into George Tower in Tech Square, a new home designed to support learning, collaboration, and innovation while creating new opportunities for engagement with students, alumni, industry partners, and the broader Georgia Tech community.
Demand for ISyE's undergraduate program continues to grow, with a record 1,536 students enrolled for the fall 2026 semester, a 10% increase from the previous year. ISyE graduates continue to find success after graduation, with a median starting salary of $90,000 for 2025-26 bachelor's degree recipients and 84% of job-seeking graduates receiving at least one job offer before graduation. Alumni pursue careers across consulting, logistics, finance, technology, manufacturing, and startups, with top employers including The Home Depot, Delta Air Lines, McKinsey & Company, Capital One, and PwC.
The College of Engineering also achieved a historic milestone in the latest U.S. News rankings, rising to No. 2 nationally. All 10 undergraduate engineering programs were ranked among the nation's top five.
]]>Upon returning to Georgia Tech, Phute reflected on her summer internship and what it taught her about the evolving relationship between research and industry.
Student: Mansi Phute
Research Interests: Machine learning (ML) robustness and artificial intelligence (AI) safety
Degree Program: Ph.D. in Computer Science
Faculty Advisor: School of CSE Professor and Associate Chair Polo Chau
2026 Internship: International Business Machines (IBM), San Jose, California
What about IBM interested you in applying for and accepting an internship there?
IBM is often at the forefront of AI safety, my field of interest, and has a culture that encourages exploratory and fundamental research. I felt this would give me a closer look at cutting-edge industry approaches without compromising on my research interests or my progress toward my thesis.
How well did your coursework and experience at Georgia Tech prepare you for your IBM internship?
My experience at Georgia Tech was very helpful in preparing me for IBM. My coursework and other academic experiences certainly transferred over, but I believe that the wide range of people I met during those courses and what I learned from them helped me connect and relate strongly with people at IBM. Being conversant in different fields of research really helped me interact better with IBM coworkers and feel comfortable in a new environment.
What did you work on while interning at IBM?
I worked on IBM’s AI Foundations team, focusing on the security of multimodal agent communication during my internship. This is an important problem as we see an increase in agents applied in many use cases. It was also closely aligned with my research interests of AI safety.
Do you have a favorite memory or remarkable achievement from your internship?
One of my favorite moments was presenting my work to a broad, cross-team audience of technical and non-technical members. Afterward, my manager told me I was good at explaining my research to people with varying levels of familiarity with the domain. This feedback meant a lot to me because communicating clearly across different audiences is a skill I've deliberately worked to improve. So, hearing that the effort was paying off was very rewarding.
Overall, how helpful was this internship toward your studies at Georgia Tech and your career as an aspiring researcher?
This internship was very valuable for my development as an aspiring researcher. I worked alongside accomplished people in the AI safety field on projects that aligned closely with my research interests. I also saw how those same projects connect to a company's broader business priorities, a perspective that isn’t easily available in academic settings. I shared many fruitful discussions with people working in safety, policy, and alignment, which gave me a much clearer sense of how industry approaches these issues compared to the more academic-oriented framing I am used to.
Based on what you learned during your internship, how important is private industry in progressing research and scientific discovery?
Working in private industry was a fascinating experience. I come away believing that industry plays an important role in advancing research, especially in AI, where companies have access to computing resources that are less prohibitive than in academic environments. I also think that because private industry has a strong hand in implementing and deploying research, understanding industry priorities can help us frame and design our research in ways that complement industry applications. This ensures research has a bigger impact, particularly in the domain of ML safety and reliability.
Upon returning to Georgia Tech, Phute reflected on her summer internship and what it taught her about the evolving relationship between research and industry.
]]>This summer, M.S. student Joey Cuthbert contributed to this mission through an internship at the Air Force Research Laboratory (AFRL). Upon returning to campus, Cuthbert reflected on his internship and what he learned working alongside researchers in government and the defense community.
Student: Joey Cuthbert
Research Interests: Machine learning (ML), model-based systems engineering
Degree Program: M.S. in Computational Science and Engineering, home unit in H. Milton Stewart School of Industrial and Systems Engineering
2026 Internship: Sensors Directorate Internship Program with Air Force Research Laboratory (AFRL) and the National Air and Space Intelligence Center (NASIC), Beavercreek, Ohio
What about AFRL interested you in applying for and accepting an internship there?
The Sensors Directorate Internship Program (SDIP) provided a unique opportunity to work alongside mentors from AFRL and NASIC on a defense-related research project over a 14-week internship. This aligned with my desire to work on applied ML research in the defense sector and allowed me to better understand the ins and outs of government and government-contracting work. The program provided competitive pay and housing throughout the program, which was a huge plus for me.
How well did your coursework and experience at Georgia Tech prepare you for your AFRL internship?
My experience and coursework at Georgia Tech helped me a great deal this summer. I believe my understanding of ML has greatly improved over the past two semesters, which helped me complete my internship project. All of my experiments ran on high-performance computing (HPC) systems, and I felt I had a head start since I completed an HPC class last spring.
What did you work on while interning at AFRL?
I worked on an image-classification robustness project for convolutional neural networks (CNNs) using synthetic aperture radar (SAR) data. I built a robustness benchmark by testing a model against nine types of noise, and used it to show how we can effectively increase robustness by inducing shape-bias in the model during training.
Do you have a favorite memory or remarkable achievement from your internship?
During the summer, we went on a tour of nearby Wright-Patterson Air Force Base, where we visited the sensors directorate buildings and checked out some of their labs. I also received the best poster presentation award among approximately 40 interns.
Overall, how helpful was this internship toward your studies at Georgia Tech and career as an aspiring researcher?
This program provided great strides toward my research career goals. My coursework has provided a great foundation in ML, and I was able to apply this knowledge to a project. The internship offered me lots of autonomy, as well as time to explore different paths to find results.
From what you learned on your internship, how important are government agencies in progressing research and scientific discovery?
I believe government agencies are massively valuable in advancing research and scientific discovery, especially within the defense sector. All work at AFRL has the goal of giving warfighters the greatest advantage possible. This often entails looking 10 to 20 years into the future of science and technology and trying to get there as fast as possible.
This summer, M.S. student Joey Cuthbert contributed to this mission through an internship at the Air Force Research Laboratory (AFRL). Upon returning to campus, Cuthbert reflected on his internship and what he learned working alongside researchers in government and the defense community.
]]>The internship provided Burnett with valuable insight into national laboratory research and reinforced skills he developed through his studies at Georgia Tech. When he returned to campus, we asked Burnett to share more about his internship and what he learned.
Student: Tage Burnett
Research Interests: Fusion energy, computational plasma physics, high-performance computing, and structure-preserving machine learning
Degree Program: Ph.D. in Computational Science and Engineering
Faculty Advisor: School of CSE Assistant Professor Qi Tang
2026 Internship: Oak Ridge National Laboratory, Oak Ridge, Tennessee
Many people are unfamiliar with national laboratories, like ORNL. Could you explain the purpose of these institutions and why they are important?
The Department of Energy (DOE) national laboratories are responsible for moving forward science and technology in the United States and solving high-consequence challenges in science, energy, and national security. They work on both applied and theoretical research with both short-term and long-term returns. ORNL has eight core research areas: biology and environment, energy science, fusion and fission, isotopes, physical sciences, national security, neutron science, and supercomputing. I was an intern in the supercomputing division.
How well did coursework and experience at Georgia Tech prepare you for your ORNL internship?
My coursework at Georgia Tech was vital in my preparation for this internship. I wrote highly parallel code where I leaned heavily on what I learned in CSE 6220: High-Performance Computing. I also worked on numerical methods which required an understanding of partial differential equations and numerical linear algebra which I also learned at Georgia Tech from classes like CSE 6643: Numerical Linear Algebra and a space plasma physics course.
What did you work on while interning at ORNL?
At ORNL, I was a developer on the Adaptive Sparse Grid Discretization (ASGarD) codebase. The code uses adaptive sparse grids and the Discontinuous Galerkin method to beat the curse of dimensionality and solve high-dimensional partial differential equations (PDEs). The code is designed to simulate fully kinetic plasmas in up to 6-dimensional phase space. My project was to implement an iterative method to solve the efficiently solve the Poisson equation within the codebase. This project gave me hands on experience with linear algebra, numerical PDEs, parallel computing and software engineering which was invaluable to my development as a CSE researcher.
Do you have a favorite memory or remarkable achievement from your internship?
My favorite memory from my internship was spending time with the other ORNL interns outside of work. There was an amazing group of interns at ORNL, and it was great getting to know them. One particularly good memory was when we went out to a restaurant with live music and played laser tag during our last week of the internship to celebrate our time at ORNL. The achievement I am most proud of was getting a working, highly efficient version of the Poisson solver into ASGarD. The ASGarD codebase is open source, so I hope other plasma physics researchers will use the code and find it helpful for their research.
While interning, you were selected for a GEM Fellowship, which Georgia Tech and ORNL nominated you for. What does this fellowship mean to you and is there anything you would like to say to your supporters?
To me, receiving the GEM Fellowship indicates that other people recognize the hard work I am doing, and they believe in my ability to meaningfully contribute to the field. Having this support from GEM, ORNL, and Georgia Tech gives me greater confidence in myself and my potential and inspires me to put my all into my work. I would like all my supporters to know that I am so grateful for the opportunity you have given me to be a part of the excellent community of researchers within GEM, ORNL, and Georgia Tech. I will do my very best to make your support worthwhile!
Overall, how helpful was this internship toward your studies at Georgia Tech and career as an aspiring researcher?
The internship was extremely important to both my studies at Georgia Tech and my career as a researcher. The hands-on experience I gained is irreplaceable and it helped me to apply all the skills I have developed throughout my education. I am also optimistic that the internship will open doors for me when I am seeking a job post-graduation.
]]>The internship provided Burnett valuable insight into national laboratory research and reinforced skills he developed through his studies at Georgia Tech. When he returned to campus, we asked Burnett to share more about his internship and what he learned.
]]>“Every living organism runs on chemistry, and metabolomics is the attempt to read that chemistry directly by measuring thousands of small molecules at once: in a drop of blood, a leaf, a microbial colony, and even a single cell,” Fernández says.
Advances in understanding metabolites could provide new insights for cancer diagnostics, drug development, and environmental monitoring.
“The Metabolomics Society’s members are pushing the field forward and translating metabolomics knowledge into real health benefits for society,” he adds. “Being selected by that group of scientists and students feels like a special kind of honor.”
Fernández joined Georgia Tech in 2004 and also serves as the Vasser-Woolley Chair in Bioanalytical Chemistry in the School of Chemistry and Biochemistry. His research focuses on developing tools to measure and analyze small-volume samples, tissues, and single cells. He also directs the Systems Mass Spectrometry Core at the Parker H. Petit Institute for Bioengineering and Bioscience.
His two-year term on the Metabolomics Society's Board of Directors begins Oct. 1.
]]>Ahmadi and Brown find that neighborhoods with higher shares of Black residents experience higher energy burdens, even after accounting for factors such as income, renter status, and housing characteristics. In this study, energy burden refers mainly to the share of household income spent on electricity, gas, and water. The authors estimate that an approximately 11 percentage-point increase in a neighborhood’s Black population share is associated with about a 1 percentage-point increase in household energy burden, equal to an average annual increase of about $785 in utility costs. These findings suggest that unequal energy burdens are tied not only to household finances, but also to the lasting effects of segregation and discrimination.
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]]>When Chevron reported its highest quarterly profit in six years on July 31, 2026, it was just one detail in a larger picture: Analyst firm Wood Mackenzie estimates the global oil and gas industry is on course for a cash windfall of US$495 billion in 2026. That’s profit above and beyond what the industry expected before the U.S.-Israel war with Iran began.
Three separate bills seeking to tax those profits are now in Congress, and President Donald Trump has even said the oil companies are “making too much money.”
As an applied microeconomist, I am often asked how taxes affect economic activity. Economists have long held a more nuanced view of windfall taxes than either side of the current debate suggests. Advocates often make overly optimistic revenue projections, and opponents often overstate how much such a tax might discourage investment. A 1980s U.S. windfall-tax experiment is instructive on both counts.
Read Full Story on The Conversation
]]>Three separate bills seeking to tax those profits are now in Congress, and President Donald Trump has even said the oil companies are “making too much money.”
As an applied microeconomist, I am often asked how taxes affect economic activity. Economists have long held a more nuanced view of windfall taxes than either side of the current debate suggests. Advocates often make overly optimistic revenue projections, and opponents often overstate how much such a tax might discourage investment. A 1980s U.S. windfall-tax experiment is instructive on both counts.
]]>A hospital decides how many operating rooms to staff on a specific day. A vaccine that works in a trial fails to reach the population that needs it. A single manufacturer’s plant shuts down due to a hurricane and a routine medical supply becomes unavailable nationwide. A public health agency has to decide whether limited resources will have greater impact through a screening program or a housing intervention.
These are the types of real-world challenges students in the Health Systems minor will learn to address. They are not purely medical questions. They are systems questions, and they are the kinds of challenges industrial and systems engineers are equipped to solve.
"Many of today’s health challenges are fundamentally systems challenges,” said Pinar Keskinocak, the H. Milton and Carolyn J. Stewart School Chair and professor in ISyE. “Improving health requires not only advances in medicine, but also better systems for prevention, access, care delivery, and decision-making."
The minor was developed by Professors Turgay Ayer, ISyE’s Virginia C. and Joseph C. Mello Chair and professor, and Nicoleta Serban, an ISyE professor, working with faculty across ISyE's health systems area.
“Health systems problems are complex because decisions made in one part of the system often have consequences elsewhere,” said Ayer. “We developed this minor to give students a systems-level understanding of healthcare systems, while equipping them with practical analytical and decision-making tools. Our goal is for students to leave the program prepared to translate data into better decisions and, ultimately, better health outcomes.”
“This minor grew out of years of health systems research and teaching across ISyE,” added Serban. “Through my work in health analytics, Medicaid policy, healthcare access, and health system complexity, and through teaching Public Health Systems, I saw both the breadth of faculty expertise in this area and strong student interest in engaging with it. The minor brings those strengths together in one pathway that enables students from across Georgia Tech to understand health systems and develop the analytical tools to improve them.”
The minor is 15 credit hours: a statistics foundation, two required health systems courses, and at least two electives.
Students begin with a statistics course, choosing from seven options across campus: ISYE 3770, ISYE 3030, BME 2400, ECE 3077, ECON 2250, MGT 2250, or PUBP 3120. This flexibility allows students from a variety of academic disciplines to enter the health systems core with a shared quantitative foundation.
Two ISyE courses form the core. Public Health Systems (ISYE 4510), designed by Serban and Keskinocak, works at the population scale. Many health challenges are shaped long before patients enter a hospital. The course examines factors that influence access to care, prevention, and population health, and explores how engineering and data-driven approaches can improve outcomes.
Students study healthcare access: how to measure it, how geography shapes it, and what epidemiology and spatial analysis reveal about who a system reaches.
The course also spends three weeks on prevention and wellbeing across infectious and non-infectious disease. The organizing theme is what Serban calls the three E's: equity, efficiency, and effectiveness, and the trade-offs among them when resources are finite. Students leave able to identify where quantitative methods can improve public health decision-making.
Intelligent Healthcare Delivery Systems (ISYE 4515) launches alongside the minor. The course was originally designed by Ayer and is being adapted for this minor by Dima Nazzal, ISyE’s associate chair for academic administration, and Lauren Steimle, the Harold R. and Mary Anne Nash Early Career Professor and assistant professor in ISyE. The course focuses on healthcare delivery: how patients move through clinics and hospitals, where care transitions break, and how to map a process well enough to identify where to change it. Students learn to evaluate a health system's performance and model improvements through process design and resource allocation, such as bed allocation, operating room block scheduling, and nurse staffing.
“Just as doctors diagnose and treat disease when patients present with symptoms, students in this class will learn engineering tools to diagnose and solve process problems that lead to symptoms such as delays in care, shortages of medical supplies, and provider burnout,” said Steimle. “With these skills, students will be prepared to help healthcare systems deliver the right care to the right people, in the right place, at the right time.”
The remaining six credit hours come from a slate of more than 25 electives in five categories: health systems analytics and modeling; health policy, economics, and management; environmental, public health, and bio-inspired systems; health systems modeling and optimization; and machine learning and data science for health. The courses come from Biomedical Engineering, the College of Computing, the Scheller College of Business, the Ivan Allen College of Liberal Arts, the College of Design, Civil and Environmental Engineering, and Electrical and Computer Engineering, as well as ISyE. Students are encouraged to choose from more than one category.
"A student can come into this from computing, from policy, from business, from design," said Nazzal. "We built the electives so that whatever quantitative preparation a student already has counts for something, and so that nobody has to leave their major behind to work on health. Health systems problems don't get solved by one discipline, and the curriculum shouldn't pretend otherwise."
Students may also complete an optional experiential component through a health-focused Senior Design capstone, undergraduate research, a Vertically Integrated Project, or a Serve-Learn-Sustain project. Students whose primary project isn't health-related complete a structured addendum connecting the work to health systems challenges.
For most students, courses count toward both major and minor requirements. Prerequisites and full requirements are in the catalog, and students should check them against their own program before declaring.
Georgia Tech is well known for health research. Less well known is the role industrial and systems engineering has played in advancing health systems research for decades.
ISyE's health systems footprint spans different kinds of problems. In healthcare operations, faculty and students work on patient flow, scheduling, capacity, and care coordination inside hospitals and clinics. In health systems and supply chains, they study how care, drugs, vaccines, and medical equipment move across networks of providers and suppliers. In AI and analytics for health, they address medical decision-making, disease modeling, and the role of algorithms in healthcare. In public health systems, they examine access, equity, and population-level resource allocation.
That work runs through a Master of Science in Health Systems, the Center for Health and Humanitarian Systems, and Senior Design projects that have been going into Georgia’s health systems for years. Research collaborators include the Centers for Disease Control and Prevention, Children's Healthcare of Atlanta, Emory University, and the Georgia Department of Public Health among many others. Senior Design sponsors have included Emory Healthcare, Wellstar, Grady Health System, Piedmont Healthcare, and Northside Hospital. These projects are not case studies: student teams work on real challenges brought by sponsors and deliver decision-support tools and other design solutions.
More than twenty ISyE faculty work in health and humanitarian systems, spanning patient-centered decision support, clinician guidance, healthcare operations, health network design, and policy evaluation.
"ISyE has been a leader in health systems research, education, and practice for decades,” said Keskinocak. “This minor creates a clear pathway for undergraduate students from across Georgia Tech to apply analytics, AI, optimization, and systems thinking to some of society's most important challenges in healthcare and public health."
Full requirements are in the Georgia Tech Catalog and on the ISyE Health Systems minor page.
]]>
Despite decades of research, the chaotic nature of turbulence makes it difficult to predict and control. This challenge impedes more than smoother air travel. Solving the turbulence problem could lead to advances in areas ranging from sustainable energy to training a smarter workforce for the era of artificial intelligence (AI).
To advance understanding of turbulence, the National Science Foundation is establishing a new, $30 million Science and Technology Center (STC) at Michigan State University. Georgia Tech is among eight universities supporting the center.
Assistant Professor Qi Tang will join the STC for Transformative Explorations in Multi-Physics and Engineering of Scientific Turbulence (TEMPEST). TEMPEST, launching on Sept. 1, aims to build trustworthy, predictive models of real-world turbulence.
Tang will lead TEMPEST’s modeling and scientific machine learning (ML) efforts. NSF will fund Tang and Georgia Tech with over $1 million from the center’s five-year, $30 million award.
By understanding and predicting turbulence, TEMPEST can unlock new applications, with a focus on fusion energy and national security. The center will also generate long-term research projects with applications in air and space flight, manufacturing, chemistry, and broaden science education and AI fluency.
“Turbulence has resisted prediction for a century,” said Tang, a faculty member in the School of Computational Science and Engineering (CSE).
“STC TEMPEST aims to develop a unified, predictive science that advances fusion energy, improves hypersonic technologies, and deepens our understanding of how stars created the elements that make up our world and ourselves. For everyday people, the center points toward abundant clean energy and faster, more efficient flight."
Turbulence is the motion of a fluid characterized by chaotic changes in pressure and speed. Turbulent flows can occur across all scales, from interactions between subatomic particles to astrophysical scales, including supernovas, black holes, and cosmic rays.
While turbulent flows are common and occur naturally, scientists still do not fully understand them. Small changes in a turbulent flow can produce dramatically different outcomes. Combined with the countless interactions across multiple scales of time and space, this makes turbulence extraordinarily difficult to predict.
“Rather than studying individual pieces of this enormously complex problem in isolation, we are bringing together theory, experimentation, computation and artificial intelligence to develop a deeper understanding of turbulence across scales,” said Michael Murillo, an MSU professor and the director of TEMPEST.
“Our goal is not simply to understand turbulence better, but to make it predictable and controllable in ways that will enable new technologies and scientific discoveries.”
The NSF TEMPEST award supports students and researchers at Michigan State University, Auburn University, Baylor University, Georgia Tech, San José State University, Texas A&M University-Corpus Christi, University of Rochester, and Yale University to combine theory, computation, AI techniques, and experimentation to build trustworthy predictive models of real-world turbulence for high-consequence applications.
Additional partners include Los Alamos National Laboratory, Sandia National Laboratories, Lawrence Livermore National Laboratory, Pacific Fusion, and General Atomics.
Together, TEMPEST researchers will build more accurate and reliable physics-grounded models. The center will test new ideas against real-world observations, then use those results to refine the models.
Tang contributes expertise in ML, scientific computing, and plasma physics to STC TEMPEST.
Earlier this year, Tang received an Early Career Research award from the Department of Energy’s Office of Science. He is using the award to build ML and data science tools that help scientists analyze massive datasets from fusion experiments and simulations.
This interdisciplinary approach is intended to move science from understanding why turbulence behaves as it does to predicting how it will behave. Through prediction and simulation, scientists could eventually engineer solutions to control turbulence in real-world scenarios.
The center will make its data and software broadly available and engage the public through museum exhibitions, immersive media, and educational programs that are expected to reach more than 10,000 K-12 students annually. TEMPEST will also help train an AI-fluent scientific workforce prepared to tackle complex problems across disciplines.
“One reason I am excited to work in TEMPEST is because it aligns perfectly with our School of CSE mission. As a discipline, CSE complements theory and experimentation as a mode of scientific discovery,” Tang said.
“We build computational models to simulate scientific and engineering concepts, like turbulence in this case, so that we can test theories that are too difficult, expensive, or risky for physical experiments.”
]]>A Georgia Tech research team was recently recognized for an influential paper that helped define how applications could run efficiently outside the cloud.
The team received the 10-Year Test of Time Award at the 20th ACM International Conference on Distributed and Event-Based Systems (DEBS 2026) in July.
Professor Umakishore Ramachandran and his former Ph.D. students – Enrique Saurez, Kirak Hong, Dave Lillethun, and Beate Ottenwälder – were recognized for their 2016 paper, Incremental Deployment and Migration of Geo-distributed Situation Awareness Applications in the Fog. Saurez, now a researcher at Microsoft, was the lead author of the paper.
Most of a person’s daily internet use, such as sending emails or shopping, runs through the cloud. Cloud computing does have latency issues, but this is typically not perceptible to people. However, in situation-awareness applications, such as virtual reality or autonomous vehicles, this latency becomes a barrier.
“Cloud computing is not appropriate for these latency-sensitive applications where events occur at computational perception speeds as opposed to human perception speeds. And this is the reason that edge computing became important,” Ramachandran said.
Rather than using the cloud, edge computing brings computation closer to the data source. This method reduces latency and backhaul bandwidth consumption. Beyond latency reduction, edge computing offers other advantages over the cloud. Businesses and organizations that handle confidential data may not want to store their records in the public cloud, and edge computing offers a more secure alternative.
The awarded paper proposed a new programming model, Foglets, that enables domain experts with limited knowledge of edge computing to run their applications on the geographically distributed edge infrastructure.
“We showed that with edge compute you can actually do some of the things that you need for situation awareness applications,” Ramachandran said.
“All of these students that I worked with on this paper have graduated and moved on to industry and academia and are doing great things, so it’s a nice honor to see something we did 10 years back get recognition.”
A Georgia Tech research team was recently recognized for an influential paper that helped define how applications could run efficiently outside the cloud.
The team received the 10-Year Test of Time Award at the 20th ACM International Conference on Distributed and Event-Based Systems (DEBS 2026) in July.
But recent research from Georgia Tech’s School of Economics in the Ivan Allen College of Liberal Arts suggests adding an asterisk to earlier research that makes that conclusion, saying previous studies failed to account for one simple fact: people adapt.
Georgia Tech economist Bobby Harris used a massive database of Fitbit step count data to measure how temperature shapes physical activity and found that extreme heat cuts step counts by 6% when compared to ideal weather. And while residents of the warmest regions cut their activity by an average of only 354 steps on days over 100 degrees, those living in the coldest regions cut theirs by 1,081, according to Harris’ analysis.
To be fair, cold bites, too. On days that stay below freezing, people take roughly 1,000 fewer steps. That’s a 12% drop, enough to pack on a pound over the course of a typical Madison, Wisconsin winter, Harris found.
But as the climate grows warmer, how humanity will respond to warmer temperatures remains a significant concern. In fact, earlier research projected that, by 2050, temperature-driven declines in physical activity could contribute to 500,000 premature deaths a year worldwide and annual productivity losses topping $2.4 billion.
Projections like those typically assume everyone responds to heat the same way, with no capacity to adapt, Harris said.
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This award is part of NASA’s Space Technology Research Grants Program, which supports groundbreaking projects with the potential to transform space science and technology.
Through the three-year, $750,000 award, Mazumdar and her research team will develop laser-based methods to simultaneously measure temperature, chemical species, gas velocity, and other properties in the gases surrounding heat shield materials.
“We aim to implement our measurement techniques in arc jet or plasma jet facilities, like the ones at NASA, to assist with the evaluation of thermal protection systems for next-generation spacecraft,” Mazumdar said.
The project uses ultrafast lasers, which produce extremely short, high-intensity pulses. These pulses allow researchers to study the behavior of molecules on extremely short timescales and measure properties that can improve understanding of the gases surrounding a spacecraft during atmospheric entry.
Mazumdar said she and her students are excited about this project and hope it will help NASA develop new heat shields for spacecraft traveling to destinations such as Mars, Venus, and Titan.
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]]>This award is part of NASA’s Space Technology Research Grants Program, which supports groundbreaking projects with the potential to transform space science and technology.
Through the three-year, $750,000 award, Mazumdar and her research team will develop laser-based methods to simultaneously measure temperature, chemical species, gas velocity, and other properties in the gases surrounding heat shield materials.
“We aim to implement our measurement techniques in arc jet or plasma jet facilities, like the ones at NASA, to assist with the evaluation of thermal protection systems for next-generation spacecraft,” Mazumdar said.
]]>College of Computing alumna Nova Ahmed (CS Ph.D. 2010) will return to campus on Sept. 14 to discuss her two decades of experience applying technology to address social and humanitarian challenges.
Ahmed will present Connecting Systems with Humans as part of the OMSCS Speaker Series. The lecture will explore the evolution of Ahmed's research, from sensing systems designed for eldercare homes to low-resource technologies that address challenges faced by women and marginalized communities.
“I was inspired by many other projects that handled social and humanitarian problems, especially one where Jill Diamond worked on domestic violence under the supervision of Amy Bruckman at Georgia Tech,” Ahmed said. “I thought, ‘this is what work should look like, where lives are changed, and impacts are made.’”
Ahmed’s research journey began with designing sensing systems for eldercare homes as a creative solution to an existing commercial problem. After completing her doctorate, she returned to Bangladesh, where she found that conventional technology design approaches often did not fit communities whose challenges were deeply connected to social and cultural contexts.
Her work subsequently shifted toward low-resource technologies designed for women and marginalized communities.
In her upcoming OMSCS Speaker Series lecture, Ahmed will discuss projects focused on social justice and on preventing violence and sexual harassment, as well as sensing technologies designed to improve people’s lives. She will also share research and projects inspired by students and discuss her ongoing work examining women in computing and STEM, including the stressors faced by undergraduate students in STEM fields.
One of Ahmed’s early projects was Protibadi, a technology-based effort to address sexual harassment in Bangladesh.
Her work designing technology for marginalized communities has reinforced the importance of developing solutions that account for the specific needs and circumstances of the people they serve.
“Designing something is easy, but designing for someone who needs something very different from others, being a marginalized one, takes a lot of courage and often can get overlooked,” Ahmed said. “But once it can be done, it is extremely rewarding.”
Ahmed is a computer scientist and professor at North South University in Bangladesh. Her primary research interests include feminist human-computer interaction (HCI), low-cost sensor systems, and information and communication technologies (ICT) for development.
Ahmed hopes those who attend her lecture this month will take away the importance of continuing to pursue meaningful change.
“The fact that things do not change much, but still we can keep trying to make the world a better place,” she said.
Ahmed said she is looking forward to returning to Georgia Tech.
“I am so humbled, honored, and can't wait to meet many of my old friends,” she said.
The lecture will take place Sept. 14 from noon to 1:30 p.m. in the Klaus Building, Rooms 1116 East and West. The event is free and open to the public.
College of Computing alumna Nova Ahmed (CS Ph.D. 2010) will return to campus on Sept. 14 to discuss her two decades of experience applying technology to address social and humanitarian challenges.
]]>The award is the NSF’s most prestigious honor for early-career faculty and supports researchers with the potential to serve as academic role models and to lead advances in their department or organization.
"Receiving the NSF CAREER Award is a tremendous honor and an opportunity to advance my long-term research agenda,” Saeed said. “It was only made possible by the creativity and dedication of my students and the unwavering support and guidance of my family and mentors.”
Modern data center servers manage resource allocation and load distribution separately, which can result in conflicting decisions. A key idea behind Saeed’s proposal is to develop an integrated view of these operations to improve efficiency without requiring additional hardware.
“When performing operations jointly, you can maximize performance and completely eliminate the chances of conflict,” Saeed said.
Another driver of the project is what Saeed calls the “single queue fallacy.” This occurs when data center load controllers assume that all incoming requests to a server wait in a single queue to be processed.
In reality, servers are much more complex than this and can handle multiple queues at the same time. Modern workloads have heterogeneous load requirements, meaning that different requests end up landing in different queues.
“This single queue fallacy can lead to severe underutilization of these servers,” he said.
Recent research by Saeed shows that a server’s throughput can be doubled by avoiding the single-queue fallacy.
The potential benefits of this project are wide-ranging and impactful. Maximizing server efficiency would reduce costs and energy use. With fewer resources needed, the project could contribute to more sustainable computing infrastructure. Lower operational costs would benefit companies, application developers, and users.
“The goal of my proposal is to develop mechanisms and policies that can allow data center operators to easily maximize the utilization of all hardware,” he said.
As part of the educational component of his proposal, Saeed plans to organize competitions for students to design more efficient load and resource management algorithms using artificial intelligence.
In addition to this award, Saeed was named a Brook Byers Institute for Sustainable Systems (BBISS) Faculty Fellow last fall to support his goal of making data centers more sustainable.
]]>The potential benefits of this project are wide-ranging and impactful. Maximizing server efficiency would reduce costs and energy use. With fewer resources needed, the project could contribute to more sustainable computing infrastructure. Lower operational costs would benefit companies, application developers, and users.
]]>Georgia Tech is hosting the 2026 MFEM (Modular Finite Element Methods) Community Workshop, Sept. 22-25. MFEM supports research in computational physics, earth systems modeling, engineering, energy, and other fields.
The four-day workshop is being held at the Georgia Tech Global Learning Center and will focus on improving software for scientific computing and discovery. Participants can also attend online. Registration for the workshop is open through Sept. 11.
“We're very excited and grateful for the opportunity to have this workshop at Georgia Tech,” said Tzanio Kolev, a computational mathematician at Lawrence Livermore National Laboratory (LLNL).
“Georgia Tech has a great reputation in our field, and hosting at universities is a great way to connect with students. We see students as our future colleagues who will improve MFEM for generations to come.”
MFEM is an open-source software library for solving equations in computational models. Scientists and engineers use it to build and test virtual designs on some of the world’s most powerful supercomputers before creating real-world prototypes.
In fact, MFEM powered a tsunami early-warning model that ran on El Capitan, the world’s second-fastest supercomputer. The framework completed a simulation in a fraction of a second, 10 billion times faster than conventional algorithms. Kolev was part of the team that won the 2025 Gordon Bell Prize for the project.
MFEM’s impact extends beyond its original developers. The AWS Center for Quantum Computing uses the software as the foundation for a tool called Palace. This project runs 3D electromagnetic simulations to aid in the design of quantum computing hardware.
“These workshops have been very beneficial for both the broader user community and also for MFEM developers,” said Kolev.
“Every workshop, we are surprised by the ways people are building on our work, seeing what incredible, interesting, amazing things they do with it.”
Next month’s workshop at Georgia Tech will connect MFEM users and developers from national laboratories, academia, government, and industry.
The United Kingdom Atomic Energy Authority joins LLNL and Georgia Tech in sponsoring this year’s workshop. Nearly 20 scientists from Department of Energy (DOE) laboratories are attending in person. They represent LLNL, Los Alamos National Laboratory, Princeton Plasma Physics Laboratory, and the Naval Nuclear Laboratory.
The workshop’s first day features a free, hybrid tutorial. LLNL’s High Performance Computing Innovation Center will lead the tutorial, helping new users get started with MFEM and learn what the software can do. The tutorial requires separate registration for virtual participants.
The workshop will also host a simulation and visualization contest. Participants can submit images and videos of simulations using MFEM, which will be posted in a gallery. The workshop organizers will select an overall winner.
Further workshop activities include:
The MFEM workshop highlights the role open-source software plays in scientific discovery.
By making tools freely available, researchers can build on each other’s work rather than starting from scratch. This shared approach can accelerate innovation, improve software, and make advanced computing tools accessible to a wider community.
Georgia Tech hosts a Center for Scientific Software Engineering and an Open-Source Program Office. This year’s workshop connects these units with the MFEM community to help put the software into the hands of more researchers across science and engineering.
“The MFEM workshop aims to foster collaboration among all MFEM users and developers,” said Qi Tang, a workshop organizer and assistant professor in the School of Computational Science and Engineering.
“Hosting its annual community workshop brings researchers from DOE laboratories, universities, and industry to campus, giving Georgia Tech faculty and students direct access to experts from the field.”
]]>Georgia Tech is hosting the 2026 MFEM (Modular Finite Element Methods) Community Workshop, Sept. 22-25. MFEM supports research in computational physics, earth systems modeling, engineering, energy, and other fields.
The four-day workshop is being held at the Georgia Tech Global Learning Center and will focus on improving software for scientific computing and discovery. Participants can also attend online. Registration for the workshop is open through Sept. 11.
]]>“The future of computing extends far beyond the tech industry alone, and every sector increasingly relies on computational thinking and digital tools,” Associate Dean for Undergraduate Education Olufisayo Omojokun said.
“Students who double major embody that vision by combining technical skills with expertise in another field. That combination prepares them to solve real-world problems in innovative ways.”
While the national average for double majoring across all undergraduate disciplines sits at roughly 11%, Tech students are charting their own distinct paths. Among recent computer science graduates, 17.5% (596 students) successfully completed at least one minor, and 3.8% (131 students) graduated with a full double major.
“Overall, interdisciplinary interest is high, especially in areas like math, robotics, and economics,” said Bethany Mason, director of computing enrollment.
A Snapshot of Interdisciplinary Paths
While mathematics remains the most common pairing, computing students combine their studies with other fields in a wide range of ways. These combinations reflect individual interests and career goals, shaping how students translate technical skills into different professional contexts.
The top double majors among recent College of Computing graduates are mathematics, applied languages and intercultural studies, and industrial engineering.
Other recent graduates have minored, with Fintech, Mathematics, and Computing and Business being the top choices.
Students pursue degree combinations for a variety of reasons. Elliot Huang (CS and Psychology, 2026), for example, added psychology after becoming interested in how people think. He now applies both fields in computational cognitive neuroscience research.
For Hunter Richardson (CS and Business Administration, 2026), the connection between computing, accounting, and data systems made business a natural complement to his CS studies. He said the combination also helped him during recruiting and will inform his work in Tech Assurance at KPMG.
Oliver Lee (CS and Electrical Engineering, 2025) was drawn to electrical engineering after developing an interest in embedded systems, computer vision, and physical devices. His CS background now gives him a software foundation to apply to hardware and engineering projects.
For Aaron Huang (CS and Biochemistry, Spring 2027), the path to a second major was influenced in part by his parents, both physicians. He has since combined his interests through research in medical labs, where computational methods are increasingly central to the life sciences.
Looking Ahead
The success of these students highlights a clear mandate for the College of Computing: to support and expand these impactful pathways even further.
“Our role is to support those pathways with curricula and advising that make it feasible for students to meaningfully integrate rigorous computing preparation with study across other fields, so they graduate prepared for a wide range of careers and graduate programs,” Omojokun said.
Moving forward, the College is actively exploring how to broaden and formalize more of these interdisciplinary tracks.
“We don't want students to just manually piece together a double major; we want to build structured frameworks that seamlessly blend disciplines from day one,” Omojokun said.
“We’ve already proven it can be done. For years, the immense student demand for combining mathematics and computer science led directly to the creation of our formal, joint mathematics and computing major.”
Looking to the future, the College will use that successful blueprint to design even more formalized joint degrees, helping the next generation of Yellow Jackets change the world through the exponential power of computing.
]]>College of Computing leaders often talk about a concept that defines the field’s future: “X to the Power of Computing.” It is the idea that computing acts as a force multiplier, exponentially amplifying every discipline or industry it touches.
]]>Georgia Tech’s Itamar Kolvin is aiming to solve that problem using molecular motors powered by tiny chemical reactions, giving researchers a new way to guide how fibers assemble into larger structures in the lab. The work could open the door to advances in wound healing, artificial tissues, and organ repair.
Now, Kolvin, an assistant professor in the School of Physics, has been awarded a $747,000 CAREER grant from the National Science Foundation (NSF) to support this research.
The NSF Faculty Early Career Development Program is a five-year grant designed to help promising researchers establish a foundation for a lifetime of leadership in their field. Known as CAREER awards, the grants are NSF’s most prestigious funding for early-career faculty.
“The CAREER award is a crucial opportunity to push this research forward,” says Kolvin. “NSF plays a critical role in advancing science, and we wouldn’t be able to do our work without their support. I’m incredibly grateful for their commitment to advancing science.”
While the body naturally assembles these fibers, their small size makes protein filaments difficult to control in a lab setting. Without guidance, the materials grow randomly, creating weak and disorganized structures. But Kolvin has found that exposing the filaments to controlled fluid flows can help them grow in predictable ways.
That’s where Kolvin’s molecular motors come in. He attaches the motors to rod-shaped particles called microtubules, transforming the otherwise inert particles into microscopic motorboats. Powered by chemical reactions, the microtubules move through the fluid and generate tiny currents. Those currents guide the suspended protein filaments, directing how they align and assemble.
Like sticks in a stream, the current helps the protein filaments align with the flow around them. When millions of filaments interact in this way, they can form bundles, clusters, and large-scale networks.
“How do these rods align, when do they tangle, and when do they form networks?” Kolvin asks. “I’m interested in learning how we may be able to predict and ultimately control that behavior in order to direct the ways these structures can grow.”
Kolvin’s earlier work has already shown success with actin, the filaments responsible for building muscles. When suspended in fluid, the molecular motors helped actin fibers bundle together and form a membrane-like structure.
While that work demonstrated that molecular motors could influence assembly, Kolvin now aims to create a more dynamic, tunable system. Actin is limited, he explains, because of its simple rod-like shape, lack of rigidity, and because its bonds become permanent once the fibers bundle together.
He believes the more rigid, helix-shaped flagella in this new work will offer a wider range of opportunities. “The shape and rigidity of flagella expand the variety of patterns they can form,” he explains. “These new structures could have different applications.”
Through molecular engineering, the Kolvin Lab creates flagella that are temperature-sensitive, meaning that they can make and unmake bonds at different temperatures. This property might be key in creating a system that could be assembled and disassembled on demand.
“This could make it possible to tune materials in real-time by warming or cooling the system," Kolvin explains.
By combining molecular motors with temperature-sensitive protein fibers, Kolvin aims to create systems that can be predictably shaped, assembled, and disassembled on demand, opening the door to new possibilities for tissue engineering and regenerative medicine.
The work could also help answer long-standing problems in physics about active matter and collective behavior, revealing how flow and shape influence the way millions of microscopic building blocks align, pack, and assemble into complex materials.
“This CAREER award provides an exciting opportunity to pursue new ideas and tackle difficult, far-reaching questions,” Kolvin says. “I’m looking forward to seeing where this research leads in the years ahead.”
]]>Speare plans to use the funding to build on her lab’s previous finding that naturally occurring predatory bacteria can reduce disease severity in threatened staghorn corals by defending them against harmful bacteria. Her new research will move beyond direct predator-prey interactions to better understand how bacterial predators influence the broader microbial communities living on corals.
“We know bacterial predators can alter disease outcomes in corals,” explains Speare. “What we don’t yet comprehend is what predation actually does to a complex microbiome inside a living animal. Does a predator simply remove particular bacteria, or can those interactions ripple through the entire microbiome and ultimately affect the host?”
Understanding those changes could reveal why some corals are better able to resist disease and recover from environmental stress than others.
Speare and researchers from the Speare Marine Microbial Ecology Lab will investigate microbial predation outside the laboratory in a whole-community context.
“Most of what we know about microbial interactions comes from studying one or two populations in a test tube,” says Speare. “But microbes can behave very differently in a living host. We want to understand those interactions where they are actually happening.”
Her research will use staghorn corals as a model for observing these interactions over time. Because corals are made up of colonies of genetically identical animal polyps, scientists can repeatedly sample the same colony and track how its microbial communities change. This approach offers a unique window into how microbiomes evolve within an animal host, something that is much more difficult to study in many other animals used in research
"One of the really powerful things about corals as a model is that we can repeatedly observe what is happening within the same host," says Speare. "Instead of taking a single snapshot of a microbiome, we can follow how interactions unfold through time and explore how those changes ultimately affect the animal."
Speare hopes the research will uncover how bacteria interact within coral microbiomes and whether those interactions can help corals stay healthy and resist disease.
“It’s unusual to have a model system where fundamental questions about microbial ecology can have such immediate relevance to conservation,” says Speare. “If we learn something that can improve coral health or restoration efforts, we can communicate those findings directly to the practitioners who are actively working to restore these populations.”
Speare credits two prior grants for providing preliminary data for the MIRA award. A NOAA Ruth D. Gates Coral Restoration Innovation Grant helped her develop disease models and investigate the potential health applications of predatory bacteria in corals. A Georgia Tech Sustainability Next Seed Grant filled a critical knowledge gap in the research by testing how these bacterial predators interact with healthy corals.
“Before we could ask what microbial predation does within a complex microbiome, we needed to establish that these predators could persist within corals without negatively affecting the host,” says Speare. “That work gave us the foundation to start asking much bigger ecological questions.”
The Sustainability Next Seed Grant, administered by the Brook Byers Institute for Sustainable Systems, also supported workshops and collaboration-building efforts that strengthened partnerships with the University of Miami’s Lirman Lab and Rescue a Reef which provide corals and expertise for ongoing restoration-focused research.
“The flexibility that comes with this funding is incredibly exciting,” says Speare. “We have five years to follow the biology wherever it leads us. If we discover an unexpected interaction or mechanism, we have the freedom to pursue it rather than being constrained by a single predefined project. That gives us the opportunity to build a much broader understanding of how microbial predation influences coral health.”
Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number 1R35GM165598.
]]>
Communications Manager I
]]>Instead of becoming steadily stickier as they are pulled apart, soft hydrogels first become less adhesive and then more adhesive as the pulling speed increases, revealing a previously unknown "sweet spot" where detachment is easier. The discovery challenges a long-held assumption in adhesion mechanics and reveals a new physical mechanism that governs how soft materials attach and detach.
"We expected the adhesion to increase continuously with pulling speed, as predicted by classical theories," said Yuhang Hu, associate professor in the George W. Woodruff School of Mechanical Engineering and the School of Chemical and Biomolecular Engineering. "Instead, we found the exact opposite over a broad range of speeds. That told us there had to be a completely different physical process at work."
]]>George W. Woodruff School of Mechanical Engineering
]]>"One of the goals of the program is to give students the time and support needed to make meaningful progress on their dissertation research while helping them understand the broader policy, economic, and societal implications of their work," said Laura Taylor, director of EPIcenter.
The stipends enable participants to focus exclusively on clearly defined research goals. The program also supports peer discussions, communication training, and interdisciplinary learning opportunities designed to strengthen both their research and professional development.
This year's cohort explored topics ranging from electricity markets and air pollution to critical mineral supply chains and grid modernization, highlighting the breadth of energy-related research taking place across Georgia Tech.
Exploring Complex Energy Challenges
Ana Mazmishvili, who studies environmental and energy economics, used the summer to examine how climate policies affect communities across state lines.
"My research measures who is actually exposed to pollution from power plants when some states adopt climate regulations to cut emissions while neighboring regions do not," Mazmishvili said. "Because air doesn't stop at state borders, the key question is what happens once the pollution is emitted, and who ends up breathing it."
Her work focuses on the Regional Greenhouse Gas Initiative (RGGI), a cap-and-trade program in the Northeast, and investigates whether the benefits and burdens of emissions reductions are distributed equitably between regulated and neighboring states.
Mazmishvili said the program provided valuable time to focus on her job-market paper, a central component of her dissertation.
"The regular meetings with the program director and other fellows create useful accountability checkpoints and let me hear perspectives from people in very different fields," she said. "We're also learning how to make academic research understandable to a general audience, a skill I expect to use well past this summer."
Industrial and systems engineering doctoral student Faeze Fahimi Aghda spent the summer developing an optimization model for the U.S. gallium supply chain, a critical component of many advanced technologies.
Her research uses mathematical modeling to examine where and when domestic gallium processing facilities should be established under the threat of supply disruptions.
"Working on my research through EPIcenter has taught me to look at my problem from a policy point of view rather than focusing only on the math," Fahimi Aghda said. "The feedback within the meetings helped me improve my model."
Ryan Anthony, in the Jimmy and Rosalynn Carter School of Public Policy, explored how one of the largest oil shocks in U.S. history affected electricity customers and whether utility ownership influenced the impact on consumers.
"So far, my research suggests that it mattered a lot,” Anthony said. “Municipal utilities held rates down and absorbed many of the costs, while private, investor-owned utilities passed more costs through to their customers."
Anthony said the program provided critical support for the archival research required for the project.
"My project depends on data that only exists in old government reports, and that kind of archival work is difficult to fund," he said. "EPIcenter gave me the time and space to do it properly."
Connecting Research to Real-World Impact
For Samin Alipour, the summer provided an opportunity to explore how electric grids can adapt to growing numbers of distributed energy resources.
"Most electric distribution systems were built like one-way roads, carrying power from a substation to homes and businesses," Alipour said. "Rooftop solar, batteries, and electric vehicles are turning those roads into two-way systems."
Her research examines how these emerging technologies can be coordinated to increase grid flexibility and clean energy adoption while maintaining safety and reliability and ensuring that costs and benefits are distributed fairly.
With support from EPIcenter, Alipour focused on the economic and policy dimensions of those challenges. "I did not want my research to remain only a technical model," she said. "The program has helped me connect the technical results of my dissertation to economic value, reliability, equity and compensation policy."
One study developed during the summer was accepted for presentation at a specialized power systems conference, an achievement Alipour credits in part to the opportunity to focus on the broader implications of her work.
Building the Next Generation of Energy Scholars
Beyond advancing individual research projects, the Summer Research Program encourages students to engage with colleagues from different disciplines and develop skills for communicating complex ideas to broader audiences.
“Through regular cohort meetings, participants build a community of accountability, discuss research challenges, explore interdisciplinary energy topics, and develop communication skills,” said Gil Gonzalez, program support coordinator for EPIcenter. “Students also write a research-focused blog post for EPIcenter and present their work at the program's fall workshop, which allows them to share their research with the broader Georgia Tech energy community.”
As EPIcenter continues to support interdisciplinary energy scholarship at Georgia Tech, the Summer Research Program equips future leaders with the tools to address complex energy challenges through technological innovation, informed policy, and economic analysis.
]]>"One of the goals of the program is to give students the time and support needed to make meaningful progress on their dissertation research while helping them understand the broader policy, economic, and societal implications of their work," said Laura Taylor, director of EPIcenter.
The stipends enable participants to focus exclusively on clearly defined research goals. The program also supports peer discussions, communication training, and interdisciplinary learning opportunities designed to strengthen both their research and professional development.
This year's cohort explored topics ranging from electricity markets and air pollution to critical mineral supply chains and grid modernization, highlighting the breadth of energy-related research taking place across Georgia Tech.
]]>Shreyes N. Melkote, Morris M. Bryan Jr. Professor in the George W. Woodruff School of Mechanical Engineering and executive director of the Novelis Innovation Hub at Georgia Tech, has been named interim associate vice president of Corporate Engagement, effective Sept. 1. He will report to Executive Vice President for Research Tim Lieuwen and will lead the Office of Corporate Engagement (OCE) during a national search for the position’s permanent successor.
Melkote succeeds J. Mark Nolan, who announced he will step down from the role effective Aug. 31 after helping establish and grow Georgia Tech’s integrated approach to corporate engagement and industry partnerships.
“I am grateful to Shreyes for stepping into this important leadership role during this transition,” said Lieuwen. “Throughout his career, he has demonstrated an exceptional ability to build meaningful partnerships between academia and industry. His deep understanding of research, innovation, and corporate collaboration makes him uniquely qualified to lead our corporate engagement efforts as we continue advancing Georgia Tech’s mission and strengthening relationships with industry partners around the world.”
Melkote brings extensive experience building industry partnerships and collaborative research programs. He serves as executive director of the Novelis Innovation Hub at Georgia Tech and has led the Institute’s strategic engagement with The Boeing Company since 2012 through its University Innovation Program. An internationally recognized manufacturing researcher, Melkote has authored more than 300 publications and is a fellow of ASME, SME, and CIRP.
“I am honored to serve in this role and build upon the strong foundation established by Mark Nolan and the Office of Corporate Engagement team,” said Melkote.
A national search is underway for the permanent associate vice president of Corporate Engagement. The search is being led by Chris Jones, John F. Brock III School Chair and Professor in the School of Chemical and Biomolecular Engineering, with support from executive search firm WittKieffer.
Learn more about the position and search process.
Join Georgia Tech undergraduate Harrison Burnside on this latest episode of Engineered at Tech as he tours Katherine Graham's lab and discovers how to track pathogens in the Chattahoochee River. The goal is to help local agencies pinpoint sources of pollution in rivers and reservoirs to protect public health.
Watch the video on the COE News page
]]>Join Georgia Tech undergraduate Harrison Burnside on this latest episode of Engineered at Tech as he tours Katherine Graham's lab and discovers how to track pathogens in the Chattahoochee River. The goal is to help local agencies pinpoint sources of pollution in rivers and reservoirs to protect public health.
]]>Launched in 2025, INNS serves as a hub for neuroscience and neurotechnology research, connecting researchers across disciplines to advance discovery, innovation, and societal impact.
“A core part of INNS's mission is helping people find one another, connect around shared interests, and build something bigger than they could accomplish alone,” says Executive Director Christopher Rozell. “Simon has spent his career bringing together people, perspectives, and disciplines to tackle complex challenges. I can't think of a better person to help lead our interdisciplinary research efforts and support the next generation of collaborative neuroscience research.”
A longtime leader in Georgia Tech's neuroscience community, Sponberg helped shape the institute's early foundations through the Neuro Next Initiative, which evolved into INNS. As associate director, he will help guide research strategy, foster new collaborations, and support interdisciplinary work across the neuroscience ecosystem.
“Neuro-related research touches so many fields that we inevitably have a problem of finding all the potential right people and opportunities to tap into,” he said. “A core responsibility of this role is helping catalyze the ideas of new teams of talented researchers, educators, and trainees from inception to realization.”
Sponberg is the Glen Robinson Professor in Complex Systems with appointments in the School of Physics and the School of Biological Sciences, where he directs the Agile Systems Lab. His work also connects him to the Institute for Bioengineering and Bioscience (IBB) and the Institute for Robotics and Intelligent Machines (IRIM), underscoring the cross-disciplinary approach that defines both his research and leadership.
Since joining Georgia Tech in 2014, he has built a highly collaborative research program spanning neuroscience, biology, physics, engineering, and robotics while helping foster interdisciplinary connections across campus. He currently leads a Multidisciplinary University Research Initiative (MURI) that brings together neuroscientists and engineers from five universities to understand how brains achieve fast, flexible perception and decision-making in complex sensory environments. He also co-leads the Integrative Movement Sciences Institute, an NSF Biological Integration Institute focused on understanding movement and muscle function across scales.
His contributions have been recognized through numerous honors, including a Young Investigator Award from the International Society for Neuroethology, a Klingenstein-Simons Fellowship in the Neurosciences, and the Leddy Family Dean’s Faculty Excellence Award.
As associate director, Sponberg will focus on helping researchers identify new opportunities for connection and collaboration. In addition to overseeing seed funding programs, he hopes to create pathways for researchers to build teams, access support resources, pursue ambitious interdisciplinary research ideas, and team with Georgia Tech’s undergraduate and graduate neuroscience degree programs.
“I look forward to being a resource for our community when people are looking for help in building teams or finding opportunities to support their ideas,” he said. “Bring your best ideas and please reach out if you want to talk about ideas in the interdisciplinary neuro space that you want to see realized.”
Techlanta is organized in collaboration with Georgia Tech OIT, the new Allen–Davidson–Coleman XR Makerspace, the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), and the Symbiotic and Augmented Intelligence Laboratory (SAIL).
The event will feature Georgia Tech and Atlanta technology leaders exploring the convergence of artificial intelligence, extended reality, robotics, human-centered systems, and other emerging technologies. Programming will include keynote and featured presentations, live technology demonstrations, networking, and opportunities to engage with the Atlanta technology ecosystem.
“Techlanta is an exciting opportunity to share our vision for Human-Centered Systems Engineering in ISyE, where we put people at the center of how we engineer emerging technologies,” said ISyE Associate Professor, SAIL, and ADC XR Makerspace Director Mohsen Moghaddam. “Through SAIL and the ADC XR Makerspace, we are exploring how AI, robotics, XR, and related technologies can augment people and expand their capabilities in future workplaces, rather than replace them.”
Professor Moghaddam will be presenting the latest developments from ISyE’s Allen–Davidson–Coleman (ADC) XR Makerspace and ISyE’s Symbiotic and Augmented Intelligence Lab (SAIL).
Techlanta builds on the organizations’ ongoing collaboration to showcase Atlanta’s position as a global hub for emerging technology innovation while creating new connections between industry, research, and the next generation of talent.
Registration is now open for Techlanta 2026. Register now →
https://www.eventbrite.com/e/techlanta-2026-tickets-1993945297059
“Atlanta continues to strengthen its position as a global hub for emerging technologies, and we’re excited to build on our collaboration with Georgia Tech, one of the world’s premier universities, to drive applied R&D and strategic innovation across the Southeast and beyond,” said Adam Kornuth, Atlanta Chapter President of the VRARA and AAIA Atlanta chapters.
With over 60 chapters around the world, the VRARA and AAIA boast a network of more than 80,000 professionals and 4,000 organizations.
For more information about the Virtual Reality Augmented Reality Association, visit thevrara.com. For more information about the Applied AI Association, visit aaiaglobal.com.
]]>
Courtney Hill
Communications Program Manager
Office of Information Technology
courtney.hill@gatech.edu
The Air Quality Index (AQI) measures how clean or polluted the air is. A healthy AQI is between zero and 50, but when wildfire smoke blows in and settles over cities, the AQI can reach levels of 500 or more. Poor air quality changes where and how people spend their time and money, reduces productivity (even for those working indoors), and increases healthcare costs.
“Environmental regulations like the Clean Air Act dramatically improved our air quality over the past 40 years, but as wildfire season becomes the new normal, wildfire smoke is eroding those gains,” Wichman said. According to recent research, wildfire smoke has erased about a quarter of the progress made over previous decades, and more than half in many western states.
Read Full Story on the IAC News Page
]]>The Air Quality Index (AQI) measures how clean or polluted the air is. A healthy AQI is between zero and 50, but when wildfire smoke blows in and settles over cities, the AQI can reach levels of 500 or more. Poor air quality changes where and how people spend their time and money, reduces productivity (even for those working indoors), and increases healthcare costs.
“Environmental regulations like the Clean Air Act dramatically improved our air quality over the past 40 years, but as wildfire season becomes the new normal, wildfire smoke is eroding those gains,” Wichman said. According to recent research, wildfire smoke has erased about a quarter of the progress made over previous decades, and more than half in many western states.
]]>Instead of becoming steadily stickier as they are pulled apart, soft hydrogels first become less adhesive and then more adhesive as the pulling speed increases, revealing a previously unknown "sweet spot" where detachment is easier. The discovery challenges a long-held assumption in adhesion mechanics and reveals a new physical mechanism that governs how soft materials attach and detach.
"We expected the adhesion to increase continuously with pulling speed, as predicted by classical theories," said Yuhang Hu, associate professor in the George W. Woodruff School of Mechanical Engineering and the School of Chemical and Biomolecular Engineering. "Instead, we found the exact opposite over a broad range of speeds. That told us there had to be a completely different physical process at work."
Read the full story on the George W. Woodruff School of Mechanical Engineering website.
]]>Instead of becoming steadily stickier as they are pulled apart, soft hydrogels first become less adhesive and then more adhesive as the pulling speed increases, revealing a previously unknown "sweet spot" where detachment is easier. The discovery challenges a long-held assumption in adhesion mechanics and reveals a new physical mechanism that governs how soft materials attach and detach.
"We expected the adhesion to increase continuously with pulling speed, as predicted by classical theories," said Yuhang Hu, associate professor in the George W. Woodruff School of Mechanical Engineering and the School of Chemical and Biomolecular Engineering. "Instead, we found the exact opposite over a broad range of speeds. That told us there had to be a completely different physical process at work."
]]>For researchers in Georgia Tech's Cyber-Physical Security (CPSec) Lab, however, the vulnerabilities behind many of these incidents are far from new.
Associate Professor Saman Zonouz leads the CPSec Lab and has studied programmable logic controllers (PLCs) for years. These devices automate critical infrastructure, including water treatment facilities, power grids, manufacturing plants, and transportation systems. The lab’s work has revealed widespread internet exposure and software vulnerabilities that leave many industrial control systems vulnerable to cyberattacks.
"Out of the 16 critical infrastructure sectors defined by the Cybersecurity and Infrastructure Security Agency, four are considered lifelines," Zonouz said. "Of those four, communications, energy, transportation, and water, the water sector is the most vulnerable, which is why it is so often targeted."
PLCs serve as the brains of industrial operations, monitoring sensors and controlling equipment that keep essential services operational.
"Imagine you have a thermostat that controls the temperature of your house. That is a type of controller," Zonouz explained. "The professional version does the same thing in industry."
When these controllers are directly accessible from the internet, attackers can exploit them to disrupt operations, manipulate industrial processes, or interfere with the systems that deliver essential services. Controllers may be intentionally exposed to allow operators to monitor equipment remotely. They can also be unintentionally accessible online because of configuration errors.
However, internet exposure is only part of the problem.
The CPSec Lab maintains a collection of PLCs that researchers reverse engineer to better understand their firmware, communication protocols, and security weaknesses. Their research has found that many controllers contain vulnerabilities that attackers can exploit once they gain access.
"Not only can the attackers see the house they want to rob, but the doors are also left unlocked," Zonouz said.
In 2024, Zonouz and his collaborators presented PLCHound at the ACM Conference on Computer and Communications Security (CCS), introducing an automated system that identifies internet-connected PLCs hidden within massive internet-scale datasets collected by services such as Shodan and Censys. The work was led by Ph.D. student Ryan Pickren. Provost and Executive Vice President for Academic Affairs Raheem Beyah, Assistant Professor Frank Li, and Research Scientist Animesh Chhotaray are co-authors of the study.
Rather than relying on traditional scanning techniques, PLCHound identifies subtle network signatures that reveal industrial devices that prior methods often missed. Using the system, the researchers conducted one of the largest studies of publicly reachable PLCs from major manufacturers.
Their findings showed that previous estimates undercounted the number of internet-accessible industrial controllers by as much as 37 times. Even more concerning, nearly 96% of the identified devices exposed protocols linked to recently disclosed critical vulnerabilities.
The researchers did more than document the problem. After identifying exposed devices, the team launched a large-scale notification campaign, contacting more than 7,000 industrial operators to alert them that their systems appeared vulnerable. The effort enabled many organizations to investigate and address security issues before they could be exploited.
The recent attacks on municipal water systems reinforce concerns researchers have raised for years: many critical infrastructure operators continue to rely on operational technology designed primarily for reliability and performance rather than for cybersecurity.
Improving those defenses, Zonouz said, will require more than simply patching individual vulnerabilities.
The researchers cite the energy sector as a model. Compared with other critical infrastructure sectors, electric utilities generally operate under more mature cybersecurity requirements and undergo routine compliance audits, providing organizations with greater visibility into the devices connected to their networks and the risks they pose.
Implementing those improvements will not be easy. Many municipal water utilities operate with limited budgets and aging infrastructure, leaving little funding available for cybersecurity investments. As attacks on critical infrastructure become more frequent, the researchers argue that gaining visibility into operational technology assets and strengthening oversight are essential first steps to protect the systems communities rely on every day.
The CPSec Lab is a collaborative laboratory within the School of Cybersecurity and Privacy as well as the School of Electrical and Computer Engineering.
]]>For researchers in Georgia Tech's Cyber-Physical Security (CPSec) Lab, however, the vulnerabilities behind many of these incidents are far from new.
]]>Communications Officer II at the School of Cybersecurity and Privacy
]]>Georgia Tech received the $18.1 million award through NSF's Programmable Cloud Laboratories initiative, a national effort to create AI-enabled automated laboratories that researchers can access remotely.
ISyE’s contribution is led by Pascal Van Hentenryck, the A. Russell Chandler III Chair and professor in ISyE, and includes faculty members Nagi Gebraeel, Roshan Joseph, Kamran Paynabar, Eunhye Song, Xiaochen Xian, and Yao Xie. The broader multidisciplinary effort is co-led by Van Hentenryck, Aaron Stebner, associate director of the Georgia Tech Manufacturing Institute (GTMI), Eugene C. Gwaltney Jr. Chair, James R. and Sarah R. Borders Faculty Fellow, and professor in the School of Materials Science and Engineering, and Tom Kurfess, GTMI executive director and HUSCO/Ramirez Distinguished Chair in Fluid Power and Motion Control in the George W. Woodruff School of Mechanical Engineering.
“Manufacturing is moving toward intelligent, autonomous, and interconnected systems that can learn, adapt, and accelerate innovation,” said Pinar Keskinocak, the H. Milton and Carolyn J. Stewart School Chair of ISyE. “This award positions ISyE and Georgia Tech at the forefront of that transformation. By combining ISyE’s strengths in AI and systems engineering with interdisciplinary collaboration and state-of-the-art facilities, this initiative will accelerate scientific discovery and autonomous manufacturing, and create new opportunities to tackle complex challenges in engineering and manufacturing.”
At the center of Georgia Tech’s contribution is the Advanced Manufacturing Pilot Facility (AMPF), operated through GTMI. The facility combines advanced manufacturing equipment, industrial robotics, and automated research capabilities to help accelerate the development of new materials and manufacturing technologies.
While the initiative brings together experts from multiple disciplines, many of its core challenges align closely with ISyE’s strengths in systems thinking, optimization, machine learning, workflow design, and systems engineering. As part of the effort, ISyE researchers will contribute expertise in these areas to support the development of autonomous research workflows and AI-enabled manufacturing systems.
“This is the AI that will transform scientific discovery and manufacturing,” said Van Hentenryck, who also serves as the director of the NSF AI Institute for Advances in Optimization. “This is deep multidisciplinary collaboration.”
Beyond its research impact, the initiative will provide ISyE students with hands-on experience working on complex, multidisciplinary challenges involving AI, robotics, and scientific discovery while gaining exposure to new domains where ISyE methodologies can be applied.
“This type of deep collaboration across disciplines gives students a window of what is possible in the future and how they can help shape it,” Van Hentenryck added.
]]>Communications Manager I
]]>Eunhye Song, a Coca-Cola Foundation Early Career Professor and associate professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Tech, has been named vice president/president-elect of the INFORMS Simulation (I-SIM) Society, recognizing her leadership and growing impact in the field of simulation.
I-SIM is a specialized community within the Institute for Operations Research and the Management Sciences (INFORMS) dedicated to advancing simulation research and practice while fostering collaboration and professional development among members of the simulation community.
Simulation has become increasingly important as advances in computing and data availability enable researchers to build more detailed models of complex real-world systems, helping organizations evaluate decisions before implementing them and avoid costly trial and error.
“We have much more data, computing power and the ability to build more detailed simulation models than ever before,” Song said. “That’s exciting because we’re getting closer to accurately representing what’s happening in the real system.”
Song’s connection to the simulation community spans over a decade. She first attended I-SIM's flagship Winter Simulation Conference as a first-year Ph.D. student in 2013 and has participated ever since. After joining the faculty ranks in 2017 – first at Penn State University between 2017 and 2022, then at ISyE where she joined in 2022 as an assistant professor – she became increasingly involved in service and leadership activities within the society.
As vice president/president-elect, which is a two-year term that began in July, Song will help guide the organization’s priorities and support initiatives that advance simulation research while identifying emerging areas of focus for the field.
“I’m honored to help the society think about the most relevant and emerging areas in simulation,” Song said.
Beyond its research mission, Song said the simulation community has played a key role in shaping her professional journey through mentorship, collaboration and service.
"I-SIM is a very tight-knit community, and I have received so much advice and mentorship from previous and current members,” Song said. “By the time it’s your turn to lead, everyone is happy to step up. I look forward to helping continue that great tradition in this new role.”
With more than 12,000 members worldwide, INFORMS is the leading international association for professionals in operations research, analytics, management science, and related fields. The organization advances the science and technology of decision making through publications, conferences, competitions, networking communities, and professional development services.
Communications Manager I
]]>Recycled materials promise a cleaner future, but recycled content alone does not necessarily make a product sustainable. At Georgia Tech’s Daedalus Lab, assistant professor, National Science Foundation CAREER Award recipient, and Brook Byers Institute for Sustainable Systems Faculty Fellow Christos Athanasiou and postdoctoral researcher Danqi Sun are working to provide greater certainty to designers and engineers by rethinking how materials are tested for their fracture characteristics. Their article in Science Advances details a new testing protocol that reduces cost, increases speed, and simulates real-world conditions.
Materials shape nearly every part of modern life, from packaging and consumer products to bridges and medical devices. Choosing the right material involves balancing durability, cost, manufacturability, and environmental impact. Yet those decisions are not always guided by a clear understanding of how materials age and fail under real-world conditions, especially for recycled materials like plastics.
One way that materials frequently fail is by cracking. A small crack can begin almost invisibly. Over time, it can spread from regular wear and tear and exposure to common environmental factors like moisture, temperature fluctuations, or even dirt. Eventually, the crack expands, and the part fails. Engineers have studied fracture for more than a century, but connecting the science of cracking to practical decisions about sustainability remains a major challenge.
The characteristics of recycled plastics often vary from those of the same material in unrecycled, or virgin, form. Products made from recycled plastics may be sold with sustainability claims under the assumption that they will perform as if they were made with virgin material. However, premature failure requiring repair or replacement can quickly change the sustainability equation as well as the acceptance of recycled materials by manufacturers and consumers.
Materials rarely fail due to a single factor. They may be exposed to several factors simultaneously, such as mechanical loading, chemical environments, temperature changes, moisture, and time. Traditional fracture protocols test one specimen at a time under carefully controlled laboratory conditions, which bear little resemblance to the real world. To move beyond this limitation, Sun developed an in-situ, high-throughput platform capable of studying how materials degrade and fail under more realistic conditions.
The platform changes conventional fracture testing in three important ways. First, it can test multiple specimens simultaneously rather than one at a time. By monitoring samples in parallel, testing time can be reduced by more than 60%. Second, it allows materials to be tested in realistic environments. In this study, researchers examined virgin and recycled plastics in alkaline environments that resemble conditions encountered in applications like landfill liner membranes and geotextiles. Third, the platform incorporates an imaging technique known as photoelasticity, which reveals the formation of stress fields that form around the origin of a newly developing crack. This allows researchers to see cracks develop earlier than before, giving them a clearer picture of the forces that drive crack growth.
The researchers have made the technology available for licensing through Georgia Tech’s Office of Technology Licensing. “Our goal was to make fracture testing not only faster but also more informative,” Sun said. “By combining high-throughput testing, realistic environments, and full-field stress imaging, we can better understand how materials fail under conditions closer to real-world applications.”
Recycled plastics are often viewed as a greener choice. But according to the study, it’s not always so straightforward. If a recycled product fails prematurely and needs to be replaced frequently, its environmental and economic costs can increase despite its recycled content. As Athanasiou puts it, “Failing materials don’t just break products. They can break sustainability promises.”
For example, comparing virgin polyethylene terephthalate (PET) with recycled PET (rPET) in applications such as landfill geotextiles, the researchers discovered that rPET showed lower resistance to environmental stressors, particularly in alkaline conditions over a pH of 9. In this application, specifying rPET over virgin PET would likely eliminate all of the presumed economic and environmental advantages of using a recycled material.
“Recycling is essential, but recycled content alone does not tell the full story. If a material fails too soon, the environmental benefits can disappear,” Athanasiou said.
For the researchers, the significance of the work extends beyond recycled plastics. The broader goal is to provide a fast, affordable, and realistic platform for evaluating the sustainability of any material choice. Because current testing protocols are costly, not widely available, and limited in the information they yield, engineers, manufacturers, and policymakers often have little choice but to continue to specify non-recycled materials because they will perform as expected. Having cheap and accurate data on recycled materials will help to accelerate their adoption because matching the engineering properties of recycled materials to their most appropriate applications will become more obvious.
The researchers also hope to expand the platform to simulate even more complex environments and apply it to a wider range of materials. Because the system generates large amounts of detailed data, it may enable opportunities to use computational modeling or artificial intelligence to digitally simulate mechanical testing, driving down costs and expanding availability even more.
The larger vision is a future in which sustainability is judged not by labels or assumptions, but by evidence for how a material performs, how long it lasts, how it fails, and what it costs society and the environment over its full lifetime.
Please visit the Daedalus Lab YouTube channel to see an explainer video about this new testing protocol: https://youtube.com/watch?v=zmRhiRIiAkQ
Read the paper here: https://www.science.org/doi/10.1126/sciadv.aeh0456
This research was supported by the National Science Foundation CAREER Award No. 2338508.
]]>This press release is shared jointly with the Savannah River National Laboratory (SRNL) newsroom. Georgia Tech faculty Martha Grover and Maggie Kosal also serve as SRNL Joint Appointees.
The Georgia Institute of Technology and the Savannah River National Laboratory announced the joint appointment of Facundo M. Fernández to collaborate in research around mass spectrometry, an analytical technique used to measure the mass-to-charge ratio of ions for research.
“Our partnership with Facundo will deepen SRNL’s innovative research in mass spectrometry and its groundbreaking applications,” said Tammy Taylor, SRNL’s deputy director of Science and Technology. “His expertise and collaboration will undoubtedly accelerate our lab’s drive for scientific excellence and impactful discoveries.”
Fernández is renowned internationally for his work in bioanalytical chemistry. His research focuses on developing tools to analyze small-volume samples, tissues and single cells, with applications in understanding diseases such as cancer, cystic fibrosis and inflammatory bowel disease. He has published 234 peer-reviewed papers, given over 230 invited lectures, and supervised 35 doctoral and master’s degree students.
He also directs the Systems Mass Spectrometry Core (SyMS-C) at Georgia Tech’s Parker H. Petit Institute for Bioengineering and Bioscience, managing more than 15 mass spectrometers.
“Being appointed as a joint faculty member with SRNL opens many new opportunities for collaborative research at the intersection of biology, chemistry and engineering,” said Fernández. “This type of collaborative research is what Georgia Tech is renowned for. We aim to address societal questions with global impact. I have been incredibly impressed with the quality of science at SRNL, and I look forward to many joint discoveries in the future.”
Fernández is a Regents’ Professor and the Vasser-Woolley Chair in Bioanalytical Chemistry at Georgia Tech’s School of Chemistry and Biochemistry. He earned his bachelor’s and master’s degrees (Licenciatura) in chemistry from the Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, in 1995, and his doctorate in analytical chemistry from the same university in 1999. From 2000 to 2001, he was a postdoctoral researcher at Stanford University’s Department of Chemistry. He served as a senior postdoctoral researcher and later as a research scientist between 2002 and 2003 with a research group at the University of Arizona.
“Professor Fernández is a renowned expert in the field of mass spectrometry, and it has been a privilege to already have him as a collaborator involved in our Laboratory Directed Research and Development program,” said SRNL’s Christopher Orton, division director for Nuclear Nonproliferation. “This joint appointment will strengthen the relationship between SRNL and Georgia Tech as we continue to work together to improve our understanding of the environmental fate of chemical contaminants in complex matrices.”
SRNL’s Joint Appointment Program provides university faculty opportunities to engage in research and development addressing the nation’s energy related challenges. SRNL staff and joint appointees help ensure America’s security and prosperity through transformative science and technology solutions, and joint appointees serve as a bridge between their university and SRNL researchers to deliver the future workforce for the Department of Energy.
Savannah River National Laboratory is a multi-program federally funded research and development center managed and operated by Battelle Savannah River Alliance for the U.S. Department of Energy’s Office of Environmental Management. EM transforms the nation’s environmental liabilities into opportunities for innovation, job creation, and economic growth, while ensuring safe, secure and prosperous communities across America. For more information, visit energy.gov/em.
The ACS is one of the world’s largest scientific societies, and its Fellows Program recognizes outstanding achievements in scientific research, education, leadership, and service to the chemical profession and honors a select group of members each year.
"Election as an ACS Fellow is a significant honor that recognizes not only scientific excellence but also leadership and service to the profession," said Julia Kubanek, Georgia Tech's vice president for Interdisciplinary Research. "Yuanzhi's pioneering research, her leadership within ACS and the Strategic Energy Institute, and her commitment to advancing interdisciplinary collaboration have strengthened Georgia Tech's impact in chemistry, energy, and environmental research. We are proud to celebrate this well-deserved recognition."
Tang was recognized for her contributions to environmental chemistry, biogeochemistry, and energy-related research, as well as for her leadership and service to the chemical sciences.
"Given her exceptionally energetic research program, which spans topics ranging from the basic understanding of chemical cycling on Earth to creative solutions to recover rare elements from wastes, this honor is richly deserved and completely unsurprising," said Jean Lynch-Stieglitz, chair of the School of Earth and Atmospheric Sciences. "We are lucky to have Yuanzhi as part of EAS."
As SEI executive director, Tang leads Institute-wide efforts to strengthen Georgia Tech's energy research enterprise by connecting expertise across disciplines and fostering partnerships with industry, government, and national laboratories. She also maintains an internationally recognized research program focused on understanding the chemical and biological processes that shape natural and engineered environments.
Established in 2008, the ACS Fellows Program honors a distinguished group of scientists who have made exceptional contributions to chemistry and related fields while also demonstrating dedicated service to the society. With this election, Tang joins 17 Georgia Tech ACS Fellows.
"I’m deeply honored," Tang said. "This recognition reflects the contributions of many outstanding students, postdoctoral researchers, colleagues, collaborators, and mentors throughout my career. I am grateful for the opportunity to work alongside such talented people to advance scientific discovery and build interdisciplinary partnerships that address critical energy and environmental challenges."
Founded in 1876, the American Chemical Society represents more than 170,000 members worldwide and is a leading source of scientific information through its journals, conferences, and educational programs.
]]>The ACS is one of the world’s largest scientific societies, and its Fellows Program recognizes outstanding achievements in scientific research, education, leadership, and service to the chemical profession and honors a select group of members each year.
"Election as an ACS Fellow is a significant honor that recognizes not only scientific excellence but also leadership and service to the profession," said Julia Kubanek, Georgia Tech's vice president for Interdisciplinary Research. "Yuanzhi's pioneering research, her leadership within ACS and the Strategic Energy Institute, and her commitment to advancing interdisciplinary collaboration have strengthened Georgia Tech's impact in chemistry, energy, and environmental research. We are proud to celebrate this well-deserved recognition."
]]>Researchers at Georgia Tech play a key role in the international collaboration. The Georgia Tech-LIGO research group includes School of Physics Professor Laura Cadonati, Assistant Professor Surabhi Sachdev, Research Scientist Margaret Millhouse, Postdoctoral Scholar Prathamesh Joshi, eight graduate students, and multiple undergraduates.
The LVK network detects gravitational waves when a massive cosmic event — like the collision of two black holes — creates invisible ripples in the fabric of space-time. Waves ripple out at the speed of light, and millions of years after the events that first created them, they reach the LVK detectors.
But detecting gravitational waves does not simply mean capturing a signal — clues first need to be untangled from background noise.
“Identifying gravitational-wave signals requires carefully separating real astrophysical events from random fluctuations in the data,” says School of Physics graduate student Urja Shah, whose work to quickly identify phenomena supports rapid follow-up by the broader astronomical community.
To support the identification of phenomena, School of Physics graduate student Megan Arogeti conducts consistency tests between waveforms, checking results to find unexpected or unusual features. “Tests like this give us confidence in our models as we continue to observe gravitational waves with increasing sensitivity,” she explains. “They support new observations and help identify exciting new physics.”
“These efforts help ensure that gravitational-wave signals are robustly identified and accurately characterized, turning each detection into a precise measurement,” adds Shah. “In turn, these measurements deepen our understanding of some of the most massive and dense objects in the universe and the fundamental laws governing the cosmos.”
When a sensor detects a gravitational wave, it produces a distinctive response, says School of Physics graduate student Shobhit Ranjan. “Those signals encode a wealth of information we can analyze to learn about their sources — their masses, spins, distance, and location.” But in order to detect these chirps, the detectors must be carefully calibrated, and if calibration is not optimal, the signals can be compromised.
Now, a new tool is helping the LVK collaboration recalibrate less optimal signals. The technique is already showing promise: In an article recently accepted in Physical Review Letters, LVK researchers successfully applied it to two interesting signals. The first signal served as a testing opportunity for the method. The team used astrocalibration to recover the data and check it against secondary independent calibration data that was available. They then put the technique to use, recovering information from a second event where no secondary calibration data were available.
“Like autotune in the music industry, the new research shows that theoretical models can be used as guides, similar to how sheet music can help a studio shift off-key music to its correct tone,” Ranjan explains. “These theoretical models suggest the shape of the signal, and together with data from other detectors, we can adjust the data and read it correctly.”
“The fact that these detectors can now not only sense cosmic events, but leverage them to improve the data being collected marks a new era in gravitational wave science,” he adds.
The LVK Collaboration also published their fifth catalog of gravitational wave events this spring. The findings include an updated estimate of how fast the universe is expanding, evidence for the existence of second-generation black holes, the most precise sky localization ever achieved for a gravitational wave source, and the first measurement of three vibrational modes of a black hole.
“Our group helped enable 140 detections out of the 161 reported in this catalog,” says Joshi, who contributed to one of the flagship searches and designed a specialized search focused on detecting especially heavy black hole mergers.
Joshi also worked on determining precise locations of where the gravitational waves originated from in the universe — research that he says will allow astronomers around the world to perform long-term follow-up observations of interesting events.
One record-setting detection showed two black holes that had violently collided more than 3 billion light-years from Earth. Researchers were able to pinpoint its location in the sky more precisely than any other gravitational wave event observed before.
Improvements in the LVK network’s ability to localize events along with the large number of detections allowed for a better estimate of the Hubble constant, which measures the rate at which the universe is expanding. The new measurement is over 25% more precise than previous estimates.
The new catalog also includes the “clearest” gravitational wave signal ever detected. The clarity of the signal led to the most accurate test of general relativity ever performed and confirmation of Stephen Hawking’s black hole area theorem.
“This catalog provides not just the largest number of black hole detections, it marks a new era of rapid progress,” Sachdev says. “This is just the beginning of what these observations will allow us to uncover.”
]]>As ISyE’s A. Russell Chandler III Professor, Huo’s theoretical research focuses on explaining why modern deep-learning methods preform so well. He also uses statistics, machine learning, and data science to better to better understand the reliability and fairness of learning systems.
Huo has authored more than 15 refereed journal articles since 2023 and currently has 10 papers under review. His career includes 71 journal articles, 41 conference papers, 10 book chapters, and an edited volume.
“What I find most rewarding is that rigorous theory and useful tools are not in tension – the mathematical questions that fascinate me most often turn out to be the ones that help others make sense of their data,” Huo said. “I’m deeply honored to receive this award and especially grateful to my students and collaborators, who have been at the heart of this work from the very beginning.”
Huo’s first algorithm for distance covariance remains a standard tool for testing statistical dependence and is reproduced in widely used statistical software. He co-directs the Georgia Clinical and Translational Science Alliance's Biostatistics, Epidemiology and Research Design program, which is supported by the National Institutes of Health. He also serves as a co-principal investigator on the $20 million NSF AI Institute for Agent-based Cyber Threat Intelligence and Operation.
Huo said he is proud of the researchers he has trained. In the most recent recruiting cycle, his doctoral graduates earned tenure-track faculty offers from Georgetown University and the University of Florida. Earlier advisees hold faculty positions at the City University of Hong Kong, Korea Advanced Institute of Science and Technology, and Seoul National University of Science and Technology, while other former students are researchers at companies that include Apple, Citadel, and JP Morgan.
His recently published work includes two 2024 papers in the Journal of Machine Learning Research (JMLR). He and his students established learning guarantees for deep neutral networks, including minimax-optimal convergence rates of neural-network classifiers was accepted in 2026 by IEEE Transactions on Information Theory, and his work on the universal consistency of wide and deep networks appeared at the International Conference on Machine Learning.
Huo’s work on the fairness of learning systems is reflected in a 2025 Journal of the American Statistical Association paper that characterizes the asymptotic behavior of the adversarial-training estimator, complementing his JMLR work on distributionally robust estimation. At the Conference on National Information Processing Systems (NeurIPS) 2025, Huo and collaborators introduced a kernel-based quantification of the accuracy fairness trade-off in representation learning, along with a new diffusion method for imbalanced text-to-image generation, while a 2026 International Conference on Learning Representations paper advanced policy optimization for large-language-model reasoning.
]]>Caused by the Vibrio coralliilyticus pathogen, the infection is one of the most notorious causes of tissue loss and death in stony corals. In the study, all untreated corals bleached within 48 hours. But corals exposed to the predatory bacteria fared much better: more than half showed no signs of bleaching beyond the infection site — and disease progression was effectively halted.
“Disease is a major driver of death for these corals, and with sea surface temperatures continuing to rise globally, we anticipate that rates of disease will only increase. It’s part of a deadly synergy profoundly threatening Caribbean coral reefs,” says lead author Lauren Speare, assistant professor in the School of Biological Sciences. “Predatory bacteria function like a living probiotic, fighting coral disease without harsh side effects. This could be a targeted way to protect and treat our most vulnerable coral reefs."
The study, “Halobacteriovorax Halts Disease Progression in Endangered Caribbean Corals,” was published in The ISME Journal. In addition to Speare, the research team included Georgia Tech master's student Chloe Manley and postdoctoral scholar Macey Coppinger; University of California, Santa Barbara graduate students Sunni Patton and Eddie Fuques, and Professor Rebecca Vega Thurber, director of the UCSB Marine Science Institute.
Speare became interested in the research while completing her postdoctoral training with Thurber. “Dr. Thurber discovered that predatory bacteria are present in many coral microbiomes,” Speare recalls. “We theorized that they might be contributing to what keeps the ecosystem healthy, balancing it through predation.”
At the time, the theory was hard to test. Marine predatory bacteria are difficult to preserve long-term, making experiments challenging. The bacteria are also extremely scarce, with populations increasing during a coral infection and rapidly declining after. Catching them while their populations are high is a matter of timing, Speare says.
"It's a bit like trying to catch a mountain lion in the act of hunting a deer. If we aren’t looking at the right time, we might miss it entirely,” Speare says. “I knew that if I wanted to study these bacteria in more detail, I would need to carefully design my experiments and timing.”
To test their theory, the team spent six weeks conducting experiments at the Mote’s Elizabeth Moore International Center for Coral Reef Research and Restoration (IC2R3) in Summerland Key, Florida, a facility that maintains lab-grown living corals in seawater aquariums.
“First, we had to make our corals sick,” Speare says. “But there wasn’t an established way to reliably create these infections in this species in a laboratory setting.”
After weeks of experimenting, Speare developed a “pathogen-sticker,” a small agar patch containing the disease-causing pathogens. When placed at the coral’s base, it mimics how infections spread in the wild.
Then, at the first sign of infection, the team treated the coral with the Halobacteriovorax predatory bacteria. “Surprisingly, the most effective method was to pour the bacteria directly into the sick coral’s tank,” Speare says. “The bacteria are tiny, so we were able to create a concentrated liquid of them by using a filter small enough that only they can pass through.”
Halobacteriovorax are among the fastest-known predatory bacteria, and quickly navigate to their food source – presumably the pathogen causing the infection.
Because of the straightforward delivery method, Speare believes the team’s methods could be readily adapted for coral restoration efforts, offering a simple way to deliver treatment on natural reefs.
“There are several approaches to treating corals and mitigating stress, but these techniques don’t work for all situations and all species,” she explains. “Corals are complex, and there is no single cure-all, so we need as many tools as possible to help corals survive.”
For Speare, the next step will be to move from lab-based work to reef environments. She’s particularly curious as to why the predatory bacteria aren’t already moderating illness on natural reefs. “If this is such an effective way to control pathogens, why isn’t this system preventing disease outbreaks on reefs already?" she says. "We need to understand what's limiting this natural defense system – and that’s what we’re digging into next."
Funding: Lauren Speare was supported as a Simons Foundation Awardee of the Life Sciences Research Foundation. The Vega Thurber Lab was funded by the National Science Foundation.
DOI: https://doi.org/10.1093/ismejo/wraf270
]]>As the brain develops, billions of neurons form precise networks that enable perception, movement, and cognition. Disruptions in this process can contribute to neurodevelopmental conditions such as autism and schizophrenia. To better understand how such disorders arise, Jain’s lab will use molecular and genetic tools to trace the pathway from gene expression to neural connectivity to behavior.
“I am honored and excited to receive support from the Whitehall Foundation,” Jain says. “It will help us pursue research questions at a stage when our findings can still shape our lab’s long-term direction.”
Jain joined Georgia Tech in 2024. He earned a Ph.D. in molecular and cellular biology from the University of Arizona and completed postdoctoral work at the University of California, Los Angeles.
]]>Their work, led by Sourabh Saha, associate professor and Woodruff Faculty Fellow, and Harnjoo Kim, who conducted the research during his doctoral studies and later as a postdoctoral fellow in Saha's lab, was recently published in the journal Nature Communications.
Nanoscale 3D printing allows researchers to create structures thousands of times smaller than the width of a human hair. These structures have potential applications in fields ranging from advanced computing and optics to biomedical devices and clean energy technologies. However, increasing printing speed often comes at the expense of quality.
Read the full story on the George W. Woodruff School of Mechanical Engineering website
]]>Their work, led by Sourabh Saha, associate professor and Woodruff Faculty Fellow, and Harnjoo Kim, who conducted the research during his doctoral studies and later as a postdoctoral fellow in Saha's lab, was recently published in the journal Nature Communications.
Nanoscale 3D printing allows researchers to create structures thousands of times smaller than the width of a human hair. These structures have potential applications in fields ranging from advanced computing and optics to biomedical devices and clean energy technologies. However, increasing printing speed often comes at the expense of quality.
]]>George W. Woodruff School of Mechanical Engineering
]]>Dunkin is an IISE Fellow, the highest classification of IISE membership that recognizes outstanding leaders of the profession who have made significant, nationally recognized contributions to industrial and systems engineering. She has served as chief information officer at the U.S. Department of Energy and the U.S. Environmental Protection Agency, as well as chief strategy and innovation officer at Dell Technologies. She has also held numerous leadership positions at Hewlett Packard, largely in the areas of manufacturing, research and development and IT. She currently serves as a distinguished external fellow with Georgia Tech’s Strategic Energy Institute.
Dunkin holds appointments as a distinguished professor of the practice in Georgia Tech’s School of Cybersecurity and Privacy and in the Jimmy and Rosalynn Carter School of Public Policy. She is also a distinguished external fellow at the Georgia Tech Research Institute (GTRI).
“The Emerging Technologies forum is a great opportunity for practicing ISEs to get exposure to a range of emerging technologies in a short period of time and identify those that they want to experiment with and implement in their organizations,” Dunkin said.
The Aug. 26 event, which will be held virtually from 1-5 p.m. EDT, will explore technologies shaping the future of industrial and systems engineering, including artificial intelligence, digital twins, and robotics and autonomy.
As event chair, Dunkin will be joined by experts from the healthcare, aerospace, logistics, manufacturing and technology industries, including representatives from Royal Caribbean, The Boeing Company, UPS and other organizations.
The complimentary event is open to engineers and improvement professionals of all backgrounds. Registration is available through the IISE Emerging Technologies Forum website.
Meghna Iyer (Biology 2026) came to Georgia Tech trying to understand her mother’s illness. What she discovered is changing how scientists connect three neurodegenerative diseases.
]]>When a bartender checks an ID, they quickly verify a customer’s date of birth and identity before serving them.
Companies that employ online age verification claim their products function the same way on the web. That bartender analogy has, in part, justified laws passed in twenty-five US states — comprising more than 40% of Americans — mandating the use of digital age verification to gate access across social media and adult content online. Further regulation, targeting social media sites, is currently in process in a number of states.
However, new research from Georgia Institute of Technology (Georgia Tech) and the University of California, Irvine (UC Irvine) reveals that the reality of online age verification is far from ideal.
The study found that the vast majority of sites covered by these laws do not appear to enforce age verification at all. When sites do comply, they often route users through third party age verification services.
The researchers found that one such third party, Yoti, a London-based company used by Meta, OnlyFans, Sony PlayStation, and TikTok, provides services for an estimated 60% of websites deploying age verification services.
Depending on the verification method, a verification attempt via Yoti may transmit a user’s IP address and/or OS and browser metadata sufficient to uniquely identify and track devices. Some of the IP, OS, and browser metadata may be sent to credit card companies and IP geolocation services, while ID information may be sent to a known data broker, or another verification service.
“There have been laws passed and court cases settled on the promise that these companies are incentivized to keep users’ data private,” said Assistant Professor Michael A. Specter at Georgia Tech’s School of Cybersecurity and Privacy. “We found that reality is starkly different.”
Aside from privacy concerns, researchers note that differing state policies could lead to what they call the “Balkanization of the U.S. web.” In other words, users may have access to different parts of the internet depending on the state they are in—potentially limiting the free exchange of ideas and information.
According to Assistant Professor Harry Oppenheimer of the Jimmy and Rosalynn Carter School of Public Policy, users are already accustomed to experiencing the internet differently across countries. However, this may signal the beginning of similar fragmentation within the United States.
“We are going to start seeing comparable differences between U.S. states,” said Oppenheimer. “Users in some states will now have to go through additional steps to access information. Close your laptop in New York before a flight to Dallas and try to load the same web page—now you see two different results.”
“We also observed age verification deployed on websites accessed from New York, which has no law requiring verification,” said Associate Professor Paul Pearce of UC Irvine’s Department of Computer Science. “We don’t know why these sites are deploying such verification—it could be a move to limit liability or simplify operations. Regardless, it points to an emerging threat for the open Internet where restrictive laws from some states could impact the entire country and beyond.”
The study, Papers Please: A First Look at Age Verification on the Web, was led by Georgia Tech Ph.D. student Shreyas Minocha, undergraduate Isaac Sheridan, and professors Oppenheimer, Pearce, and Specter. It is part of the proceedings of the 47th IEEE Symposium on Security and Privacy and was presented in San Francisco on May 20th, and featured in Ars Technica.
CORRECTION: A previous version of this article, posted in error, included statements that were not part of the researchers’ findings or intent. This version has been updated for clarity, and to reflect the research as published in IEEE S&P.
The research also reveals that most websites that require age verification don’t enforce the policy.
]]>Researchers at Georgia Tech say they have developed a system to help answer that question.
Known as FIRA, the tool analyzes drone crashes to determine whether they were caused by tampered machine-learning (ML) models. The team will present its findings at the 35th USENIX Security Symposium in August.
The research addresses a growing safety challenge as drones are increasingly used for deliveries, infrastructure inspections, and agriculture.
As drones rely more on machine learning to navigate and make decisions, they also become vulnerable to model poisoning attacks. In these attacks, adversaries manipulate an AI system during its learning phase, embedding hidden triggers that can cause failures under specific conditions.
“Machine learning drones are making more decisions in flight, which makes ML a safety-critical component of these systems,” said Yizhi Huang, Ph.D. student and lead researcher on the project.
“When something goes wrong, investigators need a way to ask whether the model was responsible, but the model is the part of the system that no one can examine after a crash. FIRA gives investigators a way to investigate these cases by reconstructing what the model was doing during the crash. As more drones run with ML, this kind of forensic capability can help drones be used more effectively and safely.”
When a drone crashes, investigators must determine whether the cause was malicious interference, weather, or mechanical failure. Without reliable forensic tools, accountability is difficult to establish, and safety standards are harder to enforce.
FIRA identifies how drone components interact with machine learning models and monitors those interactions in real time, even with limited bandwidth.
The system functions like a flight recorder, capturing key system activity and reconstructing a timeline after a crash. It then analyzes the model’s behavior to determine whether a malicious trigger was introduced via poisoned ML training data.
In tests across multiple drone platforms and crash scenarios, FIRA identified failure causes and distinguished cyberattacks from environmental or mechanical issues.
The system does not require access to a drone’s source code, making it practical for real-world investigations.
“As commercial drone use expands, tools like FIRA could help improve accountability and trust in AI-powered systems operating in public airspace,” said Huang.
FIRA: Enabling Automatic Forensic Investigation of Unmanned Aerial Vehicles was led by Georgia Tech’s Cyber Forensics Innovation Lab in cooperation with the Cyber-Physical Security Lab. These labs reside in the School of Cybersecurity and Privacy and the School of Electrical and Computing Engineering.
]]>Researchers at Georgia Tech say they have developed a system to help answer that question.
]]>Presented annually, the ISCA Influential Paper Award recognizes a standout paper from the ISCA Conference 18-22 years prior. Winning papers are those which have demonstrated “the most impact on the field (in terms of research, development, products or ideas) during the intervening years.”
The awarded paper, Adaptive Insertion Policies for High-Performance Caching, has been highly influential in cache replacement research. As a Ph.D. student at the University of Texas at Austin, Qureshi co-authored the paper with his advisor Yale Patt and collaborators from Intel, including Aamer Jaleel, Simon Steely, and Joel Emer.
“I’ve been working on memory systems for 20 years and if I had to pick one favorite paper, it would be this one,” Qureshi said. “Both because of the simplicity of the solution and for the impact it had.”
When the paper was published at ISCA 2007, on-chip cache sizes were growing but still managed almost exclusively by the Least Recently Used (LRU) replacement policy.
The paper showed that more than half of the lines in cache were discarded before they could be used under LRU policy and that this happened because the workloads being run were larger than the cache size. The team came up with a simple solution of modifying the “Insertion Policy”, such that the incoming lines were inserted at the LRU position instead of the MRU position, thus protecting the cache from thrashing patterns. The problem was that some workloads benefited from this policy while others were hurt by it.
Instead of applying one policy across the whole cache, their solution dynamically tested two small segments against each other, each running a different policy. Whichever policy had fewer cache misses was applied to the entire cache. They named this technique Set Dueling.
Qureshi clearly remembers the moment he knew this paper would be important. He was up late working on the project when he ran the final simulation with the solution.
“I was so excited that I just didn’t sleep that night. I knew that the solution would get incorporated and it would change how people think about caching. I could not wait to share the results with my collaborators” he said.
Set Dueling has since become a common technique for choosing between two competing policies when neither wins on all workloads. With close to 1,000 citations, the paper has greatly influenced research on cache optimization.
This recognition is Qureshi’s third test-of-time honor. In 2024, he received one at the IEEE/ACM International Symposium on Microarchitecture, for his work on Multi-core Cache Partitioning and in 2025, at the IEEE/IFIP International Conference on Dependable Systems and Networks, for his work on DRAM Reliability.
Qureshi said that his goal in working in computer architecture is to have an industry impact.
“It’s very gratifying to see that the ideas that we developed a decade or two decades ago are having an impact and being incorporated,” Qureshi said. “As a researcher, these are the best awards you can have because it serves as a validation that the work you’ve done is valuable to both industry and follow-up research.”
]]>When Robbie van Zyl first started working with drones, it was not for defense. It started with curiosity.
As a high school student, van Zyl spent summers in a Georgia Tech aerospace lab, where he was introduced to rotorcraft and autonomous systems. By the time he enrolled at Georgia Tech, that early exposure had grown into a deeper interest. He became a competitive drone racer, gaining hands-on experience with the technology.
But even then, he recognized a growing risk.
“I was using this technology to have fun,” said van Zyl, founder and CEO of Askari. “But I also recognized it could equally be used to do very malicious things.”
That realization became the foundation for Askari, a counter-drone defense company developing systems designed to detect, track, and stop hostile drones.
Van Zyl first pitched the idea for Askari as a first-year student through Georgia Tech’s CREATE-X Startup Launch, an accelerator that empowers students to launch successful startups. At the time, the concept of counter-drone defense was not widely seen as urgent. However, that perspective shifted as global conflicts began to demonstrate the impact of low-cost, unmanned systems.
The widespread use of drones in Ukraine revealed how inexpensive and accessible technologies could reshape modern warfare. Unmanned systems now account for a significant share of battlefield activity, exposing new vulnerabilities across defense and infrastructure.
“That was the first moment I could point to and say this is real,” van Zyl said. “This is not theoretical anymore.”
Askari is building autonomous systems that can identify and neutralize drone threats in real time. The company’s technology is designed to distinguish among objects such as drones, people, and the surrounding environment, allowing it to respond with precision.
“We are building systems that can understand what they are looking at,” van Zyl said. “They can tell the difference between a drone, a person, or a tree, and act accordingly.”
Unlike traditional defense systems that rely on expensive infrastructure, Askari is focused on developing solutions that are scalable and accessible to a wider range of users, including frontline operators and security teams. The goal is to provide a faster, more adaptable approach to this challenge.
The company has raised approximately $1.7 million in early funding and is already working with U.S. Department of Defense customers, with growing demand for counter-drone solutions. The team has expanded to 10 people and is scaling to meet that demand.
Georgia Tech’s commercialization ecosystem played a critical role in Askari’s development.
Through CREATE-X, van Zyl was able to test and refine his idea while gaining exposure to the fundamentals of building a company. He also gained access to a community of founders, mentors, defense leaders, and builders who helped him navigate early-stage challenges. The experience provided an environment to pressure-test the concept and receive feedback, helping him better understand how it could function in real-world scenarios. At the time, the idea was still taking shape, but it helped clarify how it could evolve into a viable solution.
After gaining experience in the robotics and defense sectors, van Zyl reengaged with Georgia Tech, where the Institute’s network of mentors, resources, and programs helped accelerate the company’s growth.
“Georgia Tech has been instrumental,” van Zyl said. “We would not be where we are today without it.”
Today, Askari operates out of The Biltmore, home to CREATE-X and part of Georgia Tech’s innovation ecosystem in Tech Square, placing the company back within the same environment where the idea first began.
“Askari is a strong example of what we aim to do,” said Rahul Saxena, CREATE-X director. “Students building companies that address real, emerging challenges. It reflects the kind of thinking we want to encourage early on, paired with the ability to continue developing an idea as the need becomes clearer. That progression is a critical part of how students move from concept to company.”
After graduating, van Zyl gained experience working in robotics and autonomous systems, including in Silicon Valley. He also spent time building the company outside of Atlanta before ultimately returning.
The decision to come back was both strategic and mission-driven.
Many of Askari’s customers, including Department of Defense organizations, are based in the Southeast. Being in Atlanta allows the company to remain close to those partners while continuing to build within Georgia Tech’s ecosystem. The company’s return also reflects its deep ties to Georgia Tech’s talent pipeline. van Zyl’s co-founders include his younger brother, Marc van Zyl, a Georgia Tech computer science student, and Benjamin Airdo, a close friend and mechanical engineering graduate. Eight of the company’s 10 team members are connected to the Institute as current students, graduates, or researchers.
While Askari’s current focus is counter-drone technology, van Zyl sees the startup’s mission as part of a larger shift in how modern warfare is evolving.
For the first time, autonomous systems powered by artificial intelligence are moving beyond the digital world into physical environments. That transition introduces new risks that extend beyond traditional defense scenarios.
“This is not just a drone problem,” van Zyl said. “It is the broader proliferation of robotics in real-world environments.”
Askari’s trajectory reflects how Georgia Tech’s commercialization ecosystem supports founders as they move from early ideas to companies.
From its start in CREATE-X to its return to The Biltmore, the company remains closely tied to the Institute while building technology focused on real-world deployment and impact.
“We want to build systems that help protect people,” van Zyl said. As Askari continues to grow, that focus remains central to its mission.
For communities across the country, this growth hits close to home, and not without controversy. What do data centers actually deliver for the local economies that host them?
New research from Daniel Yue, assistant professor of Information Technology Management at Georgia Tech’s Scheller College of Business, and his co-author, Yiyang Zeng, examines how data center openings affect local jobs, wages, business activity, and electricity prices. Their findings suggest that geography plays a decisive role in whether communities see meaningful economic gains.
“Enormous amounts of capital are flowing into specific communities, much of it tied to new construction, while rigorous evidence on the local benefits of these facilities has been thin,” said Yue. “Community pushback has organized rapidly across the country. Our paper begins to fill that gap by providing new evidence using detailed, facility-level data paired with county-level economic indicators.”
A Historic Investment Wave
There are more than 2,500 data centers, either active or under construction, across the United States. Individual hyperscale facilities often cost more than $1 billion to construct and can consume as much electricity as a small city. Is it all worth it?
On average, Yue and Zeng found that when a data center opens, the host county sees a measurable lift: Employment rises by about 3.5%, wages by 5%, business establishments by nearly 5%, and household income by about 2%. Building permits also increase sharply, reflecting construction activity tied to new facilities.
These are real, economically meaningful gains. But Yue and Zeng discovered that these gains are much smaller than what might be expected from a large investment. And they’re not evenly distributed.
Why Metro Areas Benefit More
The researchers’ clearest finding is that metropolitan areas capture most of the economic benefits from data centers, while rural areas see far fewer spillover effects. While metro counties saw increases in employment and new business growth, non-metro counties saw no measurable gains.
The reason comes down to what economists call “agglomeration,” or economic density.
Data centers don’t operate in isolation. They rely on construction contractors, engineers, equipment suppliers, professional services, and a skilled workforce. Those connections are far easier to build in places that already have deep labor markets and established business networks.
Metropolitan areas are well-positioned to absorb the indirect spending that data centers generate. High-wage technical employees support restaurants, retail, and local services. Suppliers and contractors can scale up quickly. These spillover effects amplify the impact of the initial investment.
In rural areas, that amplification is much harder to achieve. Facilities tend to employ relatively few permanent workers — often fewer than 100 — and many specialized services are imported from outside the county. As a result, the broader economic ripple never materializes.
That doesn’t mean rural communities see no benefit at all. The research finds a small but real drop in unemployment rates in non-metro counties, and local governments may still gain tax revenue or infrastructure investments. But the sweeping job and wage growth often promised during local recruitment efforts will not likely arrive on its own.
“Location, not facility size, determines whether the local benefits show up,” Yue said.
The Hidden Cost: Electricity Prices
Yue and Zeng’s research also uncovers an important trade-off. Data centers use a lot of electricity. A single large facility can use as much power as roughly 80,000 homes. In areas where the researchers can cleanly measure price effects, electricity prices rise by about 5% after a data center enters.
“When the benefits to communities are small, even downsides like higher electricity prices that strain infrastructure will be felt by locals,” Yue shared.
Who pays for the increased cost of electricity isn’t straightforward. Yue and Zeng’s research suggests communities should ask specific questions about who pays for new infrastructure and how those costs will be distributed. Local utility companies divide costs differently among homeowners, businesses, and large industrial users, including data centers. Because cost-sharing systems vary by state, each data center development is unique.
What Communities Should Consider
As states and cities work to attract or push back against data center construction, Yue and Zeng hope their research will encourage more evidence-based decision-making.
For metro areas with strong labor markets and dense business ecosystems, data centers can deliver meaningful, though not transformative, economic gains. For rural communities, the positive impact is more complicated.
“In 10 years, communities will likely wish they had pressed harder on the quality of the decision itself, including whether the debate was evidence-based, whether their local economy was equipped to capture the gains, and whether the fine print aligned with residents' long-term interests,” Yue said. “It’s vital that communities look past flashy, headline incentive packages and focus on the details: tax abatement structures, electricity tariff arrangements, and who ultimately pays for infrastructure upgrades.”
As data centers continue to dot the American landscape, understanding where they create shared value — and where they don’t — will be critical for community leaders and policymakers alike.
Read More: The Local Economic Effects of Data Center Entry
“I am very honored and excited to receive the NSF CAREER Award,” says Zhu. “This award will support research by my fantastic team of students and post-doctoral researchers and give me the opportunity to carry out education and outreach programs that expand our impact.”
Since joining Georgia Tech in 2024, Zhu’s research has focused on the mathematical foundations of machine learning and their applications in science and engineering.
With support from the CAREER Award, Zhu and his team will explore the two-way relationship between data and structure in machine learning. They aim to understand how known structures in scientific and engineering problems (e.g., symmetries or physical constraints) can help machine learning models learn more accurately and efficiently from limited data. They will also study how machine learning can uncover hidden structures directly from data, revealing patterns or principles that may not be known in advance.
The project focuses on settings where large amounts of high-quality data are difficult or expensive to obtain, as is often the case in science and engineering. Using mathematical analysis, Zhu and his team will examine how much data is required to accurately learn a model, how structural information can reduce this data requirement, and how much data is needed to reliably identify a model’s underlying structure.
According to Zhu, this approach could reduce the amount of data and time needed to build and test accurate models, leading to more reliable, interpretable, and efficient AI for scientific discovery.
“Such advances align with national AI priorities and help strengthen the mathematical foundations needed for future scientific and engineering applications of AI,” he says.
Zhu believes it is important to help students understand AI, noting that they must learn how to interpret and evaluate its outputs rather than accept them uncritically.
“AI has increasingly become incorporated into many fields of study,” he says. “Institutions must determine how to best integrate it into education while also teaching students how it works. The AI education and outreach components of my project aim to help prepare students for careers at the intersection of mathematics, computing, and science.”
Zhu’s CAREER Award will support educational initiatives at multiple levels, including new graduate and undergraduate courses on machine learning. It will also support a machine learning boot camp for high school students, organized by the School of Mathematics in collaboration with Emory University’s Department of Mathematics. The boot camp seeks to introduce students to foundational ideas in AI and machine learning, with an emphasis on the mathematical principles needed to understand and responsibly use these tools.
]]>Housing and transportation are top priorities for many city mayors, policymakers and public policy researchers—including Brian An, an assistant professor at Georgia Tech’s Jimmy and Rosalynn Carter School of Public Policy. But in February 2021, soon after Winter Storm Uri wreaked havoc in Texas, an eight-hour power outage at his Atlanta home became an epiphany.
“While housing stability had long been on my mind, losing power drove home the importance of another piece of urban infrastructure: reliable access to electricity,” says An, an EPIcenter faculty affiliate and co-director of the Center for Urban Research. “It sparked my interest in studying the intersection of energy and urban policy to help make cities and communities not only socially equitable but also resilient to extreme weather.”
Read Full Story on the EPIcenter News Page
]]>Housing and transportation are top priorities for many city mayors, policymakers and public policy researchers—including Brian An, an assistant professor at Georgia Tech’s Jimmy and Rosalynn Carter School of Public Policy. But in February 2021, soon after Winter Storm Uri wreaked havoc in Texas, an eight-hour power outage at his Atlanta home became an epiphany.
“While housing stability had long been on my mind, losing power drove home the importance of another piece of urban infrastructure: reliable access to electricity,” says An, an EPIcenter faculty affiliate and co-director of the Center for Urban Research. “It sparked my interest in studying the intersection of energy and urban policy to help make cities and communities not only socially equitable but also resilient to extreme weather.”
]]>News Contact: Priya Devarajan, Research Communications Program Manager
]]>Communities across Georgia and the nation are navigating a range of economic and energy-related pressures. Gas prices, inflation, and the rapid growth of data centers are shaping the cost of goods and services, influencing everyday household financial decisions.
At the same time, ongoing geopolitical tensions are driving fluctuations in global oil markets and fuel prices. The expansion of AI data centers is also increasing demand for land, power, and water resources. And conflicts involving energy infrastructure in parts of the Middle East and Europe have affected supply stability.
Responding to these challenges requires careful analysis of emerging trends, supported by strong research in policy and economics. Faculty Affiliates of Georgia Tech’s Energy Policy and Innovation Center study these complex, interconnected issues affecting energy systems, costs, and access. They analyze emerging trends, evaluate policy options, and identify practical pathways forward.
Read Full Story on the EPIcenter News Page
]]>Communities across Georgia and the nation are navigating a range of economic and energy-related pressures. Gas prices, inflation, and the rapid growth of data centers are shaping the cost of goods and services, influencing everyday household financial decisions.
]]>This battle of the brains has also been playing out over the course of evolution, but not as a simple clash between old and new.
“There was a theory proposed in the ‘50s that the brain evolved in layers starting with basic bodily functions, to emotions in the reptilian brain, leading up to sophisticated reasoning in humans,” explains Nabil Imam, an assistant professor in the School of Computational Science and Engineering and a faculty member with Georgia Tech’s Institute for Neuroscience, Neurotechnology, and Society (INNS). “This is not how an evolutionary biologist would think about the problem.”
Instead of a “new” brain layered over an “ancient” one — or even a logical brain versus an emotional one — research published in Science Advances reveals that brain evolution may come down to wiring.
By studying the architecture of both biological and artificial brains, Imam’s team found that brain evolution is a strategic allocation of limited real estate. They propose a computational tug-of-war between two fundamentally different types of internal wiring — ones established even before birth.
This new understanding not only helps resolve a longstanding mystery in brain evolution but could also help us design more efficient AI systems.
When we refer to our “logical” or “lizard” brains, we’re really talking about different groups of brain regions. The logical brain is known as the neocortex, the brain’s outer layer responsible for vision, perception, reasoning, and other higher-level functions. For the lizard brain, the story gets a bit complicated.
“The limbic system, sometimes called the ‘reptilian brain,’ controls emotion broadly speaking — but it also has other components with distinct functions,” explains Imam. The system has separate regions for memory, smell, and navigation in addition to emotional regulation. “Why do people group all these different regions into one big system? There hasn’t been a good theory for what is common between these different circuits.”
To investigate, Imam’s team looked beyond individual regions to examine how these systems scale across species. Instead of comparing single areas based on function, the team analyzed how the limbic system and the neocortex change together across evolutionary history.
The result was remarkably consistent. When one component of the limbic system was larger, the others were also larger, while the neocortex was consistently smaller. These regions don’t vary independently. “Rather,” says Imam, “it’s a coordinated expansion of these regions across species.”
This reveals something new: The limbic system behaves not as a loose collection of functions, but as a unified network that expands and contracts as a group across evolution.
But what is driving this coordinated push and pull?
Imam argues that it comes down to how these different parts of the brain are wired before birth.
In the neocortex, neural circuits are organized as spatial maps. Areas that process touch in nearby parts of your body, like your index finger and thumb, are physically close to each other in the brain. The same is true for sight and sound.
Wires in the limbic system, however, are not spatially organized. They function more like a bar code, firing in unique, distributed patterns to represent specific scents or complex memories.
To test whether this was an innate trait or acquired through experience, the team developed AI models for different senses. They found that when they pre-wired an AI with localized, spatial connectivity, the network was naturally very good at processing vision, sound, and touch information. Conversely, distributed, “barcode-style” networks were essential for the AI to excel at scent recognition and memory.
The final piece of the puzzle explains how the size of brain components changes predictably across species. Because resources like space and energy are limited, natural selection chooses which system to prioritize.
The team simulated evolution by creating a multimodal network where the spatial and distributed domains competed for “real estate.” When the environment rewarded smell, all areas of the distributed system expanded and the neocortex shrank. When vision was rewarded, the opposite occurred.
This explains why the nine-banded armadillo, which relies on scent, has a massive limbic system, while the highly visual squirrel monkey is dominated by its neocortex. Across the 182 species studied, the research shows that brain evolution is not about adding new layers of "logic," but about strategically reallocating space between different wiring systems to support survival.
By translating this biological architecture to AI systems, engineers could create machines that learn as efficiently as the human brain, requiring far less data and energy.
“Today's artificial neural networks are trained by vast amounts data — it’s about nurture,” says Imam. “But the brain is not a blank slate that gets trained by experience. It is a mix of nature and nurture, and the nature is that pre-wired architecture.”
“We could translate that architecture to AI systems to make it more brain-like, or make it learn or function as efficiently as the brain.”
This work was a collaboration with Cornell University and was supported by the National Science Foundation.
DOI: doi.org/10.1126/sciadv.aec6112
]]>Media Contact
Bryant Wine
College of Computing
The latest rankings build on a record year for Georgia Tech commercialization. In 2025, the Institute reported advancing hundreds of technologies toward the marketplace, while achieving record levels of invention disclosures, issued patents, and licensed technologies. Those milestones underscore Georgia Tech’s expanding role in transforming research discoveries into products, companies, and partnerships that create economic and societal value.
“The strong performance reflects a commercialization strategy focused not only on protecting IP, but also on helping researchers translate discoveries into practical applications,” said Raghupathy “Siva” Sivakumar, chief commercialization officer at Georgia Tech. “Whether through licensing technologies, launching startups, or partnering with industry, we are building pathways that help researchers transform discoveries into real-world solutions.”
From advanced health technologies to environmental monitoring tools and next-generation aerospace ventures, Georgia Tech innovations are reaching users and markets in increasingly diverse ways. One example is Kinemo, a startup developed through Georgia Tech research that is helping people with limited mobility regain independence through wearable assistive technology. Founded by researchers from the College of Engineering, Kinemo uses physiological sensing and small intentional movements to enable users to control digital devices. The company works closely with clinicians and patients at Shepherd Center to refine the technology and expand accessibility for individuals living with spinal cord injuries and mobility limitations.
Another example is Skopii, a startup launched from research in the lab of environmental engineering professor Ameet Pinto. The company is commercializing portable imaging and artificial intelligence technology that enables users to rapidly analyze microorganisms in water and environmental systems, eliminating the need for lengthy laboratory testing. The technology has the potential to improve decision-making for water utilities, food production systems, and environmental monitoring efforts.
As research institutions face increasing pressure to demonstrate impact beyond publications and laboratory discoveries, Georgia Tech continues to show how world-class research can translate into technologies, startups, jobs, and solutions that improve lives. The latest AUTM rankings provide another measure of that success, highlighting an innovation ecosystem that consistently moves ideas from the lab to the marketplace.
Startups such as Kinemo and Skopii illustrate the broader commercialization approach reflected in Georgia Tech's AUTM rankings.
]]>T1D is caused by the autoimmune destruction of insulin-producing pancreatic beta cells, requiring individuals to manage their blood glucose levels through lifelong insulin therapy. Transplanting pancreatic islets has long been investigated as a potential curative treatment, but long-lasting success in extrahepatic sites has been limited—particularly when islets are transplanted beneath the skin—due to poor blood vessel formation, immune rejection, and cellular stress following transplantation.
Vlahos’ research addresses these limitations by combining synthetic biology and tissue engineering in a new way: engineering cells to actively reshape their local environment after transplantation to make it more hospitable for the graft. Rather than relying solely on biomaterials or porous structures to support transplanted cells, the project focuses on programming the cells themselves to sense stress and respond dynamically.
]]>Wallace H. Coulter Department of Biomedical Engineering
]]>Gong Chen, assistant professor in the School of Mathematics, has received a $450,000 National Science Foundation Faculty Early Career Development (CAREER) Award to study the long-term behavior of solitons — coherent, particle-like waves observed across physics and mathematics.
While most waves spread out as they disperse (for example, ripples on water), a soliton is different: it can keep a coherent shape while moving, and in some cases, it can interact with other waves and still emerge recognizable afterward.
“Solitons are important because they appear across many areas of science, including fluid dynamics, optics, plasma physics, field theory, and models from mathematical physics,” says Chen. “From a mathematical point of view, they are a beautiful testing ground for understanding nonlinear behavior.”
According to Chen, a guiding idea in the field is that complex nonlinear waves may eventually resolve into a collection of stable solitons alongside dispersive radiation — the more diffuse portion of the wave that spreads out and weakens. Chen’s research focuses on how these waves behave over long periods of time, especially when multiple solitons interact.
“If we start with a complicated nonlinear wave, can we predict what it will look like far in the future?” asks Chen. “I want to understand not just whether a wave is stable, but how it evolves: how stability can fail, how energy is exchanged, and how complicated wave motion eventually organizes itself.”
His work examines multi-soliton systems and more complex wave structures, including topological solitons, where long-range interactions and internal fluctuations make the mathematics more challenging.
Chen is developing new mathematical frameworks tailored to these moving and interacting waves, including tools from spectral theory and nonlinear scattering. These approaches allow researchers to analyze wave behavior with new precision in settings where existing methods are limited.
A key part of this work involves nonlinear dispersive equations, which capture the competing effects that shape wave systems.
“A complicated wave may contain several solitons, some radiation that spreads away, and small oscillations trapped near the solitons,” explains Chen. “Nonlinear dispersive equations allow us to ask precise questions: Which part of the wave persists? Which part disperses? How much energy is released during a collision? Does the system eventually simplify into solitons plus radiation?”
Although the work is theoretical, it strengthens the foundation for models used widely in science and engineering.
“A better theoretical understanding of solitons and dispersive waves improves the reliability of these models,” Chen says. “It helps us know when coherent structures should persist, when they should radiate energy, and when instability or collision effects may change the outcome.”
Chen plans to use the CAREER Award to integrate research and education. He is organizing a summer school focused on dispersive waves and developing new courses, including a second-level course in partial differential equations that emphasizes connections to physical phenomena.
“The CAREER Award provides the stability and long-term support needed to pursue a coherent research program rather than isolated projects,” says Chen. “For me, the award is especially meaningful because the research and education components are closely connected.”
Chen aims to help students connect mathematical theory with real-world phenomena.
For Chen, that connection is what makes the field compelling.
“One point I would emphasize is that soliton dynamics is a place where abstract mathematics meets very intuitive physical pictures,” says Chen. “Understanding when that particle-like behavior persists, when it breaks down, and what remains afterward is both mathematically deep and scientifically natural.”
The NSF Faculty Early Career Development Program is a five-year grant designed to help promising researchers establish a foundation for a lifetime of leadership in their field. Known as CAREER awards, the grants are NSF’s most prestigious funding for early-career faculty.
]]>
The grant will support building a robotics and AI ecosystem for dexterous and mobile manipulation, enabling robots to move through environments, interact with objects, and adapt to changing conditions.
Ye Zhao, LIDAR director and associate professor in the George W. Woodruff School of Mechanical Engineering, leads the project, with Anqi Wu, assistant professor in the School of Computational Science and Engineering, serving as co-principal investigator.
Read the full story on the George W. Woodruff School of Mechanical Engineering website.
]]>The grant will support building a robotics and AI ecosystem for dexterous and mobile manipulation, enabling robots to move through environments, interact with objects, and adapt to changing conditions.
Ye Zhao, LIDAR director and associate professor in the George W. Woodruff School of Mechanical Engineering, leads the project, with Anqi Wu, assistant professor in the School of Computational Science and Engineering, serving as co-principal investigator.
]]>FIFA President Gianni Infantino likened the scale of each game to that of a Super Bowl. The success of a tournament that large will rely heavily on technology, affecting everything from the players on the pitch, all the way to viewers at home.
On top of the state-of-the-art technology used at many large events, this World Cup will also see the debut of new technology. At the center of much of it will be electrical and computer engineering.
Experts from the Georgia Tech School of Electrical and Computer Engineering (ECE) weigh in on how the field is enabling the technology behind the world’s largest sporting event.
Read Full Story on the ECE News Page
]]>Researchers at Georgia Tech say they have developed a system to help answer that question.
Known as FIRA, the tool analyzes drone crashes to determine whether they were caused by poisoned machine-learning (ML) models. The team will present its findings at the 35th USENIX Security Symposium in August.
The research addresses a growing safety challenge as drones are increasingly used for deliveries, infrastructure inspections, and agriculture.
As drones rely more on machine learning to navigate and make decisions, they also become vulnerable to model poisoning attacks. In these attacks, adversaries manipulate an AI system during its learning phase, embedding hidden triggers that can cause failures under specific conditions.
“Machine learning drones are making more decisions in flight, which makes ML a safety-critical component of these systems,” said Yizhi Huang, Ph.D. student and lead researcher on the project.
“When something goes wrong, investigators need a way to ask whether the model was responsible, but the model is the part of the system that no one can examine after a crash. FIRA gives investigators a way to investigate these cases by reconstructing what the model was doing during the crash. As more drones run with ML, this kind of forensic capability can help drones be used more effectively and safely.”
When a drone crashes, investigators must determine whether the cause was malicious interference, weather, or mechanical failure. Without reliable forensic tools, accountability is difficult to establish, and safety standards are harder to enforce.
FIRA identifies how drone components interact with machine learning models and monitors those interactions in real time, even with limited bandwidth.
The system functions like a flight recorder, capturing key system activity and reconstructing a timeline after a crash. It then analyzes the model’s behavior to determine whether a malicious trigger was introduced via poisoned ML training data.
In tests across multiple drone platforms and crash scenarios, FIRA identified failure causes and distinguished cyberattacks from environmental or mechanical issues.
The system does not require access to a drone’s source code, making it practical for real-world investigations.
“As commercial drone use expands, tools like FIRA could help improve accountability and trust in AI-powered systems operating in public airspace,” said Huang.
FIRA: Enabling Automatic Forensic Investigation of Unmanned Aerial Vehicles was led by Georgia Tech’s Cyber Forensics Innovation Lab in cooperation with the Cyber-Physical Security Lab. These labs reside in the School of Cybersecurity and Privacy and the School of Electrical and Computing Engineering.
]]>Researchers at Georgia Tech say they have developed a system to help answer that question.
]]>Communications Officer II at the School of Cybersecurity and Privacy
]]>Logically this makes sense and has been backed up by past security research. However, researchers at Georgia Tech have found hidden paths in cyber-physical systems that attackers can use to disrupt or even destroy them.
To find these hidden paths before an attacker does, the researchers built a testing tool called ICSFlux. This new tool leans on the physics used by the industrial process and maps out the system to find new threats that were once thought impossible.
ICSFlux was deployed across 11 different programmable logic controllers in six industrial sectors, including chemical manufacturing, water treatment, power grids, aircraft, desalination, and waste processing. The process uncovered twenty genuine safety violations.
In one case drawn from a chemical-plant simulation, an attack path uncovered by the tool drove a reactor past its safe pressure limit and into a simulated explosion. By using nothing but valid operator commands, the team took the reactor from a completely normal and stable state to critical territory.
Because the method relies only on the physics of a process and not on the details of any one controller, the same tool worked across all six sectors without being rebuilt, and it reduced the search space by roughly 50%.
Burak Sahin, a Ph.D. student at Georgia Tech and the study's lead author, found that by sending a series of perfectly normal, fully authorized commands, intruders can slowly nudge a physical process toward a dangerous state.
“These systems are usually judged safe as long as nobody hacks into them,'' Sahin said. “What we found is that an attacker who can send everyday commands, the same ones a normal operator sends, can patiently steer the process toward a failure. No single command looks wrong, which is exactly why the usual defenses miss it.''
Most existing tools assume an attacker can rewire the controller or change the software inside it. In the real world, those controllers are locked down and cannot be touched. ICSFlux takes the opposite and more realistic view. It treats the controller as a sealed box that cannot be opened and works only with the commands an operator is normally allowed to send.
Rather than measuring how much of a controller's software it has exercised, the usual yardstick for this kind of testing, ICSFlux measures how close the physical system is getting to an unsafe limit and steers its testing in that direction.
“Two different sensor readings can run through the exact same code and still send a reactor in completely different directions,'' Sahin said. “Looking only at the software tells you nothing about whether the physical system is safe. We had to follow the physics, not the code.''
One of the study's most important takeaways emerged when the researchers tightened the safety margins to see whether caution alone would help. Even when every command stayed within approved limits, the way the controller reacted to a steady stream of small adjustments could still cause pressure to overshoot and the reactor to fail. In other words, staying inside the rules was not always enough.
All of the team's experiments were carried out on secured, controlled test beds. The work was conducted with Georgia Tech's Cyber-Physical Systems Security Lab, whose research spans the security of cyber-physical systems from industrial programmable logic controllers to marine, automotive, and drone platforms. Georgia Tech's Cyber Forensics Innovation Laboratory, a team of researchers who work together to further the investigation of advanced cyber crimes and the analysis and prevention of next-generation malware attacks, also contributed to the paper.
The labs are a collaboration between the School of Cybersecurity and Privacy and the School of Electrical and Computer Engineering.
Fuzzing the Physical Space: Physics-Aware Testing of Black-Box Industrial Control Systems' was accepted to the 2026 IEEE Symposium on Security and Privacy. In addition to Sahin, the team includes Ph.D. students David Oygenblik, Mingxuan Yao, and Yizhi Huang as well as Associate Professors Brendan Saltaformaggio, and Saman Zonouz.
]]>Logically this makes sense and has been backed up by past security research. However, researchers at Georgia Tech have found hidden paths in cyber-physical systems that attackers can use to disrupt or even destroy them.
To find these hidden paths before an attacker does, the researchers built a testing tool called ICSFlux. This new tool leans on the physics used by the industrial process and maps out the system to find new threats that were once thought impossible.
]]>Communications Officer II at the School of Cybersecurity and Privacy
]]>“It’s a tremendous honor to be recognized alongside such an inspiring group of scientists,” Manafzadeh says. “I’ve always been motivated by big, fundamental questions, and it’s exciting to see that kind of curiosity-driven research celebrated.”
Manafzadeh will join Georgia Tech in August 2026 as an assistant professor in the School of Biological Sciences. Her research investigates how joints function and how they evolved, using advanced technology to create animations of moving skeletons with sub-millimeter precision.
“My research is aimed at understanding how joints work and where they come from,” she explains. “Physicians can repair ACL injuries and perform hip replacements, but we still don’t fully understand joint mechanics at a fundamental level.” Because joints are a shared feature of virtually all vertebrates, she adds, nearly all movement — from slithering to sprinting to soaring — depends on them.
Manafzadeh first applied these methods to pterodactyls, “reanimating” the extinct animals to study how they flew. Now, her research could also open doors to personalized surgical treatments for people and new designs for bio-inspired robots.
]]>Technical Research Writer / Editor
Georgia Tech College of Sciences
]]>For most, that heart-pounding uncertainty ends the moment the foot finds solid ground. But for many individuals living with conditions like stroke or spinal cord injury (SCI), that sense of disconnect is a permanent reality.
“These conditions of course have a huge effect on our ability to move around and be independent — but the other side of it is the sensory feedback that we lose,” says Matthew Flavin, an assistant professor in the School of Electrical and Computer Engineering. Most rehabilitation treatments primarily focus on restoring movement, but “even if you have motor control, if you can’t feel when your foot's touching the ground it can be really hard for you to move around safely.”
In a new study published in Proceedings of the National Academy of Sciences, Flavin and an interdisciplinary team of researchers introduce a way to bridge this gap: a wearable “sensory substitution” system that translates foot pressure into high-tech patterns of heat and vibration they can feel elsewhere.
The system uses high-resolution pressure-sensing insoles designed by the team, which are placed inside a user's shoes to record how their weight shifts in real-time. This data is streamed via Bluetooth to a flexible, skin-conformable array of haptic receivers worn on the forearms, a part of the body that often retains sensation in SCI. The receivers give quick pressure feedback through vibration, while also alerting the user to longer-term pressure “hotspots” through heat.
“One of the limitations of a lot of approaches in haptics is that you're having to map a missing sense onto a completely different sense,” says Flavin. “We’re keeping the type of information that we're missing, which is the distribution of pressure, and we're just basically putting it on a different part of their body.”
Rerouting the lost sensation was key to making the device intuitive to learn. Participants were able to correctly identify the “feel” of the ground through their arms with high accuracy within a mere two-hour session. When tested with a small group of participants with stroke or SCI, the wearable significantly improved standing balance and led to steadier walking.
“What’s encouraging about these early results is that participants appeared to use the feedback in ways that supported balance and walking,” says John Rogers, a materials science and engineering professor at Northwestern University who collaborated on this study. “Our study suggests that providing pressure information through another part of the body could be a practical path for helping people compensate for lost sensation.”
While vibration provides immediate feedback for walking and balance, the team views the thermal feedback as a tool for long-term health. Heat is a slower, low-frequency signal that could alert patients to pressure hotspots, potentially preventing diabetic foot ulcers or pressure injuries for those who are bedridden or use wheelchairs.
The small, lightweight system is completely untethered, making it suitable for use during daily activities in and outside the clinic. It’s also highly adaptable to different injury types, which is ideal for conditions as variable as stroke, SCI, and diabetic neuropathy. Placement of the haptic receivers can be adjusted based on where a patient has the most sensation, and the sensitivity of the insoles can be tailored to each patient.
As a member of several of Georgia Tech’s Interdisciplinary Research Institutes — the Institute for Neuroscience, Neurotechnology, and Society, the Institute for Robotics and Intelligent Machines, and the Parker H. Petit Institute for Bioengineering and Biosciences — Flavin credits the project’s success to an interdisciplinary effort and deep engagement with clinicians and patients.
“This reinforces the importance of really engaging with your stakeholders very early on,” says Flavin. “If you're not continually refining that concept with those stakeholders, you quickly find that they might be looking for something that your device isn't delivering.”
With new funding from the National Science Foundation (NSF), the team is now working to make the technology even smaller and more reconfigurable, moving closer to a standard wearable for daily clinical use.
DOI: https://doi.org/10.1073/pnas.2536577123
]]>Photos:
Maxwell Guberman
The continued recognition highlights Georgia Tech’s research leadership in advancing energy solutions across technology, science, policy, and economics and in delivering technically advanced solutions that is scalable, secure, and sustainable for the future.
“The scale and integration of our energy ecosystem is among Georgia Tech’s great strengths,” said Executive Vice President for Research Tim Lieuwen. “A defining part of that ecosystem is the Strategic Energy Institute (SEI), our interdisciplinary research institute that brings together the talents of researchers from across disciplines to accelerate energy innovation and deliver real-world solutions.”
SEI integrates energy activities at Georgia Tech by connecting more than 1,000 researchers across the entire energy value chain and enabling collaboration with industry, government, communities, and nonprofits. SEI is deeply engaged in building community, developing resources, promoting thought leadership, and marshaling the full resources of Georgia Tech around tackling the tough energy and environmental problems and opportunities society faces.
“Georgia Tech’s energy leadership is built on the depth of our research and the breadth of our collaborations,” said Yuanzhi Tang, SEI’s executive director. “By connecting expertise across the full energy value chain, we are advancing solutions that enhance affordability, reliability, security, and sustainability.”
U.S. News & World Report evaluates the academic research performance of universities in 51 subject areas using indicators such as publications, citations, and global and regional research reputation. Georgia Tech was assessed among 292 institutions in the U.S. and continues its strong standing in the rankings, claiming the No. 32 spot overall in the nation and No. 9 among public universities.
]]>The continued recognition highlights Georgia Tech’s research leadership in advancing energy solutions across technology, science, policy, and economics and in delivering technically advanced solutions that is scalable, secure, and sustainable for the future.
]]>Lieuwen, the executive vice president for Research and Regents’ Professor in the Daniel Guggenheim School of Aerospace Engineering, received the ASME medal in 2025 in recognition of his pioneering contributions to combustion, clean energy, and the science of resilient energy systems. It is the first ASME Medal ever awarded to a Georgia Tech faculty member or graduate, marking a milestone both for Lieuwen and the Institute.
Read the full story on the George W. Woodruff School of Mechanical Engineering website.
]]>Lieuwen, the executive vice president for Research and Regents’ Professor in the Daniel Guggenheim School of Aerospace Engineering, received the ASME medal in 2025 in recognition of his pioneering contributions to combustion, clean energy, and the science of resilient energy systems. It is the first ASME Medal ever awarded to a Georgia Tech faculty member or graduate, marking a milestone both for Lieuwen and the Institute.
]]>Scientists have captured the most detailed structural images to date of a specific type of protein’s DNA repair process. The research could reveal ways to inhibit the effects of the BRCA1 and BRCA2 gene mutations that heighten the risk for breast, ovarian, and other cancers.
“This work lets us see, step by step, one mechanism by which cancer cells could manage to repair their DNA when BRCA genes mutate and fail,” says study co-author Vicki Wysocki, who is chair of the Georgia Tech School of Chemistry and Biochemistry. “By capturing this process in detail, this study opens the door to understanding how those cancerous cells survive and how treatments might disrupt that mechanism.”
Designated as a Breakthrough Article, the study Mechanism of single-strand annealing from native mass spectrometry and cryo-EM structures of RAD52 homolog Mgm101 was recently published in Nucleic Acids Research.
In addition to Wysocki, who is a professor in the School of Chemistry and Biochemistry and a professor emerita at Ohio State University, the Georgia Tech research team included co-first author Zihao Qi, a Ph.D. candidate in the Wysocki Lab.
They were joined by Ohio State researchers co-first author Carter Wheat and senior author Charles Bell, who is a professor of biological chemistry and pharmacology in the College of Medicine. Additional authors include Metro High School student Miqdad Hussain and CAS researcher Katerina Zakharova.
Normally, BRCA genes help prevent cancer by acting as tumor suppressors — producing proteins that help repair broken DNA. When cancer cells lack the tumor-suppression function of normal BRCA genes, research has shown that a protein called RAD52 performs DNA repair.
Since RAD52 allows cancer cells to survive and replicate without tumor suppression, researchers have wondered if blocking it would kill the cancerous cells. Blocking RAD52, however, requires fully understanding its repair activities, which have been difficult to capture with even the most sophisticated techniques.
DNA strands break every day in cells, which is why proteins exist to fix the breaks and keep cellular processes running smoothly, the team says. But because repairs must happen quickly and human proteins are often more complex than their ancestral counterparts, even the most advanced imaging equipment can’t capture every step in the process.
In order to understand RAD52 better, the research team turned to its ancestral protein, Mgm101, to observe several key steps in its DNA repair process.
The team decided to leverage multiple types of imaging. Wysocki’s lab at Georgia Tech conducted native mass spectrometry and mass photometry, using light to measure masses of protein-DNA complexes. The results showed that the ancestral protein Mgm101 assembled from a single copy of itself into a large multi-unit ring composed of 19 copies of the protein.
“This ring is essentially a template,” Wysocki explains. “The first strand of DNA can come down, and then the second strand comes on and starts being annealed to the first strand.” Annealing occurs when two single strands of DNA come together to form the characteristic double helix structure.
The findings were supported by what Bell’s lab determined using cryogenic electron microscopy, observing structures floating in solution and frozen in a thin layer of ice.
“RAD52 high-resolution structures have been determined with single-stranded DNA, but not with the two DNAs that it’s trying to anneal,” Bell says. “Its job is to bind single-stranded DNA and anneal it to its complement sequence. It’s been captured structurally, but only in a few states relevant to the reaction.”
“Here, we have more of the states along the full pathway from substrate, to intermediate and product. And the duplex intermediate is a conformation that’s never been seen before.”
Previously, researchers were unsure if this DNA repair process used one protein ring or two rings working together, the team says. Their findings show that just one ring is used — and that this is likely consistent across different species.
Next, the team plans to try capturing the same phases of the DNA repair process with RAD52 from humans. A clearer understanding of how this family of proteins binds to DNA strands and coaxes them back together after a break provides insights for drug targets that could halt the process in cancer cells empowered by mutated BRCA genes, they say.
“It’s still a proposed mechanism: Just because we see these snapshots of the process doesn’t mean we know all the details, but we do have the best snapshots for any protein that does this single-strand annealing,” says Bell. “This focuses our strategies for drug development.”
DOI: https://doi.org/10.1093/nar/gkag320
Funding: This work was supported by the U.S. National Science Foundation and the National Institutes of Health. The cryo-EM data were collected at Ohio State’s Center for Electron Microscopy and Analysis and processed using the Ohio Supercomputer Center.
]]>Research Writer / Editor
Georgia Tech College of Sciences
]]>It was Ferguson’s own first manufacturing industry job at Glidden Paint in high school that tipped a row of dominoes, clearing his way out of poverty. Following next in the Hall County native’s favor was his receiving the Pell Grant and HOPE Grant, which led to his associate’s degree and first job in education.
Since then, Ferguson has spent the better part of three decades advancing workforce preparation and education access in Georgia, first as chief information officer for the Technical College System of Georgia, and now through his current roles at Tech.
“Access to higher education changed the trajectory of my life. The question now is how we build systems that create those same opportunities for others — whether someone starts their career right out of high school, earns credentials while working, or returns later to pursue advanced technical education or engineering. We need to create flexible pathways that develop talent at every stage of life.”
Steven Ferguson
Ferguson was born into a family of “makers,” who got by on odd jobs and money from their small bait and tackle shop on Lake Lanier and later peddling a variety of goods. At a young age, Ferguson learned salesmanship and picked up the tinkering spirit.
“My dad was always entrepreneurial, and I think you might even consider us manufacturers, always making fishing equipment or other things,” said Ferguson. “From a very young age, I was out making jig heads, tying flies, and bagging hooks or sinkers. It was definitely in my blood.”
When he was in 10th grade, a teacher nominated Ferguson for a new youth apprenticeship program. That opportunity ultimately led to his role as an information technology apprentice at Glidden Paint, which became Ferguson’s first job in the manufacturing industry. The job was a perfect fit for Ferguson, who enjoyed learning more about the manufacturing process and the practical outlet for his computing knowledge.
He continued working there until he began studying computer science at North Georgia College and State University. Later, he transferred to Gainesville College (GC) to participate in a joint enrollment program designed to lead to eventual enrollment for a bachelor’s degree at Tech.
However, before Ferguson completed his time at GC, he had an associate’s degree and, more importantly, a job offer. GC wanted him to train others for careers in information technology.
Read Full Story on the Enrollment Management News Page
]]>It was Ferguson’s own first manufacturing industry job at Glidden Paint in high school that tipped a row of dominoes, clearing his way out of poverty. Following next in the Hall County native’s favor was his receiving the Pell Grant and HOPE Grant, which led to his associate’s degree and first job in education.
Since then, Ferguson has spent the better part of three decades advancing workforce preparation and education access in Georgia, first as chief information officer for the Technical College System of Georgia, and now through his current roles at Tech.
]]>That principle is especially relevant today across the artificial intelligence (AI) landscape. As systems scale, they increasingly become harder to measure, compare, and fix, particularly within proprietary environments.
A team led by Georgia Tech, working with collaborators across industry, has developed a new approached called Chakra to bring greater clarity to complex AI systems.
“Imagine a room where everyone is trying to collaborate, but each person speaks a different language,” said Tushar Krishna, an associate professor in the School of Electrical and Computer Engineering, who is leading the effort. “That’s a bit like today’s AI ecosystem. The internet worked because it was built on shared practices and protocols. In AI, we’re still building that kind of common foundation.”
The work, which Krishna leads through the nonprofit MLCommons, was released alongside a paper at the 2026 Conference on Machine Learning and Systems(MLSys) in Bellevue, Wash.
Understanding Systems Without Exposing Them
Cloud companies, chip designers, software developers, and infrastructure providers all describe their systems differently, relying largely on internal, proprietary approaches that are not publicly shared.
This slows innovation, reduces efficiency, and increases the cost of running AI at scale.
Chakra, named after the Sanskrit word for “wheel” to reflect a continuous cycle of improvement, is designed around that reality. Its release is not a single finished system, but a set of shared tools and building blocks.
Researchers are making available a standardized format for representing AI workloads, along with tools for collecting and analyzing data from what’s known as an execution trace.
“An execution trace is essentially a recording of how an AI system behaves,” Krishna said. “Rather than focusing only on outcomes like speed or accuracy, it captures what computations happened, when machines needed to communicate, and where delays or bottlenecks occurred.”
Those traces don’t expose the underlying code or data. Instead, they reflect patterns of behavior.
Those traces don’t expose the underlying code or data. Instead, they reflect patterns of behavior.
“It’s a bit like sharing a map of traffic patterns in a city, instead of handing over the blueprints for every building,” Krishna said.
The approach can also be used to explore how future systems might behave, giving researchers a way to test ideas and identify potential bottlenecks before those systems are built.
“All of this dramatically lowers the barrier to participating in AI systems innovation,” Krishna said.
Building a Shared Standard
The Chakra project began in 2023 as a collaboration between Georgia Tech and Meta, building on parallel efforts to better understand how AI workloads behave across production systems and simulation environments.
Part of that work built on ASTRA-sim, an open-source distributed AI system simulator developed and maintained by Krishna’s group, which models how large-scale AI systems perform across hardware and software.
“We knew that for AI to scale responsibly, we needed better ways to understand what’s happening under the hood,” Krishna said. “Companies struggle to compare systems fairly or reproduce why something worked well—or failed—because everyone uses different tools and proprietary setups.”
The early collaboration expanded into a broader effort called the Chakra Working Group (CWG) within MLCommons, a consortium that brings together companies and researchers to develop shared benchmarks and standards for AI systems, including widely used efforts like MLPerf.
David Kanter, co-founder of MLCommons and head of MLPerf, has praised the group for “defining an industry roadmap for AI workload tracing support and benchmarking.”
Today, CWG includes industry partners such as NVIDIA, AMD, Meta, HPE, and Keysight, along with contributions from multiple Georgia Tech faculty, students, and alumni (seven of whom are now working across partner organizations).
“Chakra is a fantastic showcase of the role ECE and Georgia Tech play in connecting academic research with real-world systems,” said Arijit Raychowdhury, Steve W. Chaddick School Chair of ECE. “We can bring together expertise spanning the full AI stack in really the only way that makes complex work like this possible.”
That level of collaboration is essential to developing something that can be used across the broader AI ecosystem, according to Winston Liu, a chief architect at Keysight Technologies and a member of CWG.
“What the Chakra community has built is meaningful, but the collaboration model that produced it is worth recognizing just as much,” he said. “That combination—early enough to shape the spec together and open enough that the output belongs to everyone—is genuinely rare.”
A Real-world Testbed at Georgia Tech
Much of the team’s work has depended on access to infrastructure capable of running AI systems at a realistic scale. Georgia Tech has built that capability through its AI Makerspace, one of the largest computing clusters in the world dedicated to supporting student-driven AI workloads while also serving as a real-world testbed for large-scale systems research.
In collaboration with the Partnership for an Advanced Computing Environment (PACE), CWG researchers utilized the AI Makerspace to run workloads across 128 advanced GPUs and collect execution traces from systems operating under real conditions.
“The AI Makerspace was built on a simple belief: AI should be accessible to as many as possible,” said Matthieu Bloch, associate dean in the College of Engineering. “It’s exciting to see our colleagues using it to amplify impact and give back to the broader community.”
That level of access allowed the work behind Chakra to move beyond theory and into environments where performance challenges actually emerge.
In one case study, Chakra helped identify a hidden communication bottleneck that only appeared under realistic conditions when different types of workloads were running at the same time. More simplified tests failed to surface the issue.
What Comes Next
As the Chakra tools and standards are released, the focus now turns to how they will be adopted and extended.
Krishna sees the current moment less as a finish line and more as a starting point for broader participation across the field.
“Five years from now, Chakra will help make AI systems development dramatically more reproducible and accessible,” he said. “Researchers could test ideas against realistic workloads without needing access to massive datacenters, and companies could identify problems much earlier in the design process.”
As AI infrastructure grows more costly, the ability to model new system designs allows researchers and companies to make informed decisions before committing to large-scale investments.
“Longer term, it could move us toward a ‘digital twin’ of AI infrastructure,” Krishna said. “A way to model and optimize systems before they’re ever built.”
His project was selected through a competitive, peer-reviewed process involving scientific experts, state and local resource managers, and coastal community stakeholders as part of a biennial research competition sponsored by the University of Georgia’s Marine Extension and Georgia Sea Grant, supported by the NOAA National Sea Grant College Program.
“I am excited to continue to contribute to Sea Grant’s critical mission of research that strengthens the resilience of coastal ecosystems,” says Kostka.
Kostka’s team will examine how locally sourced Spartina plants and beneficial root-associated microbes can improve marsh restoration outcomes. The research will evaluate plant growth, stress tolerance, and field performance to identify practical, scalable strategies for supporting coastal ecosystems.
Selected projects are intended to “advance the understanding, management, and strategic use of Georgia’s coastal and marine resources,” while producing results that address coastal management needs and remain accessible to communities, according to an article from Marine Extension and Georgia Sea Grant. In addition to faculty from Georgia Tech, the 2026 research awards will support investigators from Georgia Southern University and Savannah State University.
]]>Fiona Ryan, a Ph.D. student in Georgia Tech’s School of Interactive Computing, is pioneering research that tracks and predicts user gaze from a first-person perspective in 3D environments.
Currently, most AR devices react to where users look, playing catch-up. Ryan’s method could give these devices a heads-up and make the user experience more seamless.
“It allows an AR system to anticipate what the person will interact with next and where they’re going to look next so it can proactively render the experience,” she said.
Ryan is the lead author of the paper Forecasting 3D Scanpaths in Egocentric Video, which she will present next week at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in Denver.
While there is existing research on predicting user gaze from 2D still images, her work is the first to address the issue through a 3D framework.
“Because we live in a 3D world and people are dynamically moving around from multiple points of view, we need to predict gaze in 3D rather than 2D,” she said. “What we’re seeing is a path of the person’s attention in 3D through space. Our paper is the first to attempt to model this.”
Ryan conducted most of the research while interning at Meta, where she used data from Meta’s Aria Digital Twin dataset. The dataset contains first-person video footage of users interacting with objects in an apartment.
“We chose that dataset because it has a high-fidelity 3D reconstruction of a full environment, which helps us get a ground-truth 3D gaze,” she said. “We can trace eye movement and see how it intersects with the environment.”
A video demonstration of Ryan’s work shows her software tracking a user’s path toward a table with a cup on it. Once the user picks up the cup, the software correctly predicts the direction the user will turn next.
“When we look at a scene, we don’t take in everything in full detail all at once,” she said. “We fixate on certain areas, and our gaze is a sequence of fixations, which might depend on what we’re trying to do. If we want to pick up a cup, we might look toward that and then the next step would be looking at where we’re going to put it down.”
Ryan said the software can predict, on average, up to three seconds into the future — and as far as 10 seconds in some cases. That’s enough time for the AR system to proactively render a more enhanced environment.
“We’re not looking that far into the future right now, but it would be interesting to explore longer forecasting windows,” she said. “I think potential futures would diverge pretty quickly, so we’re trying to explore what can reasonably be predicted from a short segment of a person looking and moving through space.”
Ryan said her paper served as a proof-of-concept, and that there is still much future work to be done. She already has some ideas.
“I think future models can include different scenarios to help narrow down possibilities. Sometimes a person’s gaze stays on one thing for a long time. If we know what someone is trying to do, we’ll have a better idea of the likely path their attention might go.”
There could also be future implications for her work in robotics research.
“It could potentially be used for training algorithms for robots to emulate active human perception. If we can understand what a person looks at as they perform a task, we could use that to facilitate a robot learning to do that same task.”
]]>Fiona Ryan, a Ph.D. student in Georgia Tech’s School of Interactive Computing, is pioneering research that tracks and predicts user gaze from a first-person perspective in 3D environments.
Currently, most AR devices react to where users look, playing catch-up. Ryan’s method could give these devices a heads-up and make the user experience more seamless.
“It allows an AR system to anticipate what the person will interact with next and where they’re going to look next so it can proactively render the experience,” she said.
Ryan is the lead author of the paper Forecasting 3D Scanpaths in Egocentric Video, which she will present next week at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in Denver.
While there is existing research on predicting user gaze from 2D still images, her work is the first to address the issue through a 3D framework.
“Because we live in a 3D world and people are dynamically moving around from multiple points of view, we need to predict gaze in 3D rather than 2D,” she said. “What we’re seeing is a path of the person’s attention in 3D through space. Our paper is the first to attempt to model this.”
Ryan conducted most of the research while interning at Meta, where she used data from Meta’s Aria Digital Twin dataset. The dataset contains first-person video footage of users interacting with objects in an apartment.
“We chose that dataset because it has a high-fidelity 3D reconstruction of a full environment, which helps us get a ground-truth 3D gaze,” she said. “We can trace eye movement and see how it intersects with the environment.”
A video demonstration of Ryan’s work shows her software tracking a user’s path toward a table with a cup on it. Once the user picks up the cup, the software correctly predicts the direction the user will turn next.
“When we look at a scene, we don’t take in everything in full detail all at once,” she said. “We fixate on certain areas, and our gaze is a sequence of fixations, which might depend on what we’re trying to do. If we want to pick up a cup, we might look toward that and then the next step would be looking at where we’re going to put it down.”
Ryan said the software can predict, on average, up to three seconds into the future — and as far as 10 seconds in some cases. That’s enough time for the AR system to proactively render a more enhanced environment.
“We’re not looking that far into the future right now, but it would be interesting to explore longer forecasting windows,” she said. “I think potential futures would diverge pretty quickly, so we’re trying to explore what can reasonably be predicted from a short segment of a person looking and moving through space.”
Ryan said her paper served as a proof-of-concept, and that there is still much future work to be done. She already has some ideas.
“I think future models can include different scenarios to help narrow down possibilities. Sometimes a person’s gaze stays on one thing for a long time. If we know what someone is trying to do, we’ll have a better idea of the likely path their attention might go.”
There could also be future implications for her work in robotics research.
“It could potentially be used for training algorithms for robots to emulate active human perception. If we can understand what a person looks at as they perform a task, we could use that to facilitate a robot learning to do that same task.”
]]>With more than 150 attendees from industry, academia, and research organizations, the event’s high-level engagement underscored the urgency of critical issues facing the energy sector today, including the surging electricity demand, resiliency of the grid, and evolving supply chains, as well as the value of a dedicated space for candid, solutions-oriented dialogue.
“INTERSECT 2026 demonstrated the power of bringing together leaders who are actively shaping the future of energy,” said Laura Taylor, director of EPIcenter. “What began as a forum to explore emerging ideas has grown into a critical platform for aligning perspectives and advancing actionable solutions across the Southeast.”
This year’s program focused on real-world implementation challenges, including managing large-scale load growth and coordinating infrastructure investments to meet demand reliably and affordably. Panels featuring leaders from utilities, global energy corporations, and research organizations emphasized the importance of aligning strategy across sectors to ensure that the Southeast remains competitive and resilient.
Chris Womack, chairman, president, and CEO of Southern Company, delivered the keynote address, highlighting the unprecedented scale of current energy demands.
“Meeting this moment requires us to think differently — serving growth while ensuring reliability, resilience, and long-term value for our customers and communities,” said Womack.
Launched in 2017, the inaugural INTERSECT conference marked the launch of EPIcenter itself and established Georgia Tech’s commitment to connecting research, industry insight, and policy development. It focused on the need to bridge the gap between rapidly advancing technologies and slower-moving regulatory and market frameworks, a theme that continues to shape its mission today.
As INTERSECT 2026 concluded, participants pointed to a shared takeaway: With its industrial base, growing population, and integrated energy systems, the Southeast is uniquely positioned to lead in the next phase of the energy transition. With AI-driven power demand and grid infrastructure playing a significant role going forward, it is imperative to bring together the right voices to shape policies and strategies that will connect ideas to action.
]]>The highly competitive Laboratory Placement program is a paid opportunity offered through the U.S. Department of Energy’s Science Undergraduate Laboratory Internships. It provides students from a wide range of disciplines an opportunity to contribute to cutting-edge research at leading facilities, including Argonne National Laboratory, Ames National Laboratory, Lawrence Berkeley National Laboratory, National Laboratory of the Rockies, Oak Ridge National Laboratory, Princeton Plasma Physics Laboratory, and Savannah River National Laboratory.
The program’s 2026 cohort includes 16 Georgia Tech students from disciplines such as artificial intelligence, materials science, aerospace engineering, nuclear engineering, chemical engineering, mechanical engineering, and physics. Their research placements reflect the interdisciplinary nature of today’s scientific challenges, with projects covering bioinformatics, high-energy and condensed matter physics, accelerator science, environmental management, and advanced materials.
Many of the internships are closely aligned with national energy priorities, with students working in research areas including nuclear energy, hydrogen and chemical systems, materials for energy applications, plasma and fusion sciences, and complex engineered systems.
“Georgia Tech’s deep engagement with the national laboratory system creates unparalleled opportunities for our students to contribute to the future of energy,” said Yuanzhi Tang, executive director of the Strategic Energy Institute. “By connecting interdisciplinary talent with world-class research environments, we are not only advancing discovery but also shaping the next generation of leaders who will drive secure, sustainable, and resilient energy systems.”
Working alongside national lab scientists, students will not only gain access to world-class facilities but benefit from mentorship and professional networks, while contributing to research critical to national security, economic competitiveness, and a more sustainable energy future.
“These internships demonstrate the strength of Georgia Tech’s relationships across the federal research ecosystem,” said Robert Knotts, executive director of Federal Relations in the Office of Institute Relations. “They provide a direct pathway for students to engage in public service through mission-driven research at national laboratories — while strengthening connections that are vital to advancing national priorities in energy, security, and innovation.”
]]>The highly competitive Laboratory Placement program is a paid opportunity offered through the U.S. Department of Energy’s Science Undergraduate Laboratory Internships. It provides students from a wide range of disciplines an opportunity to contribute to cutting-edge research at leading facilities, including Argonne National Laboratory, Ames National Laboratory, Lawrence Berkeley National Laboratory, National Laboratory of the Rockies, Oak Ridge National Laboratory, Princeton Plasma Physics Laboratory, and Savannah River National Laboratory.
]]>Traditional sleep monitoring systems often rely on bulky equipment and nasal cannulas — small tubes inserted into the nostrils to measure airflow. While effective, these systems can be uncomfortable, intrusive, and difficult to tolerate overnight, limiting their use for long-term monitoring at home.
Now, researchers led by W. Hong Yeo, Peterson Professor in Pediatric Research at the George W. Woodruff School of Mechanical Engineering, have developed a soft, wireless nasal patch that could offer a more comfortable alternative for monitoring breathing during sleep.
The technology, described in a recent study published in Proceedings of the National Academy of Sciences (PNAS), uses ultrathin, skin-like wearable electronics to detect subtle movements of the nose caused by breathing without tubes, wires, or direct airflow measurements.
Read the full story on the George W. Woodruff School of Mechanical Engineering website.
]]>Traditional sleep monitoring systems often rely on bulky equipment and nasal cannulas — small tubes inserted into the nostrils to measure airflow. While effective, these systems can be uncomfortable, intrusive, and difficult to tolerate overnight, limiting their use for long-term monitoring at home.
Now, researchers led by W. Hong Yeo, Peterson Professor in Pediatric Research at the George W. Woodruff School of Mechanical Engineering, have developed a soft, wireless nasal patch that could offer a more comfortable alternative for monitoring breathing during sleep.
The technology, described in a recent study published in Proceedings of the National Academy of Sciences (PNAS), uses ultrathin, skin-like wearable electronics to detect subtle movements of the nose caused by breathing without tubes, wires, or direct airflow measurements.
]]>College of Sciences alumni and graduate students are among the seventy-five Yellow Jackets awarded Graduate Research Fellowships (GRF) from the National Science Foundation. The fellowships, valued at $159,000, include funding for three years of graduate study and tuition for graduate students pursuing full-time, research-based master’s and doctoral degrees in science, technology, engineering, and mathematics (STEM) or STEM education.
The Georgia Tech recipients of the fellowship, which has supported over 70,000 students since its inception in 1952, were selected from a pool of more than 14,000 applicants nationwide. Fellowships are awarded to students “who have demonstrated potential for significant achievements in research.”
Discover the full list of Georgia Tech awardees.
This concept of “lab tool as lab assistant” is the premise of a recent paper in npj | Computational Materials titled “Thinking Microscopes: Agentic AI and the Future of Electron Microscopy,” by Vida Jamali, assistant professor the School of Chemical and Biomolecular Engineering; Amirali Aghazadeh, assistant professor in the School of Electrical and Computer Engineering; and Josh Kacher, associate professor in the School of Materials Science and Engineering.
In the paper, the team introduces the concept of “thinking electron microscopes,” in which agentic AI systems are directly integrated with the instrument. This allows microscopes to move beyond their conventional role as characterization tools and toward functioning as co-scientists for human users.
Drawing on advances in specialized large language models, or LLMs, that demonstrate their ability to collaborate, reason over data, and integrate prior knowledge, the team envisions specialized LLM-based agents assigned to specific roles and areas of knowledge expertise. By explicitly incorporating domain knowledge into specialized agents and distributing information across multiple agents with focused expertise, the approach enables parallel evaluation of competing hypotheses, clearer separation of roles — such as planning, simulation, and critique — and more transparent and robust reasoning.
Within the experimental pipeline, these agents can analyze materials’ properties, physical data, chemical processes, and other relevant parameters. They could also collaborate with an agent that specializes in experimental design, refining iterative closed-loop experimentation, and real-time scientific discovery.
Although the research focuses on AI collaboration, the team notes that human researchers must retain accountability for the accuracy and integrity of both the experimental process and the results reported. This oversight begins with advocating for greater open access to research materials in all formats, building community-driven data repositories, and adopting standardization in how experimental parameters and metadata are reported. Equally important, researchers should be willing to report data from failed experiments as well as successful outcomes. Finally, organizations should work together to standardize secure APIs that enable shared, remote access to infrastructure across distances.
We see this as a step toward scientific instruments that do more than acquire data; systems that can reason over experiments, adapt measurements, and participate in the scientific discovery process alongside researchers. - Vida Jamali, assistant professor the School of Chemical and Biomolecular Engineering
The team is already developing these systems by connecting cloud-based, agentic infrastructures to microscopes at the Institute for Matter and Systems at Georgia Tech. With the addition of agentic AI, the goal is to accelerate discovery and engineering of new nanoscale materials for energy and quantum applications, as well as advance capabilities in cryo-electron microscopy and structural biology. These tools can optimize data collection, link real-time microscope observations with structural models of proteins, and dynamically adjust and prioritize experiments. The team sees this work as the first step toward the next generation of “thinking” electron microscopes, as well as an advancement in scientific discovery across domains.
- Christa M. Ernst
This research is supported by the Institute for Data Engineering and Science and the Institute for Matter and Systems
Original Publication
Jamali, V., Aghazadeh, A. & Kacher, J. Thinking microscopes: agentic AI and the future of electron microscopy. npj Computational Materials 12, 149 (2026). https://doi.org/10.1038/s41524-026-02077-y
The NSF CAREER Award supports early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. The award provides $662,045 over five years to support Sanders’ project, Patterning Hard Interlocking Particles to Achieve Soft Materials and Structures.
Read the full story on the George W. Woodruff School of Mechanical Engineering website.
]]>The NSF CAREER Award supports early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. The award provides $662,045 over five years to support Sanders’ project, Patterning Hard Interlocking Particles to Achieve Soft Materials and Structures.
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