The Georgia Tech community should anticipate increased traffic and temporary road closures near McCamish Pavilion on Monday, Nov. 2, and Friday, Nov. 13. 

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, EI2program 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.”

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Hip-hop has long used remixing to transform existing sounds, ideas, and cultural influences into something new. At Georgia Tech, that creative practice provides a framework for thinking about innovation across design, education, and technology.

The next CTRL+CM Speaker Series event, Remixing Innovation: How Hip-Hop Shapes Creativity, Design, and Technology, will bring together two Georgia Tech faculty members to explore these connections. The conversation will feature Joycelyn Wilson, an associate professor in the School of Literature, Media, and Communication (LMC), and will be moderated by Professor Susana Morris, also with LMC.

The event will be held Tuesday, Nov. 10, from 11 a.m. to 1 p.m. in the Scholars Event Theater. It is free and open to the public, and lunch will be provided. Registration is required.

Drawing on her book, Hacking Hip Hop: Design Remix Logic in Research, Method, and Practice, Wilson will examine how hip-hop's remix logic can inform creative technology and innovation. The discussion will explore how cultural practices can inspire new approaches to problem-solving, creative expression, and technological development.

Wilson, an educational anthropologist, documentary film producer, and hip-hop scholar, studies the intersections of hip-hop, media, culture, design, technology, and education. Her work examines how community, storytelling, and remix culture can shape how people learn, create, and develop new technologies.

Morris will moderate the conversation, drawing on her scholarship in Black feminism, culture, storytelling, media, and Afrofuturism. She is the author of Positive Obsession: The Life and Times of Octavia E. Butler and a co-founder of the Crunk Feminist Collective. Her work examines how race, gender, literature, and cultural expression shape how people imagine and engage with the future.

Together, Wilson and Morris will explore how cultural knowledge and creative practices can drive innovation and challenge conventional boundaries among the humanities, design, and technology. Their conversation will highlight how understanding the cultural contexts behind creative work can open new possibilities for technological development and problem-solving.

The event is part of the CTRL+CM Speaker Series, an initiative of the Collective Impact of Creative Technology (CICT) program. The series brings perspectives on culture, creativity, and technology into conversation, highlighting the ways interdisciplinary thinking can inform contemporary questions in innovation and design.

Funding from the Maxwell/Hanrahan Foundation supports the CICT program. Generative AI was used to assist with an initial draft of this article. The author reviewed, revised, and fact-checked the content and is responsible for the final version.

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. 

The conference had three goals: to showcase research by ML@GT's PhD students, to show students what's happening in other labs and fields, and to build more collaboration across the Center.

The program included 12 student presentations across four research themes. More than 20 posters were on display during the poster session. Topics ranged from efficient prediction and protein modeling to brain-computer interfaces, seizure detection, and acoustic perception.

Attendees, including Georgia Tech faculty and students, voted for their favorite presentations and posters. Prizes went to the top three in each category.

Presentation Awards

• 1st Place: Hangyu Zhou, "Learning Computational Structure for Sample-Efficient Prediction" - School of Computer Science, advised by Steve Mussmann
• 2nd Place: Darin Tsui, "Protein Circuit Tracing via Cross-layer Transcoders" - School of Electrical and Computer Engineering, advised by Amirali Aghazadeh
• 3rd Place: Pranav Deevi, "FETTUCCINE: Fast and efficient brain-to-text decoding on mobile devices" - School of Biomedical Engineering, advised by Chethan Pandarinath

Poster Awards

• 1st Place: Hyunju Kim, "Spatiotemporal Hyperedges for EEG Seizure Detection and Prediction" - School of Computational Science and Engineering, advised by Nabil Imam
• 2nd Place: Benjamin Burns, "When, why, and how do diffusion posterior samplers fail? A finite-sample lens" - School of Electiral and Computer Engineering, advised by Sara Fridovich-Keil
• 3rd Place: Tianwei Jiang, "Intelligent Acoustic Perception: From Sound Recognition to Multimodal Spatial Understanding" - School of Electrical and Computer Engineering, advised by David Anderson

The winning projects show the range of machine learning research at Georgia Tech. They include basic work on sample efficiency and generative models as well as applications in neuroscience, healthcare, biology, and audio.

The ML@GT Student Conference gives students a chance to share their research and make connections across the Center. ML@GT congratulates all of this year's presenters and award winners.

This article was drafted with the help of Microsoft Copilot.

At each step, companies must decide how much extra inventory to keep. A product can be available, in stock, and ready to ship, yet still be out of reach when customers need it most. In today's interconnected supply chains, even a small disruption can cascade across networks, leading to empty shelves or production delays.
 

“Companies can have plenty of inventory and still run out of products because they are in the wrong place,” explained Andre Calmon, associate professor of operations management at Georgia Tech’s Scheller College of Business. “Our research helps companies decide where to keep extra inventory so they can meet demand without tying up unnecessary money in products sitting on shelves.” 
 

Calmon and his co-authors, Philippe Blaettchen, Georgina Hall, and Mohit Tawarmalani received the 2026 INFORMS Computing Society Harvey J. Greenberg Research Award for their paper, “From Trees to Treewidth: Inventory Management in Complex Supply Chain Networks.” The award recognizes outstanding research at the intersection of operations research and computer science. 
 

A Faster Route to Better Inventory Decisions
 

For decades, major companies like Procter & Gamble, Intel, HP, and Boston Scientific have used a planning framework called the Guaranteed Service Model (GSM) to decide where inventory should be stored across a supply chain. The goal is simple: keep products available when customers need them while minimizing inventory costs.
 

Calmon and his co-authors developed a new mathematical method that makes those decisions much faster.
 

“Our main contribution is a fundamental theoretical advance,” Calmon said. “We developed the first exact method for the Guaranteed Service Model whose computing time is tied to a measure of network structure called treewidth.” 
 

While the underlying mathematics are complex, the core idea is surprisingly intuitive. Rather than analyzing an entire supply chain at once, the method breaks a large network into smaller, overlapping sections. Researchers can solve those sections more efficiently and then combine them into a single optimal plan. As a result, the structure of a supply chain can matter more than its overall size when determining how quickly the problem can be solved. 
 

The result is a dramatically faster way to identify the best inventory strategy.
 

In tests involving 38 real-world supply chains, the researchers found optimal inventory plans for every case they studied. Median computing time dropped from about nine-and-a-half minutes using the previous leading method to just 14 seconds. The new approach also solved large supply chain problems that existing methods could not complete.
 

For businesses, that speed could make it easier to prepare for disruptions before they happen.
 

“A company could test what happens if demand doubles in one region or if a supplier’s shipments take two weeks longer than expected,” Calmon said. “Because our method finds the best plan quickly, companies can explore more scenarios before a disruption and update their plans as conditions change.” 
 

That capability could be especially valuable during disruptive events like pandemics, natural disasters, geopolitical disruptions, or sudden changes in demand. By evaluating more possibilities in less time, companies may be able to maintain product availability while reducing excess inventory and waste. 
 

The Future of Supply Chain Research
 

Calmon's award-winning research grew from a question he once considered "unsolvable" as a doctoral student. Today, that same curiosity continues to guide his work. Looking ahead, he is particularly excited about applying his planning and optimization research to circular supply chains that recover, reuse, and recycle products and materials.
 

“When products and materials re-enter a supply chain, inventory planning becomes more complicated,” he said. “Helping companies manage those flows could make circular business models more practical.  I hope to help build planning tools that let companies tackle larger supply chains and test more possibilities at the speed their businesses require.” 

 
Read More: “Trees to Treewidth”
Learn More: Operations Management 

Iris Tien, Williams Family Professor in the School of Civil and Environmental Engineering, will be the strategic initiative lead for State Engagement. She will help BBISS strengthen collaborations between researchers and local government, with the goals of encouraging research outcomes at the municipal level and amplifying the impact and visibility of Georgia Tech research throughout the state.

Anjali Thomas, associate professor in the Sam Nunn School of International Affairs, and Valerie Thomas, professor and Anderson-Interface Chair of Natural Systems in the H. Milton Stewart School of Industrial and Systems Engineering and the Jimmy and Rosalynn Carter School of Public Policy, are the strategic initiative co-leads for International Engagement. This initiative will address global sustainability and development challenges by convening Georgia Tech experts, identifying areas of scholarly leadership at the Institute, and building on them through international exchange and research partnerships.

Micah Ziegler, assistant professor in the School of Chemical and Biomolecular Engineering and the Carter School of Public Policy, is the strategic initiative lead for Data Infrastructure. The purpose of this initiative is to build data and analysis infrastructure to support multidisciplinary sustainability research across Georgia Tech. Working with faculty, staff, and students, the team will identify the resources that support their research today, the resources that could strengthen it, and the challenges in obtaining, using, and maintaining them. In the long term, the initiative will develop infrastructure that makes sustainability datasets and models easier to share and use across the Institute.

“Iris, Anjali, Valerie, and Micah bring deep expertise and wide networks to these roles. But the real power of these initiatives will come from the colleagues who get involved, and I invite those whose work benefits from or contributes to stronger state engagement, international engagement, or data infrastructure to reach out to them,” says BBISS executive director Beril Toktay.

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.”

Georgia Tech’s Office of Technology Licensing, part of the Office of Commercialization, hosted the inaugural 2026 Innovator Awards Celebration on Sept. 30 at the Georgia Tech Hotel and Conference Center. 

I was on a run on a cool Saturday morning in February when military activity began in Iran. I, like many others, listened and wondered about the impact and duration of this on regional and global supply chains. Over the next few weeks, I talked to many in my network and heard their concerns. They wanted to know how long we thought this would last and what the cascading impacts would be. The Strait of Hormuz had closed on February 28, and even for those with robust contingency plans, this was not on their bingo card.

I happened to be traveling to Washington D.C. the following weekend and had a fair amount of downtime in airports. I had just started my Claude subscription and I wondered if it could help me build a model to project the impact of the closure on the petrochemical supply chain and its products if the closure went longer than expected. I did the research, and it helped me build, test, and validate a Monte Carlo simulation. We discussed what we learned from the model in our article "What the Public Discussion on Hormuz Is Still Getting Wrong."

We are now eight months into this and the Strait is still not free for passage. I have listened to many podcasts, watched many YouTube videos, and read many articles. I was surprised by several developments as the crisis played out. So I thought it was a good time to see what we got right and what we can learn for the future.

The model got a lot right. The physical cascade sequence was pretty accurate: naphtha and LPG first, petrochemicals next, fertilizers following, and finished goods last. The geographic impact assumptions were also on target: Asia felt the effects early, followed by Europe, with the U.S. experiencing a later impact on diesel. The argument that a diplomatic deal wouldn't immediately fix the shortage has also played out, and unfortunately continues to be accurate. If you want the full report card, it's at the end of this piece.

But the two biggest misses in the model were not data problems. They were structural blind spots. And they point to the same root cause.

“We modeled how the system would respond to the shock. We didn't model how every actor in the system would refuse to accept the outcome the model predicted.”

On the supply side, the adaptation was more creative and more persistent than any reasonable pre-crisis forecast would have assumed. On the conflict side, the escalation was more strategically sophisticated than a standard military disruption model would have captured. Both failures came from the same assumption: that actors in the system would respond to the disruption rather than actively reshape it.

That assumption was wrong. And understanding why it was wrong is more valuable than any individual forecast the model produced.

The model got the physical story right.

The supply chain cascade the model predicted has unfolded largely as projected. Naphtha shortage signals appeared around Day 20. Urea prices are up 49% year-over-year. Anhydrous ammonia is up 43% (DTN). The World Bank has fertilizer prices 60% above the 2025 baseline. The crop cycle lag means the food price impact is still building toward a Q1 2027 peak.

The geographic sequence held: Asia crude imports fell first and most sharply, California refined products dropped below the five-year range on gasoline, diesel, and jet fuel simultaneously, and Europe felt the jet fuel impact third. Aramco's CEO has put the cumulative supply loss at nearly three billion barrels, with inventory rebuilding likely taking up to two years.

The model also called the most counterintuitive point correctly: the reopening date, whenever it comes, will be largely irrelevant to shortage timing. Supply chains don't recover on the day a diplomatic deal is signed. That argument has been validated repeatedly, most recently by September's partial recovery, which reversed completely within days once October's attack surge resumed.

Getting the physical story right matters. It gave organizations a framework for prioritization and response. The more important lesson is what the model didn't see.

The supply chain was more resilient than we modeled. The actors kept finding new levers.

The model assumed that supply chain participants would respond to the disruption within the bounds of existing infrastructure, capacity, and risk tolerance. That assumption underestimated human ingenuity at scale under pressure.

The shadow fleet scaled faster than anyone projected. Between 2,500 and 3,000 vessels now operate without standard tracking, insurance, or port-state oversight. These vessels account for an estimated 50-80% of remaining Hormuz transits. This fleet didn't exist at that scale before the crisis. It was assembled, financed, and operationalized in real time as an adaptive response to the closure, and it materially offset the disruption the model predicted.

Alternative routing absorbed more volume than design capacity suggested was possible. The Cape of Good Hope route adds 10-14 days and significant cost. The UAE's Habshan-Fujairah pipeline has a nominal capacity of 3.5 million barrels per day. Both absorbed volume at levels that exceeded pre-crisis utilization assumptions, because the economic pressure to move cargo was high enough to fund operational workarounds that weren't worth doing before.

Insurance markets restructured rather than retreating. War-risk insurance premiums hit approximately 40 times pre-crisis levels in September. Conventional logic said commercial shipping would exit the corridor at that price. Instead, new underwriters entered, risk-sharing structures were created, and state-backed coverage programs emerged in several countries. The market adapted rather than collapsed.

China's SPR management suppressed apparent demand for months. China cut visible commercial imports by approximately 32% while drawing down Strategic Petroleum Reserve stocks, effectively hiding true industrial demand from global markets and delaying visible shortage signals that would have triggered a more aggressive response earlier. The SPR functioned as a demand-management tool, not a passive reserve.

The cumulative effect was a supply chain that held longer and absorbed more disruption than the model predicted. This is genuinely good news. It tells us that supply chain systems have more embedded resilience than static models capture, and that actors under pressure will find innovative solutions that weren't obvious before the pressure existed.

“The supply chain didn't break because the actors in it kept finding new levers. The question at Day 240 is whether those levers are running out.”

The shadow fleet is operating near capacity. Cape routing adds cost that eventually prices some cargoes out of the market entirely. The UAE pipeline is at or near its design limit. China's SPR drawdown cannot continue indefinitely without compromising strategic reserve purposes. The resilience mechanisms that absorbed the first eight months of this crisis were largely one-time structural adaptations. Whether there are comparable second-round adaptations available is the open question.

The conflict was more sophisticated than we modeled. The other side kept innovating too.

The supply-side resilience story has a mirror image. The model also underestimated the strategic sophistication of the actors driving the disruption.

A standard military disruption model treats conflict as a source of noise: random events that reduce flow below capacity by some percentage. What actually happened was more purposeful than that.

The October attack pattern was not random. In September, Gulf oil flows (excluding Iran) recovered to more than 81% of pre-war levels on the best days. Middle East crude exports exceeded pre-war levels on 14 days in September (Kpler). Markets began pricing in normalization. Polymarket odds for normal traffic by year-end moved upward.

Then, in the week of September 28, ten tankers were struck. Fifteen more were struck during the week of October 6–14, followed by eleven more in just four days. Flows crashed from 20.8 million barrels per day on October 8 to 2.9 million barrels per day on October 11, an 86% drop in 72 hours.

The targeting was calibrated to the recovery. The actors on the conflict side were watching the same flow data everyone else was watching, and they intervened at precisely the moment when markets were beginning to normalize.

The prohibited zone declaration followed the same logic. On September 6, Iran's Security Council head declared a prohibited zone around the strait. That declaration came as alternative routing and shadow fleet operations were demonstrating that commercial flow could be maintained at partial levels. The declaration was a second-order response to the supply-side resilience – an escalation designed to offset adaptation.

The result is a system in which supply-side actors innovate to restore flow, conflict-side actors innovate to disrupt it, and the equilibrium keeps resetting at a level of sustained disruption rather than trending toward resolution.

“Both sides kept finding new levers. The crisis is not winding down, it is evolving.”

This is what complex adaptive systems actually look like.

The model's structural assumption that actors respond to disruption rather than reshape it is the standard assumption in supply chain risk modeling. It is also the assumption that fails most dramatically in prolonged, high-stakes disruptions.

A complex adaptive system is one where every actor's response updates the environment that other actors are responding to. The supply chain's shadow fleet expansion changed the flow data the conflict side was targeting. The conflict side's October attacks changed the insurance market's risk calculus. The insurance market's restructuring changed what cargoes could move. Every adaptation triggered a counter-adaptation.

Philip Tetlock's work on expert forecasting describes this as the difference between systems that are complicated and systems that are complex. Complicated systems have many parts, but those parts behave predictably. Complex systems have actors who learn, adapt, and strategically respond to what they observe. Predicting complicated systems is hard but possible. Predicting complex systems requires a different framework entirely, one that models the adaptation process, not just the initial shock.

Goldman Sachs has described the current state as “de-Straitization,” a structural adaptation where 70% of normal flow functions as the new baseline. That view captures the supply-side resilience story. What it underweights is the conflict side's demonstrated willingness to prevent that baseline from stabilizing. The October data suggests we are not yet at a new equilibrium. We are in a dynamic contest between actors innovating on resilience and actors innovating on disruption.

That contest is not something any static model can resolve. But talking about it clearly is the first step toward building planning frameworks that account for it.
 

Accompanying Figure: Day 240 Report Card

How the original predictions have held up, including the two structural misses the model didn't anticipate.
View report card image (JPEG) | View accessible report card (HTML)
 

What supply chain leaders should be asking right now.

Day 240. Brent crude at $114.64. War-risk insurance at approximately 32 times pre-crisis levels. Crisis pressure index at 88. This is extreme. The October attacks have pushed flows back toward crisis lows after a September that briefly looked like the beginning of normalization.

The supply-side resilience that absorbed the first eight months was real and impressive. The shadow fleet, alternative routing, restructured insurance markets, and Chinese SPR management all exceeded what a pre-crisis model would have projected. The actors in the supply chain system found more levers than we gave them credit for.

But there are real limits to how far that innovation can go. The one-time structural adaptations are largely in place. The incremental gains from here are smaller and more expensive. And the conflict-side actors have demonstrated they are watching for normalization signals and will respond to them.

The strategic question for your organization is not “when does this end?” It is: what does your supply chain look like if the dynamic contest between supply-side resilience and conflict-side escalation continues for another six months? Another year? What is your plan if the levers your supply partners have been pulling start running out?

Stop planning for a reopening date. Start mapping your exposure to the second stage of this crisis: the stage where the one-time adaptations are exhausted and the underlying disruption is still in place.

The model wasn't wrong about the physical cascade. It was wrong about the nature of the system it was modeling. Eight months of data make that correction possible. The correction that matters now is building planning frameworks that treat supply chain disruption not as a shock to absorb, but as a dynamic contest to monitor.

Both sides kept innovating. That's the lesson. The question is who runs out of ideas first.

About the author.

Chris Gaffney is Managing Director, Georgia Tech Supply Chain and Logistics Institute (SCL) and Edenfield Executive-in-Residence within the H. Milton Stewart School of Industrial and Systems Engineering.

The Hormuz simulation described in this piece was developed by the SCL research team in early 2026. Data sources: IEA, EIA, Kpler, Vortexa, DTN, World Bank, IMF PortWatch, and open-source shipping intelligence. Questions and feedback: jgaffney6@gatech.edu.

Launched in fall 2026, the Martinson Faculty Fellows Program draws on the expertise of faculty across the Institute. Their fields span engineering, the natural and social sciences, sustainability, experiential education, student success, and institutional research. The shared goal is to help Honors Program students think across disciplinary boundaries, build meaningful relationships with faculty, and connect what they learn to challenges beyond the classroom.

Each Fellow brings a distinct perspective, from sustainable construction materials and evidence-based science teaching to inclusive engineering education, public history, community-based learning, and student resilience. Together, the cohort represents a wide range of academic fields and campus units. Their range of experiences is part of the program's design. By bringing educators with different approaches into one learning community, the Fellows initiative creates opportunities to exchange teaching ideas and develop mentoring practices that respond to students' varied interests and goals.  According to Faculty Director Amy D'Unger, 

One of the things that distinguishes this cohort is not only the breadth of expertise the Fellows bring, but their shared interest in creating learning experiences that reach beyond traditional disciplinary boundaries. I’m especially excited about what can happen when these faculty learn alongside one another and then bring that exchange of ideas to our students, helping students connect their Georgia Tech education to questions of purpose, progress, and service.

The Fellows also have a direct role in the Honors Program's implementation of the Leaders in Progress and Service graduation distinction. The initiative invites students to reflect on their values and consider how their knowledge and experiences can help address complex challenges and contribute to their communities.  Under a two-semester rotating model, Fellows spend one semester teaching Honors Program sections of GT 2030: Progress and Service Forum and another mentoring students pursuing immersive learning experiences. The foundational course encourages students to consider complex issues from multiple perspectives while developing a clearer sense of their own professional values, identity, and responsibilities.  

For students admitted to the Honors Program in summer 2026 or later, the new curriculum includes this three-credit foundational course. Students who earn a B or higher can then advance to immersive learning experiences. These may include undergraduate research, entrepreneurship, internships and co-ops, study or work abroad, campus leadership, sustained community service, etc.  The experiences themselves can vary widely. One student might investigate a technical problem with a research team; another might work with a community organization or explore how an internship informs future career choices. What connects the experiences is the opportunity to learn through doing, with faculty guidance that helps students consider not only what they accomplished but also why it matters.

Faculty mentorship from the Fellows is intended to make those connections more intentional. Through conversation and guided reflection, Fellows can help students link their activities to academic interests, personal growth, and the broader responsibilities of leadership and service. The relationships may also introduce students to faculty perspectives outside their major or intended career path. Executive Director David Torello expresses his vision for the program this way.

My hope for the Honors Program is that every student leaves Georgia Tech with a strong sense of purpose, meaningful relationships with faculty, and the confidence to use their talents in service to others. The Martinson Faculty Fellows help bring that vision to life by connecting students with educators from across the Institute who can help them make thoughtful choices about their learning and connect their academic experiences to their values, aspirations, and the communities they hope to serve. To me, those connections are at the heart of an Honors experience that prepares students for meaningful lives as well as successful careers.

The program invests in the Fellows as well as in students. Its collaborative professional-development component gives participants space to share evidence-based teaching strategies, examine high-impact educational practices, and learn from colleagues whose work takes place in different corners of Georgia Tech. That exchange can influence courses, mentorship, and future interdisciplinary partnerships.

Organizers also envision impact beyond the first year. Longer-term possibilities include a Faculty Advisory Council, an ongoing Faculty Learning Community, and opportunities for experienced Fellows to mentor new cohorts or help build additional immersive-learning pathways and community partnerships. Those elements remain aspirations as the inaugural cohort gets underway.

As the Honors Program marks the 20th anniversary of its first student cohort, the Martinson Faculty Fellows Program offers a people-centered investment in its future: more connections between students and educators, more ways to learn across disciplines, and more opportunities to turn knowledge into purposeful action.

2026–27 Martinson Faculty Fellows

• Antonia Antoniou — George W. Woodruff School of Mechanical Engineering
• Sarah Brackmann — Office of Undergraduate Education and Student Success, Experiential and Engaged Learning
• Kemal Budak — School of History and Sociology
• Kelly Cross — Wallace H. Coulter Department of Biomedical Engineering
• Ebenezer Fanijo — School of Building Construction
• Jonathan Gaines — George W. Woodruff School of Mechanical Engineering
• Edwin Greco — School of Physics
• Kelly Griendling — College of Engineering
• Christopher Lawton — School of History and Sociology
• Pamela Pollet — School of Chemistry and Biochemistry
• Christie Stewart — School of Biological Sciences
• Jason Wang — Office of Institutional Research and Planning

Alexandra Rodríguez Dalmau, a community-engaged sustainability project manager with SCoRE, focuses on ensuring that communities have a meaningful role in shaping emerging energy transition technologies (EETTs) from the earliest stages of research through design and deployment. Her work sits at the intersection of research and practice, connecting technical expertise with community priorities related to energy, climate, and sustainability.

"Our main objective is to create a platform and process based on trust, where communities and technical experts can learn from one another," Rodríguez Dalmau said. "The goal is not to convince communities to support a particular technology, but rather to help everyone better understand the opportunities, tradeoffs, impacts, and questions that come with these technologies."

One of these projects is a regional community engagement program connected to the Southeast Direct Air Capture Hub (SEDAC), a U.S. Department of Energy-funded initiative led by the Southern States Energy Board. As conversations unfolded around direct air capture, a technology that removes carbon dioxide directly from the atmosphere, it became clear that many of the same questions and concerns can apply to the broader set of EETTs. Scaling low-carbon energy sources and systems that manage carbon after energy is produced — like hydrogen production, renewable energy systems, battery technologies, and energy infrastructure upgrades — may be considered an unqualified good thing. The SEDAC program brought to light that communities where such projects are built have a different perspective.

In the Fall of 2025, that SEDAC platform grew into the Southeast Community Energy Futures Academy (SCEFA), a training program and community of practice that brings together communities, technology researchers, and project developers to explore both the promises and challenges of EETTs.

"Communities are often asked to host facilities or infrastructure projects that serve broader resilience or climate goals," Rodríguez Dalmau said. "The benefits can feel distant while the risks and disruptions are immediate and local. Engaging communities early in the process is critical to ensuring that EETTs align with local priorities and support communities' own visions for a sustainable future."

Rather than positioning researchers as the sole experts, the program facilitates collaborative learning and centers the knowledge of community partners as experts who possess deep understanding of local history, priorities, and concerns. Participants engage in presentations, working sessions, mapping exercises, and laboratory tours. But one of the most significant elements of the program takes place outside of these sessions.

Community site visits bring participants directly into industrial and research facilities as well as neighborhoods affected by existing industrial development. Participants see schools, residential areas, power plants, natural amenities, research facilities, and community gathering spaces and hear from site managers and community leaders.

"Engaging with communities through experiential learning activities like site visits begins the process of rooting abstract technology into a place with all its history and memories of previous encounters with industrial plants. This enables conversations instead of silence or skepticism,” says Matthew Realff, professor and David I.J. Wang Faculty Fellow in the School of Chemical and Biomolecular Engineering, and faculty director for Interdisciplinary Sustainability Education at the Brook Byers Institute for Sustainable Systems.

The SCEFA effort is a culmination of SCoRE’s relationship and project-building work over the past 11 years. Community partners who participated in the SEDAC Hub and SCEFA discussions have become key contributors to a broader regional effort that now encompasses teams from Georgia, Alabama, Mississippi, and Louisiana. The initiative brings together leaders of nonprofits and community-based organizations, researchers, student interns, and project developers to learn from each other and develop education and outreach materials related to EETTs.

Over the course of one year, participants engaged in multiple online workshops, two in-person workshops — in Baton Rouge, Louisiana, hosted by Louisiana State University, and in Mobile, Alabama, hosted by the University of South Alabama — and developed education and outreach materials to be used by community-based organizations.

The program also encourages the formation of what SCoRE describes as "unlikely coalitions" among community organizations, universities, and industry professionals. The Georgia team, spearheaded by a researcher at Georgia College and State University, is exploring how nature-based sequestration and biomass energy may be used to enhance the land and other natural amenities that residents in their rural communities see as their legacy. The Alabama team focused on carbon capture, utilization, and storage (CCUS), which is the key EETT focus in their geography. The lead organization for that team, Iyai+ (Introducing Youth to American Infrastructure), developed a role-playing game that helps participants explore the opportunities and challenges associated with CCUS, identify key stakeholders, and practice asking critical questions about proposed projects.

Jennifer Hirsch, senior director of SCoRE, who is a cultural anthropologist and serves as project lead, explained, “SCEFA prioritizes building relationships over time, with a core focus on experiencing and learning together, rather than trying to get one side to see the other’s point of view. It is only when community perspectives are taken into account that truly innovative solutions will emerge that benefit both people and climate.”

The emphasis is on process rather than predetermined outcomes. Participants spend time learning how to ask better questions, evaluate evidence, and recognize uncertainties. By investing in a shared process, participants are often better able to navigate disagreement without becoming defensive.

The approach is already producing results. Technologists involved in the program have expressed greater interest in engaging with communities earlier in their research and development process. Researchers are exploring new ways to communicate findings more clearly and transparently. Community partners are gaining knowledge, tools, and resources that allow them to engage on their own terms when new projects are proposed.

“Lasting solutions emerge when researchers and communities work together from the beginning, asking the right questions and considering both the opportunities and tradeoffs,” said Tim Lieuwen, executive vice president for Research. “SCEFA offers a powerful model for developing energy solutions with communities, not simply for them. This collaborative approach reflects how Georgia Tech can help address complex challenges that no institution or community can solve alone.”

After operating in stealth mode over the past year, North Star AI Labs is now open to founders, startups, and creators seeking to build and scale AI-driven solutions. The initiative addresses a growing gap in the innovation ecosystem, where many entrepreneurs lack access to the infrastructure, expertise, and resources needed to effectively adopt AI.

“Most AI labs are not accessible to startups,” said James Harris, entrepreneur in residence at ATDC and founder of North Star AI Labs. “If you’re a small business, you can’t just walk into a university lab and start building. North Star AI Labs was created to remove that barrier and give entrepreneurs a place where they can access tools, connect with talent, and actually build.”

North Star AI Labs provides entrepreneurs with multiple pathways to engage, including hands-on programming and events, collaborative coworking opportunities, and a project-based talent matching platform that connects founders with AI engineers and students. Participants also gain access to ATDC’s broader network of startup founders and industry experts, creating an environment designed to accelerate innovation and reduce time to market.

The initiative is supported by a growing group of partners and sponsors, including Hartmann Studios, which serves as the founding sponsor of North Star AI Labs.

“At Hartmann Studios, we see AI becoming the delivery layer for how work gets done, and North Star AI Labs at ATDC is helping make that shift accessible to builders and founders across Georgia,” said Scott Lowry, vice president of Hartmann Studios. “What stood out to us is the focus on real tools, real talent, and real application, not theory. This kind of ecosystem is critical right now as companies and entrepreneurs alike need credible, hands-on ways to adopt AI responsibly and at speed.”

North Star AI Labs has already begun demonstrating early momentum, with hundreds of participants engaging in programming and events, and new startups emerging from the community. Founders are leveraging the space not only to build products but to form critical relationships with engineers, collaborators, and investors.

“Being part of the North Star AI Labs community has been crucial for StorySense, giving us access to the expertise we need at the right time,” said David Turner, founder of the startup, StorySense. “AI is moving so quickly that no team can keep up in isolation. North Star AI Labs provides the feedback loops, shared learning, and support founders need to build and move faster.”

In addition to supporting founders, North Star AI Labs is helping bridge the gap between startups and emerging AI talent. The initiative hosts organizations such as the Georgia Tech AI Club and collaborates with student groups across the region, creating opportunities for students to gain real-world experience while supporting startup growth.

“In an AI-driven economy, access to AI talent is a core necessity. North Star AI Labs equips Georgia’s startups with these vital tools and expertise, powerfully scaling ATDC’s mission to support founders at every stage,” said John Avery, director of ATDC. “At ATDC, our mission is to support founders at every stage, and this initiative expands that support in a way that is both practical and scalable.”

With the public launch of North Star AI Labs, ATDC continues to strengthen its role as a catalyst for innovation across Georgia, ensuring that entrepreneurs have the resources and support needed to compete in an increasingly AI-driven economy.

The organization, led by Georgia Tech Professor Tibor Besedeš, has organized 92 conferences in eleven countries over its 32 years of existence. Economists from 400 institutions have presented approximately 1,300 papers at FREIT events.

“The roughly 850 economists who have presented or discussed a paper at a FREIT conference are not only trade economists in the narrow sense. They referee our papers, sit on editorial boards, write outside letters for our promotion cases, serve on grant panels, and advise the students we would like to recruit. Their sense of where Georgia Tech sits among economics departments is formed largely by incidental exposure, and there is now a good deal more of it,” Besedeš said.

For instance, the move means Georgia Tech will be named as the coordinating institution at FREIT’s upcoming conferences in Melbourne, Australia; Astana, Kazakhstan; Sardinia, Italy; Bloomington, Indiana; Seoul, Korea; and Tokyo.

FREIT, founded in 1994 at Purdue University, also holds a best graduate student paper competition every year at two of its conferences, the U.S.-based Empirical Investigations in International Trade and the Sardinian Empirical Trade Conference.

Past winners have come from Oxford, the Massachusetts Institute of Technology, Yale, Maryland, Brown, NYU, and Vanderbilt, among others. Many are now faculty presenting at the same conferences, Besedeš said.

“For me, the work is administrative rather than glamorous — coordinating seven conferences a year, maintaining the website, running the mailing list, and keeping the submission process working,” he said. “The compensation is that I see every paper submitted to every FREIT conference, which is a reasonable vantage point from which to watch a field. I get to see what the new ideas are, who are the new people entering the field, and I play a small role in helping shape both.”

For more information about FREIT, visit the organization’s website.

Driving Logistics and Operational Excellence

Selected from a highly competitive pool of applicants across Georgia Tech, Guy Mastrion stands out for his technical rigor, systems-level thinking, and track record of optimizing complex production logistics in mission-critical manufacturing environments.

A Dean's List student, Zell Miller Scholar, Ty Cobb Educational Foundation Scholar, and Eagle Scout, Mastrion has demonstrated academic excellence alongside his professional accomplishments. Through his engineering internships, he has applied software development, data analytics, and automation to improve manufacturing efficiency and solve complex operational challenges.

Engineering Innovation at SpaceX and General Motors

Mastrion's industry contributions demonstrate an extraordinary ability to translate logistics theory into measurable, high-impact operational gains:

• SpaceX, Starbase, Texas, and Cape Canaveral, Florida: At SpaceX's Cape Canaveral operations in fall 2025, he helped build a labor visibility platform for Starship thermal hardware production. His work included technician interfaces, production-floor kiosks, and dashboards providing insight into work in progress, maintenance, workforce activity, and other operational metrics.

  During a subsequent SpaceX internship at Starbase, Texas, in summer 2026, he developed a weld-inspection application that reduced inspection time from 105 seconds to 15 seconds per weld, with an estimated 876 hours saved annually. He also worked on purchasing automation, material readiness, and production workflow improvements.

• General Motors, Flint, Michigan: Mastrion developed automation to analyze production and quality data. The work was associated with an estimated increase of 817 trucks per year and an estimated $18.6 million in annual profit improvement.

  He also developed a broader digitization roadmap with projected annual benefits of up to $127 million if scaled across additional General Motors manufacturing facilities.

Leadership and Technical Innovation

Beyond his internships, Mastrion has explored the use of artificial intelligence in engineering workflows, including a regulatory-compliance application designed to check engineering drawings and records against applicable requirements. He has also served as an Autodesk Design & Make Student Ambassador and participated in the Georgia Tech–Boeing Forming Leaders in Technology mentorship program.

His work reflects the intersection of industrial engineering, technology, and operations that is central to modern supply chains, from manufacturing data visibility to material availability and throughput.

Celebrating the Future of Logistics

The Matson Supply Chain Scholarship for Emerging Leaders reflects a deep investment in emerging leaders who will shape the future of global supply chains and advanced logistics systems. Guy Mastrion’s proven capacity to streamline complex networks makes him a deserving recipient of the 2026–2027 award.

Please join the Georgia Tech Supply Chain and Logistics Institute in congratulating Guy on this prestigious honor as he continues to drive innovation in supply chain systems, aerospace logistics, and advanced manufacturing.

About Matson

Matson is a U.S.-owned and operated provider of ocean transportation and logistics services with a longstanding commitment to the communities where it does business. Through its charitable giving program, Matson supports nonprofit organizations and initiatives focused on education, environmental stewardship, human services, arts and culture, and civic and community needs.

About the Matson Foundation and Scholarship

Since 2021, the Matson Foundation has offered this annual scholarship through Georgia Tech to encourage and support full-time undergraduate students preparing for careers in transportation, supply chain management, and logistics. The $5,000 award is open to eligible students in Industrial and Systems Engineering and/or Business with a supply chain emphasis, recognizing emerging leaders with strong academic standing and demonstrated interest in these fields.

For further information about the Matson Supply Chain Scholarship for Emerging Leaders and student programs, please contact the Georgia Tech Supply Chain and Logistics Institute.

What happens when the expected outcome has an unexpected result? 

The award recognizes their paper, “Convolutional Non-Homogeneous Poisson Process and its Application to Wildfire Ignition Risk Quantification for Power Delivery Networks,” published in Technometrics. Their research advances methods for assessing wildfire ignition risk in power delivery networks, demonstrating the real-world impact of statistical innovation.

Presented annually by the American Statistical Association and the American Society for Quality, the Frank Wilcoxon Prize honors the best practical application paper published in Technometrics.

The award was presented at the 2026 Fall Technical Conference in Charlotte, North Carolina.

Ten Georgia Tech ventures showcased emerging technologies and connected with investors at the Georgia Tech Silicon Valley RoadShow on Sept. 24 in Palo Alto, California. 

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“Progress rarely happens in isolation,” said Eric Vogel, executive director of IMS. “You need to interact with people with different experiences and capabilities, share ideas, make an introduction and challenge an assumption.”

 Vogel encouraged attendees to exchange ideas, make new connections, and identify opportunities to collaborate.

Billyde Brown, external user outreach manager and senior research engineer at IMS, organized the event around three goals: celebrating founders, connecting them with innovation partners, and strengthening support for hard-tech startups in Atlanta.

“Founders Night is about bringing all of these players together so we can network, collaborate, and make connections,” said Brown.

Two Georgia Tech founders illustrated how research can lead to commercial applications. Mark Prausnitz, Regents’ Professor, Regents’ Entrepreneur, and J. Erskine Love Jr. Chair in Chemical and Biomolecular Engineering, discussed how his laboratory’s microneedle research has supported companies developing technologies for drug delivery, eye care, and dermatology. Harry Watkins, co-founder and president of Stellar Scale Nano Fabrication, described how the Georgia Tech spinout is commercializing a faster nanoscale 3D-printing platform. 

“We want to support and enable founders by connecting them with local innovation ecosystem partners who can provide critical resources, facilities and other assistance,” said Brown.

The event highlighted local resources available through the Metro Atlanta Chamber, Georgia Research Alliance, and Kicker Labs, as well as manufacturing pathways offered by LioniX International and Silex Microsystems. Together, these organizations offer support ranging from funding and product development assistance to site selection and commercial manufacturing.

The evening concluded with tours of IMS’s Materials Characterization Facility, Micro/Nano Fabrication Cleanroom, followed by a networking reception.

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.”

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.

Read the full story.

The trend is raising concern about how well prepared ChatGPT, Claude, Gemini, and other popular LLMs are to provide appropriate emotional support.

To address this concern, Georgia Tech researchers have developed a new neural framework that examines how different training sources influence empathy and social reasoning within these AI-powered models.

“A lot of people are using LLMs to help process the death of a loved one, or maybe their girlfriend broke up with them, or their boyfriend cheated on them,” said Glenn Matlin, a Ph.D. student in the School of Interactive Computing.

Matlin said the new framework he and a Georgia Tech-led research team have developed audits neural networks with an LLM and estimates the influence documents, transcripts, and other data sources have on a model’s output.

“We’re trying to connect the data to outputs, which is helpful for us in understanding where the information a language model produces comes from,” he said.

Matlin is the lead author of a new paper examining model sourcing for social reasoning and how models mimic human behavior in conversations. The paper will be presented this week at the Conference on Language Modeling in San Francisco.

Matlin said the findings suggest that an objective tone in its output indicates that a model places greater importance on textbooks or similar neutral training sources. An empathetic tone suggests the model values sources with dialogue and conversational examples more.

“We find that models tend to learn better from interpersonal dialogue when it comes to social reasoning,” he said. “Models that are good at social reasoning will rely less on textbooks about human emotions and more on FAQs or customer service dialogue.

“It can read all it wants from texts that explain anger, but that wouldn’t help it determine whether someone is angry.”

Professor Mark Riedl, Matlin’s advisor, said that knowing which sources models value most could enable engineers to alter their behavior.

“The question is, in this vast ocean of documents in this neural network, which ones become important in certain situations, and which ones don’t,” Riedl said. 

“This leads to the potential for interventions in how we train the model. If we want more empathy, we might look to see where it learns empathy and give it more of those documents, fewer of them, or other documents.”

Riedl said the framework can audit an LLM’s sourcing for advice on any topic, from financial to medical.

“We want to help people make more informed decisions about whether they should use AI for a particular task,” he said.

“You might make a different decision about whether to trust the AI’s recommendation if you knew how a skill was learned and which documents influenced that decision. The first step is knowing how it learns, where it learns from, and what documents tend to lead to certain behaviors.”

The findings that Matlin, Riedl, and their collaborators have made so far came through a partnership with the Allen AI Institute (Ai2), which allowed them to audit their open-sourced LLM, Olmo 3.

While not as large as ChatGPT or Claude, Olmo 3’s training data comprises over a billion documents.

Matilin said it’s impossible to know why ChatGPT or Claude behave in certain ways because their parent companies do not disclose their training data. However, Matlin’s study may help researchers to make better guesses about what’s happening behind the scenes.

He added that the study is the first of its kind and scale on an academic level.

“This is the first one that’s ever been done for an open data model of that type,” he said. “We’re providing a view into neural networks that is hard to come by without being in the corporate setting.”

Ashley Ni first came to BridgeUP STEM as a high school student, joining in the 2024-2025 academic year. Now she is a computer science student, returning to the program as a Helen Fellow and serving as the first BridgeUP STEM participant to experience the program as both a scholar and a fellow. 

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. 

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. 

However, a new paper by a Georgia Tech-led research team suggests that the requirements can disproportionately burden family farms and other small food producers due to a lack of technological infrastructure, resources, or compliance expertise.

The rule is mandated by Section 204(d) of the Food Safety Modernization Act, which Congress passed and President Barack Obama signed into law in 2011. Intended to help the FDA quickly identify the source of contamination, the rule requires producers or distributors with more than $25,000 in annual produce sales to comply or face significant fines. 

Earlier this year, the FDA extended its compliance deadline to July 2028. One reason for the extension may be the volume of feedback from stakeholders affected by the rule. The FDA received more than 1,200 comments during an open forum, with feedback from stakeholders ranging from major distributors to small farmers. 

“Many small farmers commented on how they may not have the devices needed to input this data,” said Soonho Kwon, a Ph.D. student in Georgia Tech’s School of Interactive Computing (SIC) and lead author of the paper. “Does this mean they have to purchase it themselves? Do they need to become educated on how to use computing systems?”

Kwon is a member of the Equity and Sustainability in Computing Lab, which is led by SIC professor and chair Shaowen Bardzell.

Many small farms also said they can’t afford to hire someone to track the data.

One small farmer said the amount of data tracking required by the rule is overwhelming. Some of the required data include:

• location and name of the field where food was harvested
• date of harvest
• packing dates
• shipping dates

“Please do not force us to do technology stuff,” the commenter said. “It’s hard enough to keep up with the local demand as it is. We run a pretty low digital technology effort. It’s basically harvest fresh organically grown veggies and sell them to local people.”

Kwon said the intention of the Food Traceability Rule is admirable.

“Preventing foodborne illness is critical, and data- and technology-driven governance can be a powerful tool toward that goal,” he said. “But it’s equally important to think critically about who is supposed to be the default user of these systems, and who gets missed in the process. It’s undermining the people who are unable to comply.”

Other factors didn’t appear to be considered by the FDA, including the lack of technological infrastructure in rural America, where many foods are grown.

“Many parts of rural America have limited or unreliable internet access,” Kwon said. “If the FDA wants them to send this data, they must comply within 24 hours. Does that mean they have to stop their daily routine and drive to a city that has internet to send it? The rule is operating on the assumption that everyone is dealing with the same physical environment.”

Culture and religion also seem overlooked. Some commenters raised concerns that Amish farmers who avoid certain technologies for religious reasons would be pressured into digital record keeping.

Many major distributors and organizations expressed support for the Food Traceability Rule in the FDA’s forum. Catherine Wieczorek, a Ph.D. student in SIC and co-author on the paper, said these organizations don’t have the same tension points as smaller producers.

“Larger food producers have the operational capacity to do the type of work the rule requires,” Wieczorek said. “We find there’s a power imbalance when it comes to smaller food producers like a family farm. Change at that scale is difficult for smaller producers.”

Bardzell, who advises Kwon and Wieczorek, said the situation provides computing researchers an opportunity to create interventions that will benefit those with fewer resources.

“In a data age when we’re adding AI into our work processes and labor practices, we need to think about how this need creates unequal burdens on different stakeholders in our food system,” Bardzell said. “It’s a significant challenge for computing going forward.”

Kwon will present the paper on behalf of his collaborators next week at the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) in Salt Lake City, Utah. Their research is supported by the National Science Foundation.

Duran spent nearly four months interning at Apple’s headquarters in Cupertino, California. His work during the internship focused on Apple’s Foundation Models, a series of generative AI models that power Apple Intelligence, and on the large-scale infrastructure and tooling around them.  

Duran’s research interests lie at the intersection of computer architecture, systems, and machine learning. More recently, he has focused on making artificial intelligence (AI) workloads more accessible, sustainable, and cost-effective. Duran is co-advised by Associate Professor Yingyan (Celine) Lin and Assistant Professor Anand Iyer in the School of Computer Science.  

Duran said he saw the internship as an opportunity to gain industry experience and apply his knowledge to real-world problems.  

“Industry research is particularly exciting to me because you can work on challenging problems while also seeing how these ideas can translate into systems and products at a very large scale and impact nearly a billion lives,” he said.  

As a research intern, Duran especially appreciated the level of independence he was given. He was expected to take initiative to find problems on his own and then develop solutions with his mentors. Although Duran liked taking ownership of his work, he also came to better understand the value of outside input.  

“One thing I’m continuing to improve is recognizing when it’s more efficient to ask for input earlier rather than spending too much time trying to solve everything independently,” he said. 

Duran said he enjoyed the internship, especially the people he met. However, the biggest highlight for him was presenting his work.  

“I had the opportunity to present several times, including to larger audiences across different organizations, and I really enjoyed discussing the findings and getting feedback from people with different perspectives,” he said.  

In addition to the technical knowledge he gained, Duran said the experience gave him a new perspective on how research and engineering work in industry.  

“I realized that combining strong research with real business needs can often create much greater impact than research alone,” he said. 

“I really enjoyed seeing my work translate into something with broader, tangible impact, and that has influenced the kind of work I want to pursue in the future.”  

The kitchen serves students in need with groceries or meals, works to reduce food waste on campus, and is part of Students’ Temporary Assistance and Resources (STAR) Services.

“The STAR Office is so grateful to the School of Cybersecurity and Privacy for sponsoring a food drive this semester,” said STAR Program Director Steven Fazenbaker. “Your successful campaign has put us in a position to serve over 300 students by keeping Klemis Kitchen fully stocked with our most popular shelf-stable food items for the rest of the fall semester.”

 “It also allows us to get a head start restocking Klemis Kitchen during the winter break, so we will be ready when the spring semester begins. Thank you so much for your over-the-top generosity.”

The school exceeded its goal by $1,600 and surpassed last year’s donation of $2,110. 

Director of Research Operations Mary Helen Hayes organized the food drive and spent September fundraising. 

“While I organized and led the drive, its success came from the generosity and community spirit of our faculty and staff,” Hayes said. 

“Thank you to everyone who contributed and helped make it possible. SCP is proud to support such a meaningful cause, and we truly hope our contribution makes a difference for Klemis Kitchen and the students it serves.”

While SCP hosts this food drive once a year, Klemis Kitchen accepts donations year-round. 

Visit Klemis Kitchen to learn more about how you can help. The Kitchen relies 100% on donations, including leftovers from the dining halls, donations from community partners like grocery stores and churches, and food drives sponsored by departments across campus. 

Photos by John Popham/College of Computing

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:

• Training often misses the mark. Thirteen participants said that standard cybersecurity training was largely irrelevant to their shipboard duties, and 14 reported receiving no mission-specific cybersecurity training.
• Operational technology is often overlooked. Eighteen participants said their training did not distinguish between traditional information technology and operational technology, such as navigation and propulsion systems.
• Obvious failures are easier to recognize. Eighteen participants said they would primarily look for visible signs of operational problems when identifying a potential cyberattack.
• Cybersecurity is often a low priority. Seventeen participants described their cybersecurity training as absent, low quality, or a low priority.

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

Cognitive behavioral therapies require patients to practice skills between sessions. Clinicians rely on retrospective patient reports to understand what happens during that time.

However, recall bias, selective disclosure, and difficulty remembering can render those reports subjective, incomplete, or inaccurate.

Clinicians can now see sensor data on how patients’ bodies react in these situations thanks to a new technology toolkit from Georgia Tech and Emory University.

A new app that syncs with a FitBit wearable device can track and record heart rate, step count, noise level, and other sensor data when patients practice prolonged exposure homework assigned by their therapists.

A web dashboard lets clinicians review that data, add notes, and track patient progress. This information helps them structure therapy sessions more effectively and accelerate patient progress.

The toolkit is the culmination of a $1.2 million National Science Foundation grant awarded to Georgia Tech’s Rosa Arriaga and Emory’s Andrew Sherrill in 2019.

Arriaga is an associate professor at Tech’s School of Interactive Computing. Sherrill is an assistant professor in the Department of Psychiatry and Behavioral Sciences at the Emory School of Medicine.

Sherrill is also a practicing clinical psychologist at the Emory Healthcare Veterans Program and has worked with veterans with PTSD for more than a decade. 

Arriaga and the students in her Ubicomp Health and Wellness Lab spent five years developing the toolkit, which they call the Patient Engagement Computational Sensing System (PECSS).

“It was a lot of master’s students and undergrads who built the back end to the app and the dashboard,” Arriaga said. “It was a lot of work and effort by a lot of students to take an idea from conception to deployment.”

The researchers originally titled the toolkit the Prolonged Exposure Collecting Sensing System, but they changed the name after realizing it could be used for other types of therapy.

“The idea is that for any therapy that has a homework component, this can bridge the gap between patient self-reporting and clinician intuition,” Arriaga said.

Nathaniel Swinger, a Ph.D. student in Arriaga’s lab, co-led a paper on the study’s results along with Ph.D. student Myeonghan Ryu. Their paper received a best paper award at the 2026 ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). Best papers are given to less than 1% of the papers published at the conference.

“Our findings showed that the deployment was quite successful,” Swinger said. “Over 75% of the patients who incorporated PECSS into their treatment experienced a clinically significant change in symptoms. We don’t know if that’s causal, but there is some evidence the system worked to facilitate the process.”

Prolonged exposure is a method for systematically approaching trauma memories and reminders to make them safe and tolerable for patients. It is typically delivered in one-on-one therapy sessions.

Sherrill said the toolkit shows promise toward enhancing prolonged exposure therapy outside of clinical settings.

“Prolonged exposure has been researched more than any other therapy that exists,” Sherrill said. “We know it’s effective, but we’ve had problems for decades implementing it in the real world.

“There’s a need for technology in taking what patients learn in their sessions and having them replicate it outside of the clinic.”

Until now, the impact prolonged exposure on a patient with PTSD depends on the patient’s willingness to self-report the results of their homework.

“The number of potential triggers is an endless list,” Sherrill said. “We want people to approach them with their guard down and not to engage in avoidance or soothing behaviors.”

Sherrill said most of his patients have shown interest in continuing to use the toolkit — even after therapy is no longer needed.

“A system like this could reduce the frequency of sessions with a therapist,” Sherrill said. “We’re teaching patients to be their own therapists. This toolkit gives them a greater sense of independence.”

Given the promising results, Swinger said that ideally the next step would be a large-scale clinical trial.

“We’re looking to better test the causal clinical impacts of the system and a more generalizable notion of efficacy,” Swinger said. “We want to rigorously test it in a clinical setting for people beyond veterans with PTSD.”

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.

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.”

With the nod, Chang becomes one of just 180 poets named finalist for the prestigious prize since its reinstatement by the National Book Foundation in 1991.

“It's such an honor to have Tree of Knowledge selected as a finalist for the National Book Awards,” Chang said. “My book OBIT was longlisted in 2020 during the pandemic, so it will be nice to celebrate in person in New York with all the other finalists.”

Tree of Knowledge emerged from Chang’s contemplation of the felling of a tree across from her house in Los Angeles, where she was living at the time. It became, as Mother Jones said, “a meditation on abstract art, mortality, language, home, and history.”

“It spiraled out to me writing about trees in paintings that I was thinking about, and then to the expulsion of Chinese people from Eureka, California, in the 1800s,” Chang said. “I also included art that I made from historical photographs of Chinese people in Eureka, so the book threads the personal, the political, the historical, and the environmental.”

The book features not only Chang’s writing, but also her visual art. The collection incorporates original embroidered photo collages created by Chang using 19th-century archival images.

Chang holds a bachelor’s degree in East Asian Studies from the University of Michigan, a master’s degree in East Asian Studies from Harvard, an MBA from Stanford University and an MFA from Warren Wilson College.

Her previous collection of poetry, With My Back to the World, earned the prestigious Forward Prize for Best Collection, while her 2020 book OBIT received the Los Angeles Times Book Prize and the Anisfield-Wolf Book Award. OBIT was also named a finalist for the National Book Critics Circle Award and the Griffin International Poetry Prize.

She also is a Guggenheim Fellow and recipient of the Chowdhury International Prize in Literature.

In addition to her endowed chair, Chang teaches in the School of Literature, Media, and Communication and serves as the director of Poetry@Tech, leading one of the nation’s premier poetry centers and reading series. Through the work of Poetry@Tech, which is celebrating its 25th anniversary this year, Georgia Tech students across engineering, science, and the humanities learn the value of poetry as craft, literature, and personal expression.

Chang is the second Bourne Chair at Georgia Tech to be named a finalist for the prize. Her predecessor, Ilya Kaminsky, was named a finalist in 2019.

The winners will be announced Nov. 18 in New York.

To learn more about Nunn School Professor and Regents' Entrepreneur Kirk Bowman's work on the exhibit, watch a video of Bowman and National Center for Civil and Human Rights curator Daniel Fuller discussing the exhibit. You can also read more here.

Kirk Bowman, professor and Regents’ Entrepreneur in the Sam Nunn School of International Affairs, served as the sole academic consultant for "The People's Game: Soccer and Human Rights," an exhibit on display at Atlanta’s National Center for Civil and Human Rights through June 2027.

The exhibit tells the story of soccer programs and fans from around the world and how they have interacted for good, from Brazilian soccer players who served as a catalyst for democratic reform in Brazil to fans who rallied around Afghan women soccer players after the Taliban took over and disbanded the club to Atlanta’s own Soccer in the Streets — a non-profit that provides opportunities and mentorship to disadvantaged youth through soccer.

“As a college professor, this is a dream come true,” said Bowman. “It’s probably the single biggest impact my work will ever have.”

Dhongde measured the quality of life among older Americans using a multidimensional well-being index she pioneered. For this study, Dhongde weighed four factors: income, housing costs, disabilities, and digital access. 

“Disadvantages tend to overlap, and their cumulative effects can be more severe than experiencing each one on its own,” Dhongde said. “By weighing them together, policymakers can identify people experiencing clusters of disadvantages and provide more targeted interventions.”

Read the full story.

Artificial intelligence may operate in the digital world, but it leaves a massive and very real physical and societal footprint. What does AI’s rapid growth mean for the future of humanity? How can it be steered towards a more prosperous future for all? 

The positive and negative potential of AI was the focus of the first Georgia Tech AI & Society Series event, hosted by the Ivan Allen College of Liberal Arts and the Michael E. Tennenbaum Family Institute for Technology and Civic Leadership on Oct. 8.

“How do we harness the technology for good and minimize the bad?” said Georgia Tech Provost Raheem Beyah in his opening remarks. Understanding and planning for AI-driven societal changes will require a knowledge of history, economics, communication, and so much more — subjects grounded in the humanities and social sciences, he said.

“No better place than Georgia Tech, and no better college than the Ivan Allen College of Liberal Arts to lead the discussion,” he added.

The panel, “We, the People, and AI: The Future of Data, Energy, Health, and Human Rights,” was moderated by Ivan Allen College of Liberal Arts Dean Amanda Murdie and included Wendy H. Wong, Professor, University of British Columbia – Okanagan Campus; Caroline Gwynn Monagle, Vice President, Strategic Initiatives, R1 RCM; and Marilyn A. Brown, Regents’ and Brook Byers Professor, Jimmy and Rosalynn Carter School of Public Policy.

One focus of the evening was data privacy. Many people are giving AI agents and other systems more and more access to their private information in the name of convenience and efficiency.

Wong, author of the book “We, the Data: Human Rights in the Digital Age,” discussed how our digital lives create massive amounts of data being collected, analyzed, bought, and sold.

“I think about data as sticky, like literally like gum on the bottom of your shoe. Really easy to make … and really hard to get off,” Wong said.

Individuals often lack access and control of data being created about them.

“The data about you don’t belong to you. They belong to the data collector,” she said.

AI has only accelerated this data collection and intensifies the need to explore whether human rights should be extended to cover our digital data.

“AI is not happening to you. AI is happening, and you have a way to think about what you want out of that,” Wong said. “We are all data stakeholders.”

AI’s possible impacts on energy and sustainability were also discussed. Brown, an expert in sustainable energy technologies and policy, shared what excites her about AI’s possible uses related to sustainability.

“AI can optimize the electricity grid. It can improve industrial processes, reduce waste, predict equipment failures, [and] help integrate variable renewable energy into the system,” Brown said.

Meanwhile, AI’s high consumption of energy is a challenge yet to be overcome and could produce unequal environmental and economic impacts, Brown said.

“My concern is that we’re not paying attention to who’s going to bear the consequences of all of that pollution relative to who is going to be benefiting from the economic growth and wealth of AI.”

From medical breakthroughs to doctors taking AI notes during appointments, AI’s influence on health and medicine was also discussed.

Monagle, a leader in the healthcare technology and services industry, discussed how AI is improving processes around healthcare and insurance but also cautioned that only certain functions could be ceded to technology and that human expertise was still very valuable in the healthcare space.

“We still have to be the ones in the driver’s seat, and that means we still have to be experts in our fields. We can’t just rely on AI to tell us everything,” Monagle said.

Higher education, and the liberal arts in particular, have an important role to play in training future professionals to consider factors beyond just technology and the bottom line when implementing AI and other technologies in their fields, Monagle said.

“It’s important that universities teach people to step back and think holistically about what we are building. Why are we building it? What is it going to achieve? Is this aligned with our values? And what are our values?” said Monagle.

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.”
 

These outstanding faculty members were chosen for their exceptional research accomplishments, demonstrated leadership, and ability to drive high-impact, interdisciplinary initiatives. Representing a wide range of academic disciplines, they embody the depth, innovation, and collaborative spirit that define Georgia Tech’s research community.

Over the next year, this inaugural cohort will engage in a dynamic, immersive program designed to cultivate strategic research leadership through mentorship, experiential learning, and cross-campus dialogue. Their work through the RLA will not only strengthen Georgia Tech’s research enterprise but also help shape its trajectory for years to come.

Please join us in celebrating and congratulating these remarkable scholars as they embark on this exciting journey. 

• Steve Diggle – Institute for Bioengineering and Bioscience; School of Biological Sciences
• Marta Hatzell – Institute for Matter and Systems; Renewable Bioproducts Institute; Strategic Energy Institute; George W. Woodruff School of Mechanical Engineering
• Ada Gavrilovska – Institute for Data Engineering and Science; School of Computer Science
• Margaret Kosal – Institute for Bioengineering and Bioscience; Strategic Energy Institute; Institute for Matter and Systems; Sam Nunn School of International Affairs
• Sheng Dai – Institute for Bioengineering and Bioscience; Strategic Energy Institute; School of Civil and Environmental Engineering
• Yuguo Tao – George W. Woodruff School of Mechanical Engineering; Nuclear and Radiological Engineering; and Medical Physics
• Chris Wiese – Institute for Bioengineering and Bioscience; Institute for Data Engineering and Science; Institute for People and Technology; School of Psychology
• Mathieu Dahan – Institute for People and Technology, H. Milton Stewart School of Industrial and Systems Engineering
• Thackery Brown – School of Psychology
• Charlotte Alexander – Tech AI, Scheller College of Business; Law and Ethics
• Jeff Young – Institute for Data Engineering and Science; Partnership for Advanced Computing Environments; Office of Information Technology
• Meltem Alemdar – Center for Education Integrating Science, Mathematics, and Computing
• Kamran Paynabar – Georgia Tech Manufacturing Institute; Institute for Data Engineering and Science; Renewable Bioproducts Institute; H. Milton Stewart School of Industrial and Systems Engineering
• John A. Christian – Daniel Guggenheim School of Aerospace Engineering
• Farzaneh Najafi – Institute for Bioengineering and Bioscience; School of Biological Sciences
• Dave Flaherty – Strategic Energy Institute; School of Chemical and Biomolecular Engineering
• Eunhwa Yang – Institute for Matter and Systems; Strategic Energy Institute; School of Building Construction
• James Tsai – Strategic Energy Institute; School of Civil and Environmental Engineering
• Jennifer Hirsch – Brook Byers Institute for Sustainable Systems; Center for Sustainable Communities Research and Education; Strategic Energy Institute

Georgia Tech is introducing a standardized process for requesting and issuing physical keys for campus facilities. The changes support the Institutional Facility Access Control Policy, which establishes requirements for granting and managing access to Georgia Tech facilities.  

As AI systems become more agile with expanded access to tools, computer networks, and other real-world systems, finding better ways of identifying and preventing risky AI behavior becomes even more urgent. Still, high-profile incidents of AI behaving in unintended or dangerous ways are rare, which makes them difficult to study and understand. 

“If we can understand and detect what changes inside an AI model right before it begins behaving in unsafe or misaligned ways, we may be able to inform more effective safeguards,” said Eyas Ayesh, a second-year Ph.D. student in Georgia Tech’s School of Psychology and graduate fellow at the Center for Computation and Cognition.

Ayesh and his advisor, Assistant Professor Anna Ivanova, are developing a probe designed to identify internal activity patterns associated with harmful behaviors in large language models. Their work is supported by a $300,000 award from Coefficient Giving.

Misbehaving Models

Training a probe requires examples of both desirable and undesirable behaviors so it can learn to distinguish between them. Because deceptive or unsafe responses can be rare and highly dependent on the model, prompt, and context, researchers may not have enough examples to determine what causes the behavior or how to recognize it the next time.

But an unexpected finding in AI research gave Ayesh an idea. In studies of a phenomenon known as emergent misalignment, researchers found that fine-tuning models on a narrow harmful task could lead them to produce a much wider range of problematic responses to unrelated prompts. For example, researchers found that fine-tuning a model to write insecure code without warning users could lead to other concerning behaviors unrelated to coding.

Ayesh realized he could use that phenomenon to solve the problem of scarce data. Starting with open-source AI models, Ayesh fine-tuned them to display targeted undesirable behaviors more frequently. Then, he analyzed different versions of the deliberately misaligned models using a probe that monitors the internal activity of the model.

The probe works somewhat like a pattern detector, looking at activity inside the model as it generates responses and searching for patterns associated with particular behaviors. Researchers can then train a classifier to distinguish patterns associated with desirable behavior from those associated with harmful behavior.

“Just as different parts of the brain turn on and off when people do different tasks, so do the different parts of an AI model,” Ayesh said. “When a model produces a specific type of response — such as deceptive statements or harmful advice — we may observe recurring patterns in its internal activity. We refer to these patterns as representations of a behavior.”

Inside the Black Box

Ayesh is now testing whether the internal patterns he identified remain consistent across differently tuned AI models. Early results suggest that signals identified in deliberately misbehaving models can also be detected in their original versions.

The next step is determining whether those signals can help researchers identify or flag concerning behavior in models that have not been deliberately fine-tuned to misbehave. 

“I hope our research in AI safety can help develop some guardrails and some ways to both identify and prevent misaligned behavior in AI systems, given how much of an impact they're already having on the world,” he said. 

Ayesh is a member of Georgia Tech’s AI Safety Initiative, which brings together researchers across disciplines to study and improve the safety of increasingly capable AI systems.

Ivanova said the value of their research lies partly in approaching AI safety from a fundamental science perspective.

“As scientists, we have been trained to think about the underlying mechanisms and causes of the behaviors we observe,” Ivanova said. “For us, it's important to develop a fundamental understanding of how these models work, or we will risk missing the bigger picture.”

RoboRambler is one of Georgia Tech’s newer student robotics clubs, but just two years after its creation, the team is making a name for itself on a national stage.  

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. 

How much rain can a hurricane make, and how much do big versus small hurricanes make? – Naarah, age 8, Pittsburgh

Hurricanes can produce enormous amounts of rain, adding up to trillions of gallons of water. But the big risk isn’t their total amount – it’s how much rain falls on each location.

One town in Texas got over 60 inches (152 centimeters) of rain from Hurricane Harvey over five days in 2017. That means empty swimming pools there would have filled with rainwater 5 feet (1.5 meters) deep. Hurricane Lane dumped 58 inches (147 centimeters) of rain on Kahuna Falls, Hawaii, the following year.

So, what causes that much rain, and does the size of the storm matter?

I’m an atmospheric scientist who teaches college students about weather at Georgia Tech. Let’s take a look at where a hurricane’s rainfall comes from and some of the questions about hurricanes and their rainfall that scientists are still trying to answer.

First, What Goes Into Creating a Hurricane?

A few ingredients are needed for a hurricane to form: A tropical thunderstorm complex, lots of moisture in the air, winds that don’t change speed much with height, and warm sea surface waters below.

The water temperature is very important.

The magic number for surface water temperature to be able to fuel a hurricane is at least 80 degrees Fahrenheit (26.5 degrees Celsius). At that temperature and above, the warm ocean water evaporates into the air, changing from liquid to vapor. As it makes that change, it provides energy to fuel the storm and also adds moisture to the atmosphere that eventually falls as rain.

When a hurricane moves over warm water, especially when the warm water extends many feet below the surface, the storm pulls in even more energy and moisture.

What Affects Hurricane Size and Rainfall?

This is one of the many questions about hurricanes that atmospheric scientists are working on.

The average hurricane is about 300 miles (482 kilometers) wide, but hurricanes – or typhoons, as they’re called in the western Pacific of the Northern Hemisphere – can be much bigger or smaller.

Super Typhoon Tip in 1979 grew to half the size of the lower 48 U.S. states. It had a radius of about 690 miles (1,110 kilometers), measured from the center of the storm to its outer edges, meaning it was 1,380 miles (2,222 kilometers) wide. Tropical Storm Marco’s gale-force winds in 2008, in comparison, had a radius of 11.5 miles (18.5 kilometers), meaning it was about 23 miles (37 kilometers) across – not much larger than New York City.

In 2025, scientists published a study showing that hurricane size appears to be influenced by how warm the ocean water is compared to its usual temperature that time of year. So, if a hurricane moves over water that is much warmer than normal, it tends to grow in size rapidly as well as growing in strength.

A recent hurricane that was very large in size was the extremely destructive Hurricane Helene in 2024. As Helene moved over water near Florida that was much warmer than normal for late September, it picked up lots of moisture that it carried all the way to the mountains of North Carolina. Several days of rain from the storm caused catastrophic flooding there.

But don’t count the small hurricanes out.

Just because a hurricane is small, that does not mean that it won’t have a big impact.

Hurricane Andrew in 1992 was destructive yet small. Its strongest winds extended only about 90 miles (150 km) from its center when it reached Miami and the Everglades. But that Category 5 hurricane is still known as one of the strongest hurricanes to hit the United States. It destroyed more than 25,000 homes.

A strong storm isn’t necessary for a lot of rain to fall. Tropical Storm Allison in 2001 is still one of the wettest tropical weather events in U.S. history. It caused over US$4 billion in damage in Texas alone, and it didn’t even develop into a hurricane!

So, What Really Leads to the Highest Rainfall Totals?

Hurricanes that move slowly or nearly stop along their path usually cause the biggest rainfall problems because their rain keeps falling over the same location. The rain may be just as intense in a fast-moving hurricane, but it doesn’t stick around as long.

An example is Hurricane Harvey, which hit southeastern Texas in late August 2017. The storm dropped an estimated 27 trillion gallons of water over the state – that’s enough to fill about 40 million Olympic-size swimming pools.

When Harvey stalled over the Houston area, the storm kept drawing moisture from the warm waters of the Gulf. Over four days, it brought precipitation that totals as high as 60.58 inches (1.54 meters) of rain over Nederland, Texas. The extreme rainfall overran the town’s drainage and transformed Nederland into an island.

If a storm moves fast, like Hurricane Michael did in 2018 when it hit the Florida Panhandle, its winds and storm surge can make a big mess, but its rainfall totals will be lower.

Michael was a Category 5 hurricane – more powerful than Harvey and Helene – but its rainfall totals for locations along its path ranged from 6 to 10 inches (15 to 25 centimeters) because it was moving so fast. That’s still a lot of rain, but not compared to Harvey or to Helene, which dumped 30 inches (76 centimeters) of rain on Busick, N.C., over a few days.

So, a hurricane can be large or small in size and still have a big impact, depending on how slowly it’s moving.

There is still a lot to learn about hurricanes. Some big questions involve what’s known as rapid intensification. That occurs when a tropical storm’s maximum wind speed increases quickly, by 30 knots (about 34.5 miles per hour or 55 kilometers per hour) or more within 24 hours.

When rapid intensification occurs, as happened with hurricanes Harvey, Michael and Helene before they hit land, the storm can surprise coastal residents and become catastrophic.

Hurricanes of all sizes can be dangerous, so accurate forecasting well before they reach land is crucial to help people prepare for their impacts. One very important area of research that today’s scientists – and future scientists – can work on is improving forecasting so coastal residents know what’s coming and have time to prepare.

Hello, curious kids! Do you have a question you’d like an expert to answer? Ask an adult to send your question to CuriousKidsUS@theconversation.com. Please tell us your name, age and the city where you live.

And since curiosity has no age limit – adults, let us know what you’re wondering, too. We won’t be able to answer every question, but we will do our best.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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On October 20, every graduate student will find an email in their student inbox from “Qualtrics” with the subject line “2026 Graduate Student Experience Survey.” This email contains a unique URL, which provides direct access to the survey. 

“We strongly encourage you to participate in this survey,” said James Black, Executive Director of Graduate Student Success in the Office of Graduate Education. “Your input is crucial in helping us understand the current state of graduate student life and identify areas for improvement. Together, we can work towards making Georgia Tech an even better place for graduate education.”

The survey is conducted once every few years to quantify various factors that impact the experiences of graduate students at Georgia Tech. The last survey was conducted in 2023. This survey is incredibly important. Institute leaders will utilize this data to make strategic investments in programs, support, and resources to improve the graduate student experience in the future. Previous surveys have led to many positive changes including:

• $2M in funding for stipend increases the year after the 2023 survey
• “Improving the graduate student experience” added to the Institute Strategic Plan yielding new mentoring-in-research programs, increases in the health-insurance subsidies, more graduate student career education, and more transparency in graduate student employment policies and offer letters
• New Navigate360 graduate student advising platform

All responses are confidential and will never be attributed to a specific person; results will only be presented in an aggregate form. 

Questions about the survey can be directed to grad.ask@grad.gatech.edu.
 

Developing a technology that works is a major milestone, but it is not the end of the story. What happens next can determine how far an innovation travels beyond the lab and who ultimately benefits from it. 

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

Called the Pacific Ocean Neutrino Experiment (P-ONE), it will be built off the coast of Washington State in the Cascadia Basin with global collaboration including Georgia Tech’s Ignacio Taboada. 

Taboada, who is the current spokesperson of the IceCube collaboration and a professor in the School of Physics, has been awarded over $1.5 million in funding through a Major Research Instrumentation grant from the National Science Foundation (NSF) to build P-ONE’s sensor trigger system, which will record and identify sources of light as they are captured by the telescope’s sensors.

“This is a multi-institute collaboration,” Taboada shares. Co-PI’s include Naoko Kurahashi Neilson of Drexel University, Nathan Whitehorn and Tyce DeYoung of Michigan State University, and Alexandra Rahlin of the University of Chicago.

2,600 meters under the sea

Taboada says the team was drawn to the underwater location, despite the associated building challenges because “the characteristics of the seawater mean that we could identify more individual sources better than IceCube can, if we can build a detector of the same size.”

Capturing astrophysical particles is a balance of finding the right medium for the sensors: the medium’s density contributes to how many particles are captured. 

While an open-air observatory would be possible, Taboada explains that “air is about 1,000 times less dense, so it means that we would get 1,000 times fewer neutrinos interacting in the detector — and neutrino detections are very, very rare.” Using a medium like ice or seawater maximizes the possibility of capturing these particles.

Ice and seawater also present unique challenges. “The ice in Antarctica is extremely transparent,” Taboada explains. This means that when a photon enters the ice, it can travel a very long distance within that ice. “But it doesn't travel in a straight line,” he says. Instead, the particle ricochets and scatters, deviating from its original path.

This makes it more difficult to determine exactly where the particle has come from — a key aspect for astronomical observations. “In comparison, light entering seawater scatters much less," Taboada says. “It always travels in a straight line.” Because of this, neutrino directions are determined more precisely in seawater than in ice.

Tracing the cosmos

Key to capturing these particles is the trigger system that Taboada will build with this new funding. That component  will collect data around interesting events, which are seen as light to the system.  

But there are many sources of light in the ocean that aren’t from astronomical phenomena. “It's not something that can be trivially predicted,” says Taboada. “It's a very complicated situation and you have to adapt the trigger to various amounts of background light.”

For example, there’s bioluminescence to consider.

Some sources, like fish or small organisms, can move around independently, while others, like bioluminescent plankton, might instead react to turbulence. The trigger system will need to identify and filter out all of these sources.

“Seawater also has a lot of potassium,” Taboada adds. “One of the isotopes of potassium is radioactive, and the optical sensors can catch light from that.”

Once the trigger system recognizes and captures the event, the data is sent to the mainland, where computers will leverage machine and deep learning to determine exactly what the sensor has captured.

“It's a process of gathering and analyzing interesting data,” Taboada says, similar to looking into a night sky and differentiating shooting stars, constellations, satellites, and planes.

From sea to space

Because P-ONE is one of the first projects of its kind, the research team plans to initially install six or seven lines of instrumentation across the seafloor. “That is rather small,” says Taboada, “but it will demonstrate how to build the instrument and how to operate it.”

“P-ONE has the eventual objective of being similar to IceCube in size,” he adds. “But it will be a northern hemisphere detector (meaning it can ‘see’ different parts of the sky than IceCube), and should have significantly better angular resolution and sensitivity.” And while P-ONE’s location will provide views that IceCube can’t, the effort also has the potential to provide a new perspective of the ocean floor.

The system will continuously monitor the deep ocean at an unprecedented scale, capturing data about environmental conditions and biological processes, key information for oceanographers and marine biologists — all while furthering the field of neutrino astrophysics.

Funding: NSF

P-ONE is a collaboration between the following organizations: 

Ocean Networks Canada; University of Victoria; University of Alberta; Department of Physics, Queen's University; Department of Physics, Simon Fraser University; TRIUMF; Department of Physics, Technical University of Munich; Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen Centre for Astroparticle Physics; Collaborative Research Centre 1258 (SFB1258) at TUM funded by the Deutsche Forschungsgemeinschaft (DFG); European Southern Observatory; Institut für Kernphysik, Goethe Universität Frankfurt; GSI Helmholtzzentrum für Schwerionenforschung; Max Planck Institute for Physics; Institute of Nuclear Physics, Polish Academy of Science; University College London; Department of Physics and Astronomy, Michigan State University; Georgia Institute of Technology; Drexel University; University of Chicago

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

The global ranking represents a substantial advance from 2024, when Georgia Tech was placed in the 126–150 band. The latest results position Georgia Tech among the world's top 100 universities for psychology and among the top 40 nationally. Georgia Tech is also the highest-ranked university in Georgia for psychology, ahead of both public and private institutions in the State.

The recognition follows improvements in several measures of research and education, particularly research quality, teaching, and international engagement.

“This recognition is encouraging, not simply because of the ranking itself, but because it reflects the collective efforts of our faculty, students, postdoctoral researchers, staff, and collaborators,” said Tansu Celikel, professor and chair of the School of Psychological and Brain Sciences. “Our focus is on asking important questions, conducting rigorous research, and preparing the next generation of scientists. It is gratifying to see that work gain greater international visibility.”

Research Quality Drives Strong Performance

One of the most notable developments is Georgia Tech's improvement in research quality, which rose from 77.2 in 2024 to 86.5 in 2026 on THE's 100-point scale.

The 2026 research quality score also compares favorably with other leading universities in Georgia. Emory University received a score of 68.3, while the University of Georgia scored 74.8.

THE's research quality indicators consider citation impact, research strength, research excellence, and research influence. Together, they provide a multidimensional assessment of scholarly contributions and their influence on subsequent research.

Georgia Tech also recorded gains in teaching, with its score increasing from 32.3 to 43.9, and research environment, which rose from 34.6 to 40.0. Its international outlook score increased from 56.1 to 59.3.

“These rankings offer one perspective on academic performance, and no single measure can capture the full value of a research and educational community,” Celikel said. “What matters most is that our work contributes meaningful knowledge, creates opportunities for our students, and helps address important questions about the brain, mind, and behavior.”

Five Programs Connecting Brain, Behavior, and Technology

The School's research and educational mission spans five complementary programs: Cognition and Brain Science, Adult Development and Aging, Engineering Psychology, Quantitative Psychology, and Industrial/Organizational (I/O) Psychology.

Together, these programs address fundamental and applied questions about human experience.

Cognition and Brain Science investigates the neural and cognitive mechanisms underlying sensation, perception, learning, memory, attention, and decision-making. Adult Development and Aging examines how cognition, behavior, and everyday functioning change across adulthood and later life.

Engineering Psychology focuses on the interaction between people and technology, including the design of systems that support human abilities, performance, and safety. Quantitative Psychology develops and applies statistical, mathematical, and computational methods to understand complex behavioral and psychological phenomena. Industrial/Organizational Psychology studies behavior in workplaces and organizations, including employee well-being, teamwork, leadership, and performance.

These areas provide complementary perspectives on how people think, learn, work, interact with technology, and adapt throughout life. They also create opportunities for collaboration across traditional disciplinary boundaries.

“Our five programs reflect the breadth of psychological science and the different ways it contributes to understanding people and the world around us,” Celikel said. “What makes our School distinctive is not only the strength of these individual areas, but also the opportunities for them to work together and connect with Georgia Tech's expertise in engineering, computing, and the sciences.”

An Interdisciplinary Environment for Discovery

The School's position within a leading science and engineering institution creates unique opportunities to advance psychological and brain sciences through interdisciplinary research, technological innovation, and collaboration.

Research at PBS spans experimental, computational, theoretical, and applied approaches, connecting discoveries about neural circuits and cognitive processes with research on human development, decision-making, workplaces, and human-centered technologies.

Over the past four years, PBS has significantly expanded its research infrastructure by establishing three Centers of Excellence focused on Navigation, Computational Cognition, and Human, Robot & AI Teaming, alongside new core facilities supporting the multimodal observation and control of brain and behavior.

These investments bring together expertise across psychology, neuroscience, engineering, computing, robotics, and artificial intelligence, creating new opportunities to investigate fundamental questions about how brains and intelligent systems perceive, learn, decide, and act.

The Centers of Excellence provide complementary platforms for interdisciplinary discovery. Research on navigation connects spatial cognition, neural mechanisms, and adaptive behavior. Computational cognition brings quantitative and computational approaches to understanding how minds and brains process information. Human, Robot & AI Teaming examines how people and intelligent technologies can interact, coordinate, and collaborate effectively.

Complementing these initiatives, the School's core research facilities support integrated approaches to studying brain and behavior across multiple levels of analysis. By enabling multimodal measurement and experimental control, these capabilities help researchers connect neural activity, cognitive processes, and observable behavior within increasingly sophisticated experimental settings.

Together, the centers and facilities strengthen the School's capacity to pursue ambitious scientific questions, support collaborative research, and provide students and early-career scientists with access to advanced research methods and technologies.

“We are working hard to create an environment where researchers can pursue questions that cross traditional disciplinary boundaries,” said Celikel. “Our Centers of Excellence and shared research facilities are investments in people and possibilities. They help us bring different perspectives together, support our students and colleagues, and pursue scientific questions that would be difficult to address within any single discipline.”

These developments reflect a broader commitment to building a collaborative research community in which fundamental discoveries about the brain, mind, and behavior can inform, and be informed by, advances in technology and computational science.

Looking Beyond the Rankings

The 2026 THE psychology rankings evaluated 694 universities across 64 countries and territories using 18 performance indicators organized into five categories: teaching, research environment, research quality, industry engagement, and international outlook.

While these rankings assess institutional performance rather than individual academic schools independently, they provide an international benchmark for Georgia Tech's development in psychological and brain sciences.

For PBS, the milestone offers an opportunity to recognize the contributions of its community while maintaining a focus on the scientific questions, educational mission, and collaborations that drive its work.

“We appreciate this recognition, but our ambitions extend well beyond rankings,” Celikel said. “Our priority is to foster an environment where talented people can pursue important scientific questions, collaborate generously, and produce research that advances our understanding of the human brain and behavior. If we do those things well, recognition will follow.”

Learn more through the 2026 Times Higher Education Psychology Rankings, the ranking methodology, and the PBS graduate programs.

The three-year project, Close-Space Sublimation for Scalable Perovskite Optoelectronics Manufacturing, is led by Liqiu Zheng, assistant professor of physics at Albany State, and Juan-Pablo Correa-Baena, associate professor and Goizueta Junior Faculty Chair in Georgia Tech’s School of Materials Science and Engineering and School of Chemistry and Biochemistry. The researchers aim to develop manufacturing approaches for perovskite thin films that could make production faster, more material-efficient, and easier to scale.

The award also will expand Albany State’s research capabilities and create hands-on learning opportunities for students at both institutions.

Georgia Tech launched the Research Collaboration Forum (RCF) in 2023 to bring together researchers from Georgia Tech and historically Black colleges and universities, as well as representatives from industry, federal agencies, and national laboratories. Participants develop partnerships and pursue new research opportunities.

Through its Seed Grant Program, the forum provides early-stage funding to help teams generate preliminary results, build capacity, and compete for larger external awards. Grants have ranged from $10,000 to $50,000. The Georgia Tech-Albany State team was among the projects funded during the forum’s inaugural cycle.

"The RCF seed funding allowed us to establish the collaboration, generate preliminary data, and demonstrate that our teams could work effectively together," Correa-Baena said. "That initial year helped us identify the key scientific questions and provided the foundation for the new three-year, $1.3 million NSF award."

The project reflects a central goal of the RCF: helping promising collaborations move from initial conversations to sustained research partnerships with national impact.

"By bringing together Georgia Tech researchers, HBCU faculty, industry partners, and federal stakeholders, we are building research capacity, strengthening long-term collaborations, and creating pathways to larger funding opportunities," said George White, director of strategic partnerships at Georgia Tech.

The award will support new thin-film manufacturing and characterization equipment at Albany State. The investment will help researchers accelerate materials discovery, build long-term research capacity, and give students access to advanced semiconductor research tools.

“This award elevates the research footprint of Southwest Georgia and recognizes Albany State’s ability to contribute to nationally relevant scientific research,” Zheng said. “Beyond the research, it creates opportunities for students to gain experience with advanced semiconductor technologies and helps strengthen the pipeline of talent entering the semiconductor workforce.”

Albany State and Georgia Tech will jointly study thin-film growth, structure, and device performance. As part of the collaboration, Georgia Tech researchers will support Albany State as the team acquires and begins using the new equipment, sharing expertise in operation, data collection, and analysis.

Students will receive hands-on training in thin-film deposition, X-ray characterization, solar-cell fabrication, and data analysis. The project also includes exchanges between Georgia Tech and Albany State, giving students access to research facilities, expertise, and collaborative research opportunities at both institutions.

The research focuses on a manufacturing technique known as close-space sublimation. Researchers typically produce perovskite thin films using liquid inks. Close-space sublimation instead uses heat to transport material as vapor across a short distance. The team will investigate whether the approach can be adapted for perovskite materials, potentially enabling faster, more material-efficient, and more scalable manufacturing.

The progression from a Research Collaboration Forum seed grant to a federally funded research project illustrates the forum’s broader goal: helping Georgia Tech and HBCU researchers turn early connections into sustained collaborations that expand opportunity, strengthen research capacity, and advance discovery.

Shortly after Carver came to Georgia Tech in 1994, he began considering joining the co-op program at the Microelectronics Research Center (MiRC), now part of the Institute for Matter and Systems. Initially unsure if he could do the program, his considerations began to take shape when his residence hall advisor, a MiRC employee at the time, introduced him to Jerry Hill, then center’s associate director. 

“I interviewed there and got the job,” Carver said. “It was kind of just an accident.”

What may have started as a simple interest soon evolved into a career path. From installing and repairing equipment, to developing the equipment control system now known as SUMS, Carver's experiences in the cleanroom helped him build skills that would become critical for his career. One of those experiences even helped lead him to graduate school.

“I lived on campus all through school, so I was usually on-call for after-hours emergencies,” Carver said. “Sometimes, a piece of equipment was not working correctly, and the users needed to complete a process to meet a deadline." One user happened to be Alan Doolittle, Joseph M. Pettit Professor. Carver remembers keeping a tool stable for Doolittle, since Doolittle's schedule meant lots of late-night work.

“The processes were long enough that we'd spend several hours in the lab talking about all sorts of topics. Those interactions eventually led him to offer me a spot in graduate school in his new research group.”

Throughout his time in the cleanroom, Carver was exposed to a wide variety of semiconductor processing equipment, but he had never worked with molecular beam epitaxy (MBE). Joining Doolittle’s research group changed that and helped shape the trajectory of his career. 

“Joining Alan's group ended up giving me that last piece,” Carver said. “I had to rebuild an MBE machine as the starting job of my graduate career.

During the final year of his graduate studies, Carver had been constantly applying and interviewing for jobs while preparing to defend his Ph.D. thesis on MBE. Trudging through the middle of the Great Recession, very few companies made hard offers, not knowing whether they could afford to hire him. As graduation approached, nerves rose. 

An interview with Intel at a Georgia Tech Career Fair, appeared to offer a path forward. As Carver moved through follow-up interviews with Intel, a previous meeting with representatives from JPL began to turn into something more.

“I distinctly remember one interviewer being Charles Norton who, upon learning of all the things I had done with MiRC and Doolittle's group, informed me that he knew of several people that would be interested in someone with my background,” Carver recalled. “I had several phone interviews shortly after the campus visit from several people at JPL.”

In January 2009, Intel was waiting for Carver to respond about a final interview while Carver was waiting for a call from JPL. With a leap of faith, Carver declined Intel’s final interview. 

After a month of uncertainty, JPL invited Carver to an in-person interview and presentation at its Microdevices Laboratory (MDL). 

After visiting Pasadena, California, Carver received an offer. On April 6, 2009, he defended his doctoral dissertation at Georgia Tech. Three days later, he began his new job at JPL’s Microdevices Laboratory. 

Building on his experience in Doolittle’s lab, Carver was tasked with overseeing the installation and development of a new multi-million dollar MBE system. Because of the scale of the investment, the project drew the attention of JPL leadership, including then-director, Charles Elachi.

A few years after completing work on the MBE system, Carver got the opportunity to work on a new Mars mission. He joined a team of engineers and scientists designing and building instruments for a new rover.

“I was part of the team that made the engineering cameras, and I wrote some of the software to test them,” Carver said. “So I got to help put hardware on another planet, which is really cool.”

The Perseverance rover landed on Mars on Feb. 18, 2021. Carver’s work on its engineering cameras connected a career that began in a Georgia Tech cleanroom with an exploration mission millions of miles from Earth.

Today, Carver works on challenges ranging from new optical space instruments to the effects of space radiation on microelectronics. His path from Georgia Tech’s cleanroom to JPL illustrates how skills developed through hands-on research and experimentation can contribute to exploration far beyond campus. 

Ramblin’ Royalty, hosted by the Student Center Programs Council (SCPC) within Student and Campus Event Centers (SCEC), celebrates students who embody Georgia Tech’s motto, Progress and Service. Previously known as Mr. and Ms. Georgia Tech, the program has evolved into a more inclusive scholarship initiative to represent all students who are making a positive impact on campus. 

A College of Sciences student was among the five students selected for this recognition.

Giuli Capparelli Sanabria

Year: 4th year Biology major
Nominated by: Phi Mu Fraternity

Giuli has embraced Georgia Tech’s motto of Progress and Service through a commitment to expanding educational opportunity and building connections across diverse communities. As a recipient of the G. Wayne Clough Tech Promise Scholarship, she’s transforming gratitude into action as a passionate advocate for the initiatives that make a Georgia Tech education accessible to students from all backgrounds. She has represented the institute at various events including the Gold and White Gala and Scholarship Brunch, and in 2025 was honored to serve as the keynote student speaker at the USG Scholarships and Awards Gala, sharing the impact of scholarship support and promoting access to higher education. Her dedication to service and representation also extends to campus life. Through Phi Mu, she’s aware of the value of connecting across different perspectives and backgrounds. As Phorum Lead, she facilitated educational programming focused on topics like implicit bias and cultural awareness, helping foster meaningful dialogue within her community. Her Georgia Tech journey reflects gratitude, advocacy, and a belief in the transformative power of opportunity. Representing Georgia Tech as Ramblin’ Royalty would be a celebration of her commitment and the impact she hopes to continue making for future Yellow Jackets.

>> Meet all the students named 2026 Ramblin' Royalty.

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.

Published in the Proceedings of the National Academy of Sciences (PNAS), the study, “Neuromodulatory control of cortical function: Cell-type-specific regulation of neuronal information transfer,” reveals that dopamine and acetylcholine, two chemical messengers essential for learning, attention, and cognitive flexibility, can fundamentally alter how neurons encode and transmit information.

The international research team, led by Tansu Celikel of Georgia Tech's School of Psychological and Brain Sciences and Fleur Zeldenrust of Radboud University in the Netherlands, found that these chemical signals influence different types of neurons in distinct ways. Their effects extend beyond changes in individual neuronal responses to reshape how multiple functional properties are organized and interact.

Beyond Turning Neurons Up or Down

Neurons process incoming information and communicate through electrical impulses known as action potentials. For decades, scientists have investigated how neuromodulators such as dopamine and acetylcholine influence this process, often focusing on whether these chemicals increase or decrease neuronal activity.

“Changes in neuronal activity alone do not necessarily tell us how effectively neurons process information,” explains Dr. Celikel. “A neuron that fires more frequently is not necessarily transmitting more useful information about its inputs. Likewise, a neuron that becomes less active may still play an important role in shaping how information is represented in the brain.”

The new study moves beyond conventional measures of neuronal activity by examining how neuromodulators affect multiple interacting properties, including the electrical characteristics of neuronal membranes, the generation of action potentials, adaptation to sustained stimulation, and sensitivity to incoming signals.

“Rather than acting like simple volume controls that turn neuronal activity up or down, dopamine and acetylcholine function as reconfiguration signals,” says Dr. Celikel. “They change not only how individual neurons respond, but also how the different components of neuronal information processing work together.”

Different Neurons, Different Responses

To investigate these effects, the researchers analyzed electrical recordings from excitatory and inhibitory neurons in the somatosensory cortex of mice, a brain region involved in processing sensory information, including touch.

Excitatory neurons generally promote activity within neural circuits, while inhibitory neurons help regulate and constrain that activity. The balance between these two populations is essential for normal brain function.

The researchers examined how activating three specific receptors, dopamine D1 and D2 receptors and the acetylcholine-sensitive muscarinic M1 receptor, influenced how neurons encode and transmit information.

Their findings revealed striking differences between neuronal populations and receptor types.

“Activating D1 receptors increased the amount of stimulus information transmitted by inhibitory neurons, while activating M1 receptors significantly reduced information transfer in excitatory neurons,” explains Dr. Celikel. “D2 receptor activation produced more modest effects, some of which were comparable to normal experimental variability.”

These findings challenge the assumption that increasing neuronal excitability necessarily improves information processing.

“What matters is not simply how much a neuron fires, but how effectively its activity represents incoming information,” adds Dr. Celikel. “Our results suggest that neuromodulators can selectively redistribute information processing across different neuronal populations.”

A More Flexible View of Neuronal Identity

Another important finding challenges traditional assumptions about how neurons are classified according to their functional characteristics.

Scientists commonly group neurons into functional categories based on properties such as their electrical activity, membrane characteristics, and responses to stimulation. These classifications are often treated as relatively stable.

However, the researchers discovered that activating neuromodulatory receptors reorganized how neurons clustered according to these properties.

Neurons that were functionally similar under baseline conditions could become more distinct following receptor activation, while previously dissimilar neurons could develop more closely related functional profiles.

“Our findings suggest that a neuron's functional identity is not entirely fixed, but depends in part on the chemical environment in which it operates,” says Dr. Celikel. “Rather than belonging to rigid, discrete functional categories, neurons may occupy a more flexible continuum of functional states.”

The researchers also discovered that neuromodulation reorganized the relationships among neuronal properties in different ways depending on the cell type.

Across the recorded populations, inhibitory neurons generally showed greater statistical coordination among their functional characteristics following receptor activation. Excitatory neurons, by contrast, exhibited a more selective reorganization, including greater independence between their sensitivity to incoming signals and other intrinsic properties.

This distinction suggests that neuromodulatory signals can shape the functional organization of neuronal populations in fundamentally different ways.

Together, the findings point to an additional dimension of neuronal regulation: brain chemicals influence not only individual cellular properties, but also how those properties relate to one another, potentially expanding the range of computational states available to neural circuits.

Implications for Understanding Brain Function

Dopamine and acetylcholine play essential roles in attention, learning, memory, and behavioral flexibility. Disruptions in neuromodulatory signaling are also implicated in neurological and psychiatric conditions, including Parkinson's disease and schizophrenia.

Understanding how these chemical systems reorganize neuronal information processing may help researchers develop more comprehensive explanations of how the brain adapts to changing behavioral demands and how these processes may be altered in disease.

The findings also highlight the importance of studying neuronal function beyond conventional measurements such as firing rates or excitability. By examining how different neuronal properties interact, researchers can gain a more complete understanding of how chemical signaling influences the brain's computational capabilities.

The current study examined individual neurons in isolated mouse brain tissue rather than measuring cognition or behavior directly. Further research will be needed to determine how these cellular changes influence the activity of larger neural networks and behavior in living animals.

Nevertheless, the findings establish a framework for understanding neuromodulation as a dynamic process that reorganizes neuronal computation rather than simply increasing or decreasing activity.

By demonstrating that dopamine and acetylcholine can reshape information transfer, functional classifications, and the relationships among neuronal properties, the study provides new insight into the cellular mechanisms that may enable the brain to adapt its information processing to changing conditions.

Publication information

Article: “Neuromodulatory control of cortical function: Cell-type-specific regulation of neuronal information transfer”

Journal: Proceedings of the National Academy of Sciences (PNAS)

Publication date: October 19, 2026

DOI: https://doi.org/10.1073/pnas.2609893123

The strategy, announced in July 2026 as part of Panama’s National Agenda on Advanced Technologies, was developed through a partnership between Panama’s National Secretariat of Science, Technology, and Innovation (SENACYT) and Tech AI, Georgia Tech’s AI solutions developer. The effort brought together leaders from government, academia, industry, and civil society.

The strategy identifies priorities for AI across economic development, workforce preparation, digital infrastructure, governance, research, and international collaboration.

Pascal Van Hentenryck, the A. Russell Chandler III Chair and professor at Georgia Tech and director of the National Science Foundation (NSF) Artificial Intelligence Institute for Advances in Optimization (NSF AI4OPT), helped lead the development of the strategy.

“Panama has a unique opportunity to leverage its position as a global logistics and financial hub to become a trusted leader in AI,” Van Hentenryck said. “The strategy lays out what is needed to develop the talent, infrastructure, data, and institutions to support that ambition.”

Panama’s focus on artificial intelligence comes as the country expands its role in Latin America’s technology ecosystem. The 2025 Latin American Artificial Intelligence Index classified Panama as an “Adopter” nation and reported a 1.47-point increase in the country’s score from the previous edition.

Building the strategy

Van Hentenryck and Timothy M. Brown, interim managing director of Tech AI at Georgia Tech, authored the strategy following months of engagement with stakeholders throughout Panama.

The process included workshops, interviews, and a nationwide survey that gathered input from more than 6,700 Panamanians. Government officials, researchers, industry representatives, educators, and community members contributed perspectives on the country’s opportunities and challenges.

“The strategy was shaped by what we heard from people across Panama,” Brown said. “That input helped identify where AI can have the greatest impact and what Panama needs to build the capacity to use it effectively.”

The resulting framework is organized around five foundational pillars:

1. Governance and regulatory framework
2. Human talent and institutional capacity
3. Data and infrastructure
4. Ethics, inclusion, and sustainability
5. International cooperation and global standards

Together, the priorities are intended to support AI adoption across sectors including logistics, financial services, healthcare, agriculture, education, manufacturing, government services, and energy.

At the center of the strategy is a vision for Panama to become “Latin America’s Trusted Hub for AI Innovation.” The plan builds on the country’s established role in global logistics and finance, envisioning a “Digital Canal” that supports the secure movement of data, technology, talent, and innovation throughout the region.

Eduardo Ortega-Barría, national secretary of science, technology, and innovation at SENACYT, said the strategy provides a foundation for Panama to participate more fully in the global AI economy.

“AI is transforming economies, societies, and the way we work,” Ortega-Barría said. “For Panama, this strategy is about preparing our country to participate in that transformation while ensuring that innovation creates opportunities for our people and strengthens our competitiveness.”

Connecting research and policy

The strategy reflects contributions from Georgia Tech researchers and experts, SENACYT leadership, policymakers, international advisers, and private-sector stakeholders. AMD also participated in the initiative.

Keith Strier, senior vice president of Global AI Markets at AMD, said international partnerships will be important as Panama develops its technology ecosystem.

“Panama is building its domestic AI capabilities and infrastructure together with the United States as a strategic partner,” Strier said. “This is an important moment as Panama establishes its role in the global AI ecosystem.”

For Georgia Tech, the project illustrates how the Institute’s research and technical expertise can inform national-level technology planning.

Rather than focusing solely on AI development, the strategy connects technical capabilities with workforce preparation, research capacity, infrastructure, entrepreneurship, cybersecurity, and responsible governance. It also calls for efforts to expand access to AI opportunities in rural and underserved communities.

Van Hentenryck said developing the strategy required understanding Panama’s priorities alongside the opportunities presented by emerging technologies.

“Working on a national strategy requires bringing together different perspectives,” he said. “Panama has its own strengths, challenges, and ambitions, and those were essential to shaping a strategy that can work for the country.”

From strategy to implementation

The launch marks the beginning of the next phase: putting the strategy into action.

The road map includes recommendations for expanding AI education and workforce training, strengthening research capacity, improving digital infrastructure and cybersecurity, establishing responsible AI governance, and creating mechanisms to support entrepreneurship and innovation.

Franklin Morales, head of the International Technical Cooperation Office at SENACYT and project lead for the AI initiative, said the strategy provides a starting point for that work.

“Now this is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning,” Morales said, quoting Winston Churchill. “After months of work, Panama launched its National Artificial Intelligence Strategy, a vision of what this country needs to build for a new technological era.”

“The launch of the strategy is an important milestone, but the real work begins with implementation,” Brown said. “The focus now is on turning these priorities into lasting capacity, developing talent, and infrastructure while supporting research, entrepreneurship, and responsible AI adoption.”

For Panama, the strategy establishes a framework for using artificial intelligence to strengthen economic competitiveness, expand opportunity, and support the country’s role in an increasingly technology-driven global economy.

NSF has awarded $20 million to renew the National AI Institute for Advances in Optimization (NSF AI4OPT) through 2031 and $18.4 million to renew the National AI Institute for Adult Learning and Online Education (NSF AI-ALOE) for a new five-year period. The awards will support research at the intersection of artificial intelligence and optimization, as well as the development of AI technologies for adult learning, higher education, and workforce development. A third Georgia Tech-led National AI Institute, the AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups (AI-CARING), will continue its research under a one-year no-cost extension.

Together, the institutes represent a broad range of AI research at Georgia Tech, with work spanning energy systems, advanced manufacturing, education, reskilling, and workforce development.

The renewed investments come as NSF continues to prioritize artificial intelligence, advanced research infrastructure, and development of the nation’s STEM workforce.

“Georgia Tech has built a nationally recognized ecosystem for artificial intelligence research, education, and application,” said Tim Lieuwen, interim president and executive vice president for Research at Georgia Tech. “These NSF investments recognize the strength of our researchers and the importance of advancing AI in ways that address real-world challenges. The continued support for NSF AI4OPT and NSF AI-ALOE will allow Georgia Tech researchers to push the boundaries of what AI can accomplish while preparing students, educators, and the workforce for an increasingly AI-enabled future.”

Advancing AI-Powered Decision-Making

The $20 million renewal of NSF AI4OPT builds on five years of research at the intersection of artificial intelligence and mathematical optimization.

Led by Pascal Van Hentenryck, the A. Russell Chandler III Chair and professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, NSF AI4OPT develops AI and optimization technologies for complex systems where decisions must be made quickly, efficiently, and under uncertainty.

In its next phase, the institute will place greater emphasis on real-time and interactive optimization, advancing scalable, efficient, and trustworthy approaches to decision-making. Research will continue to address challenges in areas such as energy, supply chains, transportation, and advanced manufacturing.

“NSF AI4OPT’s first five years demonstrated the power of bringing AI and optimization together to address some of the most challenging decision-making problems facing society,” said Van Hentenryck. “This renewal gives us the opportunity to build on that foundation and develop AI systems that can reason, optimize, and make decisions in real time. We are especially excited about advancing trustworthy AI for complex systems in energy, supply chains, and manufacturing, while continuing to educate the next generation of AI researchers and practitioners, starting with middle and high schoolers.”

NSF AI4OPT combines artificial intelligence, mathematical optimization, and computing to create systems that support decisions in complex and dynamic environments. Its research includes applications in critical infrastructure and industry, where decisions often involve competing objectives, uncertainty, and rapidly changing conditions.

The institute also has an education and workforce development mission, introducing AI and optimization concepts to students and educators while preparing learners for an AI-enabled workforce.

“NSF AI4OPT represents exactly the kind of interdisciplinary research that Georgia Tech is positioned to lead,” said Raheem Beyah, provost and executive vice president of Academic Affairs at Georgia Tech and former dean of the College of Engineering and Southern Company Chair. “The institute connects foundational advances in artificial intelligence and optimization with engineering challenges that have direct implications for our economy and society. Its continued investment in research and education strengthens Georgia Tech’s ability to prepare students to lead in a rapidly changing technological landscape.”

Advancing Adaptive Expertise Through AI

NSF AI-ALOE’s renewed $18.4 million award launches the institute’s next five years of research into how artificial intelligence can transform adult learning and online education.

The renewal builds on NSF AI-ALOE’s previous work, including the development of seven AI agents and a data architecture for AI-augmented learning. Its next phase will focus on adaptive expertise, or the ability to apply and transfer learned skills to new situations.

AI-ALOE’s research in Phase 2 will expand beyond traditional educational settings into workplace and vocational training, with a focus on occupational skills in areas including advanced manufacturing and data science.

NSF AI-ALOE will also build on advances in generative and agentic AI to develop AI agents that support the acquisition of complex skills across higher education and workplace environments.

“NSF AI-ALOE’s renewal reflects an important shift in how we think about AI and learning,” said Ashok Goel, director of NSF AI-ALOE and professor of computer science and human-centered computing in the School of Interactive Computing at Georgia Tech. “Our goal is not simply to use AI to deliver more content or automate instruction. We are exploring how AI can help people develop adaptive expertise, so they can transfer what they learn to new and changing situations. That has enormous implications for higher education, workforce development, and lifelong learning.”

The institute’s research will examine four dimensions of AI-supported learning: scalability, personalization, transfer of learned skills, and whole-person learning. It will also advance foundational AI research in machine teaching, metacognition in AI agents, and mutual theory of mind between humans and AI agents.

NSF AI-ALOE will use the data architecture developed in Phase 1 that is capable of ingesting, standardizing, analyzing, and visualizing information generated through interactions with AI tools, learning management systems, and student information systems. Researchers will use that data to better understand how learners and instructors interact with AI and improve AI-powered learning technologies.

The institute is also expanding partnerships with higher education institutions and industry. Its research network includes five colleges and universities and six industry partners in advanced manufacturing and related fields, creating opportunities to reach as many as 370,000 learners nationally through skilling, reskilling, and upskilling efforts.

“AI is changing both what people need to learn and how they can learn it,” said David Joyner, Zvi Galil PEACE Chair in the College of Computing and interim vice provost for AI in Education at Georgia Tech. “NSF AI-ALOE is uniquely positioned to study that transformation at scale. Its work can help us understand how AI can support learners without replacing the human elements of education, while giving people new ways to build and apply skills throughout their lives and careers.”

Continuing AI-CARING’s Research

The renewed support for NSF AI4OPT and NSF AI-ALOE builds on Georgia Tech’s broader participation in the National AI Institutes program.

Georgia Tech’s AI-CARING Institute will continue its research under a one-year no-cost extension, allowing the institute to carry forward its research objectives and partnerships.

The continued work of AI-CARING, alongside the renewed investments in NSF AI4OPT and NSF AI-ALOE, reflects the breadth of Georgia Tech’s AI research community and its work across disciplines.

From AI Research to Real-World Impact

The renewed NSF investments build on Georgia Tech’s broader efforts to advance AI research, education, and application through Georgia Tech AI and Tech AI.

Georgia Tech AI connects Tech’s AI community across research, education, and impact. Tech AI complements this work by serving as Georgia Tech’s engineering and delivery arm, bringing together researchers, engineers, research software engineers, students, and technical expertise to move AI projects from early-stage concepts toward operational systems.

This connection helps create a pathway from foundational research to technologies that can be developed, tested, and deployed in real-world settings.

For NSF AI4OPT, that work includes AI systems that support complex decisions in critical systems and industries, from energy and manufacturing to supply chains and transportation. For NSF AI-ALOE, it includes AI technologies that help people acquire, apply, and transfer skills across classrooms, workplaces, and lifelong learning environments.

Tech AI works at the application and deployment stage, partnering with researchers, industry, and public-sector organizations to develop and implement scalable AI solutions. Its work spans AI engineering and solution delivery, applied research, industry and government partnerships, workforce development, and responsible and trustworthy AI.

“Georgia Tech’s strength in AI comes from the connections between research, talent, and application,” said Timothy M. Brown, managing director of Tech AI. “Our NSF AI Institutes advance research across critical areas, while Tech AI serves as Georgia Tech’s engineering and delivery arm, working with industry and public-sector partners to turn AI expertise and research into deployable solutions. Together, these efforts create a pathway from AI innovation to real-world impact.”

Together with AI-CARING and Georgia Tech’s broader AI research community, the institutes contribute to a universitywide effort to advance AI that is technically innovative, human-centered, and designed for meaningful impact.

“AI is transforming virtually every sector, and Georgia Tech has a responsibility to help shape that transformation,” Lieuwen said. “These institutes bring together some of Tech’s strongest capabilities in research, education, and interdisciplinary collaboration. Their renewed support gives us an opportunity not only to advance the science of AI, but also to ensure that the benefits of these technologies reach the people, organizations, and communities that will rely on them.”

About the Georgia Institute of Technology

The Georgia Institute of Technology, or Georgia Tech, is one of the top public research universities in the U.S., developing leaders who advance technology and improve the human condition.

The Institute offers business, computing, design, engineering, liberal arts, and sciences degrees, as well as professional development and K-12 programs for fostering success at every stage of life. Its more than 56,000 undergraduate and graduate students represent 54 U.S. states and territories and more than 146 countries. They study at the main campus in Atlanta, at instructional sites around the world, and through distance and online learning.

As a leading technological university, Georgia Tech is an engine of economic development for Georgia, the Southeast and the nation, conducting more than $1 billion in research annually for government, industry and society.

About the National Science Foundation

The U.S. National Science Foundation (NSF) is an independent federal agency that supports science and technology in all 50 states, the District of Columbia, and U.S. territories. For more than 75 years, NSF has advanced the frontiers of STEM research and innovation. To keep the United States at the leading edge of discovery, NSF funds basic and solutions-oriented research that generates new knowledge to fuel industries of the future, create world-leading technologies, and improve the lives of the American people.

As interim dean, Collard will represent a college that is home to more than 3,000 students, 500 faculty members, and six internationally ranked schools.

Collard joined the Georgia Tech faculty in 1991. His research program has focused on understanding how interactions between molecules influence the properties of materials, ranging from electrical conductivity to biological responses. As an instructor he has received awards for teaching excellence and outstanding use of educational technology.

“David’s thoughtful approach and deep affinity for the college make him ideally suited to help steward this transition period,” said Raheem Beyah, provost and executive vice president for Academic Affairs. “We are grateful for his willingness to provide continuity of leadership for a college that has achieved tremendous growth in size and reputation over the past seven years.”

A national search for the College’s next dean will commence, led by College of Engineering Dean Mitchell Walker. Information regarding the search committee and key dates will be posted to provost.gatech.edu.

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.

From AIxCC to Microsoft

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.”

Continuing the Research at Georgia Tech

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

Under Tech’s Transformative Teaching and Learning (TTL) strategic initiative, a group of experienced faculty have compiled the Group Project Playbook. The Playbook provides practical design and facilitation strategies for instructors interested in maximizing group project impact.

“I appreciate receiving such a well-organized collection of resources, best practices, and practical recommendations for designing and managing course projects while minimizing common challenges,” said Tatiana Rudchenko, principal lecturer in the Scheller College of Business.

Kate Williams, associate director of Transformative Teaching and Learning, notes “our annual CTL teaching survey shows collaborative learning is the most-often used high-impact teaching practice at Georgia Tech. We hope the Group Project Playbook – created by faculty, for faculty – will help instructors plan, facilitate, and evaluate group projects.”

Download the Group Project Playbook.

The Playbook was developed by the TTL Champions, a grant-funded faculty cohort.

Generations of Yellow Jackets will come together to celebrate Georgia Tech's Homecoming the week of Oct. 19 – 24. Events will honor Institute traditions leading up to the Homecoming football game against Boston College. 

Policymakers, health system executives, community leaders and others working to address this challenge now have help from Rural Evaluation and Analytics for Community Health (REACH GA), an advanced decision-support platform that offers a comprehensive view of healthcare use in rural Georgia. In addition to updated information on rural health issues, the platform provides computer-based tools to guide allocation of healthcare resources and explore the potential impact of changes to rural health services. 

“The REACH GA platform provides up-to-date, actionable information to help leaders understand the big picture of healthcare in rural Georgia,” said Jon Duke, M.D., a principal research scientist in the Georgia Tech Research Institute (GTRI) and the project’s principal investigator. “Beyond more accurate data, the platform uses artificial intelligence (AI) and other computer-driven tools to support improved decision-making.”

Of Georgia’s 159 counties, 126 are considered rural. Approximately 24 percent of the state’s 11.3 million residents live in these rural areas.

Read the full article on the GTRI news page

Housing and Residence Life Questions: learningcommunities@gatech.edu
Housing in the WST Learning Community buildings (Stein and Goldin) is open to all who are enrolled in any Georgia Tech undergraduate or graduate degree program.

All Georgia Tech students are welcome to attend WST Center and WST Learning Community events.

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2027-28 WST Learning Community Application

Direct link to the WST Application in My Housing: https://starrez.housing.gatech.edu/StarRezPortalX/82134760/22/1377/RESOURCES-WST_APP_Landing_Page

Housing Dates

• September 22, 2026: Time tickets open for current on-campus residents and WST application available
• September 22 to October 2, 2026: Time tickets open for non-residents
• November 30, 2026: 2027-2028 WST Learning Community application closes
• December 7, 2026 at 8 a.m.: Housing Lottery application closes

Withdrawing from the WST Learning Community

Before the Lottery Deadline: Students can withdraw from WST in My Housing with no impact to their lottery decision for Academic Year Housing.

After the Lottery Deadline: Students must cancel their AY27-28 Housing application; canceling the application will remove them from WST. Students who still wish to live on campus must reapply to Housing and will be placed on the waitlist in the order of their application.

For many of these patients, care has long meant pain and disfigurement alongside other severe side effects, rather than receiving treatment that addresses the disease itself. This new ARPA-H award marks a potential turning point.

Lead researcher Susan Napier Thomas, Woodruff Professor in the George W. Woodruff School of Mechanical Engineering and the Parker H. Petit Institute of Bioengineering and Bioscience (IBB), has collaborated with her colleague J. Brandon Dixon, Woodruff Professor in the Woodruff School and IBB, for more than a decade on this project. The research partners are driven by the lack of meaningful treatment options available to patients.

“Funding support at this level is unprecedented,” Thomas said. “It finally gives us a chance to move beyond symptom management and toward real treatment. We’re addressing an underserved population with a huge unmet need.” 

A Gap in Care

The lymphatic system helps keep fluid moving through the body and plays a key role in immune health. When it does not function properly, fluid can build up in tissues, causing chronic pain and other long-term complications. Thomas noted that despite its toll on patients, lymphatic disease has lagged decades behind cardiovascular care in both treatment and research investment. 

“We are excited about this groundbreaking project in lymphatic engineering,” said Andrés García, IBB executive director. “By uniting interdisciplinary expertise, this work addresses long-standing challenges in lymphatic disease and moves meaningful solutions closer to the patients who need them most.”

What Comes Next

In the coming years, Thomas, Dixon, and their research partners will work toward an initial human trial, with an early focus on rare lymphatic conditions in children, as well as chronic disease in adults.

“This award reflects Georgia Tech’s growing leadership in using engineering to solve some of healthcare’s biggest challenges,” said Carolyn Seepersad, Eugene C. Gwaltney Jr. School Chair and professor in the Woodruff School. “It reinforces the Institute’s role in advancing innovations that improve patient care and strengthen Georgia’s position as a hub for health technology and biomedical innovation.”

The award was made through ARPA-H’s Groundbreaking Lymphatic Interventions and Drug Exploration (GLIDE) program led by Dr. Kimberley Steele.

This research was funded, in part, by the Advanced Research Projects Agency for Health (ARPA-H) under Agreement No. 1AY2AX000137-01. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. government.