Few neuroscientists would dispute that the brain relies on prediction. From houseflies evading swatters to humans catching baseballs, living things are constantly anticipating what comes next. Understanding how the brain generates those predictions could help explain one of neuroscience's most enduring questions: how the brain builds internal models of the world that allow us to learn, adapt, and anticipate what comes next.

“Without actively predicting the world, we cannot survive,” says Farzaneh Najafi, an assistant professor in the School of Biological Sciences and a faculty affiliate of Georgia Tech's Institute for Neuroscience, Neurotechnology, and Society. “There is quite some sensory-motor delay in the processing. We can’t just sit there, wait for the brain to process our environment, and then react.”

Part of the puzzle may lie in signals known as neural ramps. Almost like a drumroll leading up to a big reveal, neurons in some areas of the brain have shown gradual increases in activity immediately before a stimulus appears. For decades, researchers have interpreted this ramping activity as a neural signature of prediction, reflecting anticipation of an upcoming event.

Recently published in Science Advances, a new study from Najafi’s lab reveals these signals may not be “predictions” at all, but instead a way neurons track elapsed time.

“Surprisingly,” says Najafi, “the very first study from my lab called the Predictive Processing Lab showed that no, these are not prediction signals.”

The finding challenges a long-standing interpretation of one of neuroscience's most studied signals and reveals that the search for predictive neurons may lead to different circuits — or require different experiments to uncover. 

Launched in 2025, INNS serves as a hub for neuroscience and neurotechnology research, connecting researchers across disciplines to advance discovery, innovation, and societal impact.

“A core part of INNS's mission is helping people find one another, connect around shared interests, and build something bigger than they could accomplish alone,” says Executive Director Christopher Rozell. “Simon has spent his career bringing together people, perspectives, and disciplines to tackle complex challenges. I can't think of a better person to help lead our interdisciplinary research efforts and support the next generation of collaborative neuroscience research.”

A longtime leader in Georgia Tech's neuroscience community, Sponberg helped shape the institute's early foundations through the Neuro Next Initiative, which evolved into INNS. As associate director, he will help guide research strategy, foster new collaborations, and support interdisciplinary work across the neuroscience ecosystem.

“Neuro-related research touches so many fields that we inevitably have a problem of finding all the potential right people and opportunities to tap into,” he said. “A core responsibility of this role is helping catalyze the ideas of new teams of talented researchers, educators, and trainees from inception to realization.”

Sponberg is the Glen Robinson Professor in Complex Systems with appointments in the School of Physics and the School of Biological Sciences, where he directs the Agile Systems Lab. His work also connects him to the Institute for Bioengineering and Bioscience (IBB) and the Institute for Robotics and Intelligent Machines (IRIM), underscoring the cross-disciplinary approach that defines both his research and leadership.

Since joining Georgia Tech in 2014, he has built a highly collaborative research program spanning neuroscience, biology, physics, engineering, and robotics while helping foster interdisciplinary connections across campus. He currently leads a Multidisciplinary University Research Initiative (MURI) that brings together neuroscientists and engineers from five universities to understand how brains achieve fast, flexible perception and decision-making in complex sensory environments. He also co-leads the Integrative Movement Sciences Institute, an NSF Biological Integration Institute focused on understanding movement and muscle function across scales.

His contributions have been recognized through numerous honors, including a Young Investigator Award from the International Society for Neuroethology, a Klingenstein-Simons Fellowship in the Neurosciences, and the Leddy Family Dean’s Faculty Excellence Award.

As associate director, Sponberg will focus on helping researchers identify new opportunities for connection and collaboration. In addition to overseeing seed funding programs, he hopes to create pathways for researchers to build teams, access support resources, pursue ambitious interdisciplinary research ideas, and team with Georgia Tech’s undergraduate and graduate neuroscience degree programs.

“I look forward to being a resource for our community when people are looking for help in building teams or finding opportunities to support their ideas,” he said. “Bring your best ideas and please reach out if you want to talk about ideas in the interdisciplinary neuro space that you want to see realized.”
 

As the brain develops, billions of neurons form precise networks that enable perception, movement, and cognition. Disruptions in this process can contribute to neurodevelopmental conditions such as autism and schizophrenia. To better understand how such disorders arise, Jain’s lab will use molecular and genetic tools to trace the pathway from gene expression to neural connectivity to behavior. 

“I am honored and excited to receive support from the Whitehall Foundation,” Jain says. “It will help us pursue research questions at a stage when our findings can still shape our lab’s long-term direction.”

Jain joined Georgia Tech in 2024. He earned a Ph.D. in molecular and cellular biology from the University of Arizona and completed postdoctoral work at the University of California, Los Angeles.

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Traditional approaches to brain monitoring are often invasive, costly, and limited to clinical settings. New research from Georgia Tech points to a more accessible approach. A recent study published in Science Advances shows that a soft, wireless wearable device could help enable home-based monitoring of physiological changes associated with sleep and brain health.

The research team, led by W. Hong Yeo, Peterson Endowed Professor in the Woodruff School of Mechanical Engineering and director of the Wearable Intelligent Systems and Healthcare Center and the Korea KIAT-Georgia Tech Semiconductor Electronics Center, developed a wearable device that uses light-based sensing and wireless communication to support natural sleep monitoring at home. The device is designed to collect data outside of a clinical environment, allowing researchers to study sleep in a more comfortable and realistic setting.

“This paper introduces the first soft, wireless, and non-invasive wearable near-infrared spectroscopy system capable of continuously monitoring brain water and glymphatic clearance dynamics in a natural home sleep environment, overcoming the restrictive, costly, and invasive limitations of traditional methods like MRI and polysomnography,” Yeo said.

The device works by emitting LED light at specific wavelengths. That light interacts with tissue and fluid near the brain, and reflected signals are detected by a photodetector placed on the skin. The collected data is then transmitted wirelessly via Bluetooth to a nearby device for analysis.

The researchers note that the optical measurements can be influenced by factors beyond brain-related fluid changes. Breathing depth, slight shifts in forehead pressure, body position, motion, and temperature drift can all affect the signal. 

For that reason, the team focused on changes and trends over time rather than claiming precise measurements of brain water content. They also emphasize that some of the measured signal may reflect effects from the skin, scalp, device pressure, or movement, in addition to changes associated with the brain.

By making sleep monitoring more comfortable and accessible, this soft wearable technology could help advance future studies of sleep, glymphatic activity, and brain health in real-world settings. The Wearable Intelligent Systems and Healthcare Center is supported by the Institute for Matter and Systems at Georgia Tech. 

DOI: 10.1126/sciadv.aed2056

This battle of the brains has also been playing out over the course of evolution, but not as a simple clash between old and new. 

“There was a theory proposed in the ‘50s that the brain evolved in layers starting with basic bodily functions, to emotions in the reptilian brain, leading up to sophisticated reasoning in humans,” explains Nabil Imam, an assistant professor in the School of Computational Science and Engineering and a faculty member with Georgia Tech’s Institute for Neuroscience, Neurotechnology, and Society (INNS). “This is not how an evolutionary biologist would think about the problem.”

Instead of a “new” brain layered over an “ancient” one — or even a logical brain versus an emotional one — research published in Science Advances reveals that brain evolution may come down to wiring. 

By studying the architecture of both biological and artificial brains, Imam’s team found that brain evolution is a strategic allocation of limited real estate. They propose a computational tug-of-war between two fundamentally different types of internal wiring — ones established even before birth.

This new understanding not only helps resolve a longstanding mystery in brain evolution but could also help us design more efficient AI systems.

The Problem With the “Lizard Brain”

When we refer to our “logical” or “lizard” brains, we’re really talking about different groups of brain regions. The logical brain is known as the neocortex, the brain’s outer layer responsible for vision, perception, reasoning, and other higher-level functions. For the lizard brain, the story gets a bit complicated.

“The limbic system, sometimes called the ‘reptilian brain,’ controls emotion broadly speaking — but it also has other components with distinct functions,” explains Imam. The system has separate regions for memory, smell, and navigation in addition to emotional regulation. “Why do people group all these different regions into one big system? There hasn’t been a good theory for what is common between these different circuits.”

To investigate, Imam’s team looked beyond individual regions to examine how these systems scale across species. Instead of comparing single areas based on function, the team analyzed how the limbic system and the neocortex change together across evolutionary history.

The result was remarkably consistent. When one component of the limbic system was larger, the others were also larger, while the neocortex was consistently smaller. These regions don’t vary independently. “Rather,” says Imam, “it’s a coordinated expansion of these regions across species.”

This reveals something new: The limbic system behaves not as a loose collection of functions, but as a unified network that expands and contracts as a group across evolution.

But what is driving this coordinated push and pull?

Maps Versus Barcodes

Imam argues that it comes down to how these different parts of the brain are wired before birth.

In the neocortex, neural circuits are organized as spatial maps. Areas that process touch in nearby parts of your body, like your index finger and thumb, are physically close to each other in the brain. The same is true for sight and sound. 

Wires in the limbic system, however, are not spatially organized. They function more like a bar code, firing in unique, distributed patterns to represent specific scents or complex memories.

To test whether this was an innate trait or acquired through experience, the team developed AI models for different senses. They found that when they pre-wired an AI with localized, spatial connectivity, the network was naturally very good at processing vision, sound, and touch information. Conversely, distributed, “barcode-style” networks were essential for the AI to excel at scent recognition and memory.

The Evolutionary Tug-of-War

The final piece of the puzzle explains how the size of brain components changes predictably across species. Because resources like space and energy are limited, natural selection chooses which system to prioritize.

The team simulated evolution by creating a multimodal network where the spatial and distributed domains competed for “real estate.” When the environment rewarded smell, all areas of the distributed system expanded and the neocortex shrank. When vision was rewarded, the opposite occurred.

This explains why the nine-banded armadillo, which relies on scent, has a massive limbic system, while the highly visual squirrel monkey is dominated by its neocortex. Across the 182 species studied, the research shows that brain evolution is not about adding new layers of "logic," but about strategically reallocating space between different wiring systems to support survival.

By translating this biological architecture to AI systems, engineers could create machines that learn as efficiently as the human brain, requiring far less data and energy.

“Today's artificial neural networks are trained by vast amounts data — it’s about nurture,” says Imam. “But the brain is not a blank slate that gets trained by experience. It is a mix of nature and nurture, and the nature is that pre-wired architecture.” 

“We could translate that architecture to AI systems to make it more brain-like, or make it learn or function as efficiently as the brain.”

This work was a collaboration with Cornell University and was supported by the National Science Foundation.

DOI: doi.org/10.1126/sciadv.aec6112

Artificial intelligence isn't just changing the way we think about human intelligence — it's changing the way we study the mind. "In recent years," says School of Psychology Assistant Professor Ratan Murty, "it has become very apparent to us that we have new ways to study the brain." 

Those new methods were top of mind as over 100 researchers from across Atlanta gathered for this year’s Computational Cognition Conference (CoCo Con). Hosted by Georgia Tech’s Center of Excellence in Computational Cognition (CoCo) on March 13, the conference allowed researchers from Georgia Tech and beyond working at the intersection of the mind and advanced computing to gain insights into both human cognition and artificial intelligence. 

CoCo itself is “a hub for research, education, and community” housed within the Georgia Tech School of Psychology says Robert Wilson, associate professor in Psychology and director of CoCo. Launched in 2023, the center is home to more than 50 affiliate faculty and 100 trainees across Georgia Tech, Atlanta, and beyond using computational methods to study the mind. Through chalk talks, educational programs, and conferences like CoCo Con, the center aims to rethink how we approach the study of the mind. 

The conference featured multidisciplinary talks spanning the full breadth of computation cognition — from exploration and avoidance in anxiety, what makes music memorable, the theory of mind in humans and machines, dynamic drift diffusion modeling, and the structure of memory for narratives — overall highlighting the interdisciplinary nature of the field. 

Additionally, the day featured a robust poster session highlighting work by the eight inaugural CoCo Pilot Grant recipients as well as other postdoctoral scholars, graduate students, and undergraduates doing computational cognition research at Atlanta-based institutions. In total, there were 20 posters ranging from the physics of cognition to naturalistic decision making and beyond.  

A running theme throughout the conference was the growing influence of cutting-edge technologies like artificial intelligence — and how researchers are preparing for the ethical, social and practical challenges that they bring. “The next operating system won’t run on your phone,” said DeBrae Kennedy-Mayo, senior academic professional in the Scheller College of Business and one of the conference speakers. “It will run on your brain.” With such rapidly advancing technology and the growing reach of computational cognition research, institutions like CoCo are looking to rethink the current practices of studying brain data in a modern light.  

Ending the conference was a panel discussion with researchers from across psychology, anthropology, and related fields to reflect on the future of brain research. Together, they explored what it means to do computational cognition research through the central question: What should be in the CoCo canon? 

The discussion emphasized that understanding what we are studying — and how we study it — is particularly important in an interdisciplinary field. While the narrative or canon of a field is defined by shared knowledge, skills, and history, computational cognition blurs those boundaries. Ultimately, as posed by Emory Department Chair and Professor of Anthropology Dietrich Stout, the field is “an interdisciplinary space trying to become a disciplinary space” within the vast array of sciences, technology, mathematics, and engineering.  

With or without a defined canon, the day underscored the importance of computational cognition for understanding not just how the mind works, but the future of cutting-edge technologies that shape how we approach the study of the mind. 

For most, that heart-pounding uncertainty ends the moment the foot finds solid ground. But for many individuals living with conditions like stroke or spinal cord injury (SCI), that sense of disconnect is a permanent reality.

“These conditions of course have a huge effect on our ability to move around and be independent — but the other side of it is the sensory feedback that we lose,” says Matthew Flavin, an assistant professor in the School of Electrical and Computer Engineering. Most rehabilitation treatments primarily focus on restoring movement, but “even if you have motor control, if you can’t feel when your foot's touching the ground it can be really hard for you to move around safely.” 

In a new study published in Proceedings of the National Academy of Sciences, Flavin and an interdisciplinary team of researchers introduce a way to bridge this gap: a wearable “sensory substitution” system that translates foot pressure into high-tech patterns of heat and vibration they can feel elsewhere. 

The system uses high-resolution pressure-sensing insoles designed by the team, which are placed inside a user's shoes to record how their weight shifts in real-time. This data is streamed via Bluetooth to a flexible, skin-conformable array of haptic receivers worn on the forearms, a part of the body that often retains sensation in SCI. The receivers give quick pressure feedback through vibration, while also alerting the user to longer-term pressure “hotspots” through heat. 

“One of the limitations of a lot of approaches in haptics is that you're having to map a missing sense onto a completely different sense,” says Flavin. “We’re keeping the type of information that we're missing, which is the distribution of pressure, and we're just basically putting it on a different part of their body.”

Rerouting the lost sensation was key to making the device intuitive to learn. Participants were able to correctly identify the “feel” of the ground through their arms with high accuracy within a mere two-hour session. When tested with a small group of participants with stroke or SCI, the wearable significantly improved standing balance and led to steadier walking.

“What’s encouraging about these early results is that participants appeared to use the feedback in ways that supported balance and walking,” says John Rogers, a materials science and engineering professor at Northwestern University who collaborated on this study. “Our study suggests that providing pressure information through another part of the body could be a practical path for helping people compensate for lost sensation.” 

While vibration provides immediate feedback for walking and balance, the team views the thermal feedback as a tool for long-term health. Heat is a slower, low-frequency signal that could alert patients to pressure hotspots, potentially preventing diabetic foot ulcers or pressure injuries for those who are bedridden or use wheelchairs.

The small, lightweight system is completely untethered, making it suitable for use during daily activities in and outside the clinic. It’s also highly adaptable to different injury types, which is ideal for conditions as variable as stroke, SCI, and diabetic neuropathy. Placement of the haptic receivers can be adjusted based on where a patient has the most sensation, and the sensitivity of the insoles can be tailored to each patient. 

As a member of several of Georgia Tech’s Interdisciplinary Research Institutes — the Institute for Neuroscience, Neurotechnology, and Society, the Institute for Robotics and Intelligent Machines, and the Parker H. Petit Institute for Bioengineering and Biosciences — Flavin credits the project’s success to an interdisciplinary effort and deep engagement with clinicians and patients.

“This reinforces the importance of really engaging with your stakeholders very early on,” says Flavin. “If you're not continually refining that concept with those stakeholders, you quickly find that they might be looking for something that your device isn't delivering.”

With new funding from the National Science Foundation (NSF), the team is now working to make the technology even smaller and more reconfigurable, moving closer to a standard wearable for daily clinical use.

DOI: https://doi.org/10.1073/pnas.2536577123

Jain is one of 15 scientists selected this year for “their promise to change their fields by solving nature’s puzzles in a broad range of fields and develop next-generation technologies that can reveal biological function,” according to a Searle Scholars Program press release. 

“We are honored to be part of the Searle Scholars Program,” Jain says. “For a young lab with ambitious goals, this kind of recognition means everything. It gives us the confidence and resources to pursue high-risk, high-reward questions that could one day make a real difference for people affected by neurodevelopmental disorders.”

Jain received his Ph.D. in molecular and cellular biology from the University of Arizona and completed his postdoctoral work at the University of California, Los Angeles. He joined Georgia Tech in 2024.

Presented across multiple institutes, colleges, and campus programs, these honors celebrate faculty whose work advances discovery, education, and societal impact at Georgia Tech and beyond.

“INNS is built around the idea that solving complex challenges requires excellence across disciplines and domains,” said Christopher Rozell, INNS executive director and professor in the School of Electrical and Computer Engineering. “These awardees exemplify that vision through their leadership in research, teaching, and service. We are proud to recognize the contributions our affiliates are making across campus.”

Considered among Georgia Tech’s most competitive internal honors, these awards rely on peer‑driven selection processes that highlight innovation, mentorship, and measurable impact. This year’s recipients include faculty recognized for strengthening major research initiatives, advancing undergraduate education, and fostering interdisciplinary scholarship.

Another form of Institute recognition are tenure promotions. INNS is pleased to celebrate several faculty awarded tenure this spring, reflecting their sustained contributions to research, teaching, and leadership at Georgia Tech.

INNS Affiliated Award Recipients

Outstanding Achievement in Research Program Impact Award

Justin Biddle
Associate Professor, Jimmy and Rosalynn Carter School of Public Policy, Ivan Allen College of Liberal Arts

Recognizes a faculty‑ and staff‑led research team whose innovative program has significantly expanded Georgia Tech’s research portfolio, demonstrating measurable impact, broad influence, and meaningful engagement with external partners across academic, industry, and community sectors.

Undergraduate Educator Award

Tiffiny Hughes‑Troutman
Professor of the Practice, School of Psychology, College of Sciences

Honors excellence in undergraduate education and impactful teaching practices that support student learning and engagement.

Excellence in Teaching Recognition: Annual CIOS Award

Katharine McCann
Director of Undergraduate Research in Neuroscience, Undergraduate Degree Program in Neuroscience, College of Sciences

Recognized for excellence in teaching NEUR 4803: Special Topics – Neuroscience of Addiction, highlighting innovative and engaging approaches to neuroscience education.

Junior Faculty Outstanding Undergraduate Research Mentor Award

Farzaneh Najafi
Assistant Professor, School of Biological Sciences, College of Sciences

Honors exceptional mentorship of undergraduate researchers and a strong commitment to fostering student‑driven scholarship and research engagement.

Outstanding Undergraduate Academic Advisor – Faculty Advisor

Haley Steele
Director of Communication, Undergraduate Degree Program in Neuroscience, College of Sciences

Recognizes excellence in undergraduate advising through dedicated student support, clear communication, and program leadership within the neuroscience major.

Class of 1934 Outstanding Interdisciplinary Activities Award

Jennifer Singh
Associate Chair and Associate Professor, School of History and Sociology, Ivan Allen College of Liberal Arts

Honors leadership in interdisciplinary teaching, research, and service that bridges disciplinary boundaries and advances cross‑cutting scholarship.

Click to view other award recipients for institute research awards, excellence in teaching awards, and faculty and staff awards.

Newly Tenured or Promoted INNS Faculty Affiliates

Promoted to Professor

Patrick T. McGrath, School of Biological Sciences, College of Sciences

Awarded Tenure

• Hannah Choi, School of Mathematics, College of Sciences
• Christopher MacLellan, School of Interactive Computing, College of Computing
• Leandro Miletto Tonetto, School of Industrial Design, College of Design
• Hongchen Wu, School of Modern Languages, Ivan Allen College of Liberal Arts

Click to view all newly promoted faculty.

At Georgia Tech, undergraduate students are an integral part of the research enterprise – particularly when it comes to neuroscience. That dedication to undergraduate research was on full display on April 8, when more than 100 students from Atlanta-area universities gathered for the annual ATL Neuro Networking and Symposium Night. 

To help find answers, researchers at the Institute for Neuroscience, Neurotechnology, and Society (INNS) are using math, data, and AI to unlock the secrets of thought. Together they are helping turn the brain’s raw electrical “noise” into real insights about how people think, move, and perceive the world.

Fair warning: Prepare your neurons for the complexity of this brain research ahead.

Building AI Like a Brain

What if artificial neurons in AI programs were arranged as they are in the brain?

AI programs would then help us understand why the brain is organized the way it is. This neuro-AI synthesis would also work faster, use less energy, and be easier to interpret. Creating such systems is the goal of Apurva Ratan Murty, an assistant professor of Psychology who is creating topographic AI models like the one above of three domains — vision, audition, and language inspired by the brain. In the near future, he predicts doctors might be able to use these patterns to predict the effects of brain lesions and other disorders. “We’re not there yet,” he says. “But our work brings us significantly closer to that future than ever before.”

Computing Thought and Movement

How cats walk keeps Chethan Pandarinath on his toes. This biomedical engineer uses sensors to analyze how two sets of feline leg muscles — flexors and extensors — are controlled by the spinal cord. Understanding how that happens could help patients partially paralyzed from spinal cord injuries, strokes, or progressive neuro-degenerative diseases get back on their feet again. “My lab is using AI tools that allow us to turn complex spinal cord activity data into something we can interpret. It tells us there’s a simple underlying structure behind the complex activity patterns,” says the associate professor.

Revealing the Brain’s Spike Patterns

“The brain is like a symphony conductor,” says Simon Sponberg. “Individual instruments have some independent control, but most of the music comes from the brain’s precise coordination of notes among the different players in the body.” This physics professor studies the fantastically fast-beating wings of the hummingbird-sized hawk moth (Manduca sexta). Its agile flight movement comes as a result of spikes in electrical activity in 10 muscles. Sponberg found something that surprised him — the brain focuses less on creating the number of spikes than in orchestrating their precise patterns over time. To Sponberg, every millisecond matters. “We are just beginning to understand how the nervous system first acquires precisely timed spiking patterns during development,” he says.

Predicting Decisions Through Statistics

Put a mouse in a maze with food far away, and it will learn to find it. But life for mice — and people — isn’t so simple. Sometimes they want to explore, only want water, or just want to go home. What’s more, animals make decisions based on their history, not just on how they feel at the moment. To dig deeper into the decision-making process, Anqi Wu, an assistant professor in the School of Computational Science and Engineering, is giving mice more options. By using a new computational framework called SWIRL (Switching Inverse Reinforcement Learning), her findings have outperformed models that fail to take historical behavior into account. “We’re seeking to understand not only animal behavior but also human behavior to gain insight into the human decision-making process over a long period of time,” she says.

Modeling the Mind’s Wiring With Math

Connectivity shapes cognition in the cerebral cortex, a layered structure in the brain. The visual cortex, in particular, processes visual data from the retina relayed through the Lateral Geniculate Nucleus (LGN) in the thalamus, and directs it to the correct cognitive domain in the brain. How it does this is the mystery that computational neuroscientist Hannah Choi wants to solve. “The big question I’m interested in is how network connectivity patterns in the architecture of the LGN are related to computations,” says this assistant math professor. To find answers, she shows mice repeated image patterns such as flower-cat-dog-house and then disrupts the pattern. The goal? To grasp how the thalamus’s nonlinear dynamical system works. If scientists and doctors better understand how brain regions are wired together, such knowledge could lead to better disease treatment.

This story was originally published through the Georgia Tech Alumni Magazine. Read the original publication here.

Artificial intelligence has been touted as the most transformative technology of our time. With only a few years of mainstream use, it’s changed how we work and communicate, generated billions of dollars in investments, and sparked global debate. But according to leading neuroethics expert Karen Rommelfanger, the race isn’t over yet. 

“Can you think of a more transformative technology than one that intervenes with the fundamental organ that drives your experience in the world?” 

That fundamental organ is the brain.  

Technologies interfacing directly with the brain have been reserved for treating severe injury or disease for decades. Now, neurotechnology is expanding into brain-responsive wearables meant to enhance, augment, and monitor everyday life. As these technologies accelerate and AI is incorporated, the question is no longer if neurotechnology will transform society, but how — and who will shape the boundaries. 

These are some of the questions on which Karen Rommelfanger has built her career. Trained as a biomedical researcher and neuroscientist, Rommelfanger went on to found the Institute for Neuroethics, the world’s first think and do tank devoted entirely to neuroethics, public engagement, and policy implementation.  

“The brain is special; it’s central to who we are,” says Rommelfanger, who was also an inaugural recipient of the Dana Foundation Neuroscience and Society Award. “And that means when you intervene with the brain, there are unique responsibilities. The field of neuroethics addresses things like: How do you ensure mental privacy? How do you protect free will? How do you ensure that people have the power to be narrators of their own lives and their cognitive experience?” 

Now, Rommelfanger is joining Georgia Tech’s Institute for Neuroscience, Neurotechnology, and Society (INNS) as a professor of the practice, where she will work to further embed neuroethics into Georgia Tech’s research and technology development ecosystem. 

“Georgia Tech is producing the next generation of neurotechnologists, and Karen’s expertise will help ensure we’re preparing them to think about societal impact as deeply as they think about the technical and scientific aspects of their work,” says Christopher Rozell, executive director of INNS. “Her leadership strengthens the Institute in exactly the way this moment in neurotechnology demands.”  

“Georgia Tech has many, many ways that it leads in the technology ecosystem. But one of the powerful, unique ways it can lead is through neurotechnology,” says Rommelfanger. “I hope that the INNS, given its unique mandate for neuroscience, neurotechnology, and society, can be a lighthouse for these types of conversations.” 

Neuroethics by Design 

Health and medicine is more than just biological – societal forces can get under your skin and cause illness. Medical sociologists like me study these forces by treating society itself as our laboratory. Health and illness are our experiments in uncovering meaning, power and inequality, and how it affects all parts of a person’s life.

For example, why do low-income communities continue to have higher death rates, despite improved social and environmental conditions across society? Foundational research in medical sociology reveals that access to resources like money, knowledge, power and social networks strongly affects a person’s health. Medical sociologists have shown that social class is linked to numerous diseases and mortality, including risk factors that influence health and longevity. These include smoking, overweight and obesity, stress, social isolation, access to health care and living in disadvantaged neighborhoods.

Moreover, social class alone cannot explain such health inequalities. My own research examines how inequalities related to social class, race and gender affect access to autism services, particularly among single Black mothers who rely on public insurance. This work helps explain delays in autism diagnosis among Black children, who often wait three years after initial parent concerns before they are formally diagnosed. White children with private insurance typically wait from 9 to 22 months depending on age of diagnosis. This is just one of numerous examples of inequalities that are entrenched in and deepened by medical and educational systems.

Medical sociologists like me investigate how all of these factors interact to affect a person’s health. This social model of illness sees sickness as shaped by social, cultural, political and economic factors. We examine both individual experiences and societal influences to help address the health issues affecting vulnerable populations through large-scale reforms.

By studying the way social forces shape health inequalities, medical sociology helps address how health and illness extend beyond the body and into every aspect of people’s lives.

Origins of Medical Sociology in the US

Medical sociology formally began in the U.S after World War II, when the National Institutes of Health started investing in joint medical and sociological research projects. Hospitals began hiring sociologists to address questions like how to improve patient compliance, doctor-patient interactions and medical treatments.

However, the focus of this early work was on issues specific to medicine, such as quality improvement or barriers to medication adherence. The goal was to study problems that could be directly applied in medical settings rather than challenging medical authority or existing inequalities. During that period, sociologists viewed illness mostly as a deviation from normal functioning leading to impairments that require treatment.

For example, the concept of the sick role – developed by medical sociologist Talcott Parsons in the 1950s – saw illness as a form of deviance from social roles and expectations. Under this idea, patients were solely responsible for seeking out medical care in order to return to normal functioning in society.

In the 1960s, sociologists began critiquing medical diagnoses and institutions. Researchers criticized the idea of the sick role because it assumed illnesses were temporary and did not account for chronic conditions or disability, which can last for long periods of time and do not necessarily allow people to deviate from their life obligations. The sick role assumed that all people have access to medical care, and it did not take into account how social characteristics like race, class, gender and age can influence a person’s experience of illness.

Parsons’ sick role concept also emphasized the expertise of the physician rather than the patient’s experience of illness. For example, sociologist Erving Goffman showed that the way care is structured in asylums shaped how patients are treated. He also examined how the experience of stigma is an interactive process that develops in response to social norms. This work influenced how researchers understood chronic illness and disability and laid the groundwork for later debates on what counts as pathological or normal.

In the 1970s, some researchers began to question the model of medicine as an institution of social control. They critiqued how medicine’s jurisdiction expanded over many societal problems – such as old age and death – which were defined and treated as medical problems. Researchers were critical of the tendency to medicalize and apply labels like “healthy” and “ill” to increasing parts of human existence. This shift emphasized how a medical diagnosis can carry political weight and how medical authority can affect social inclusion or exclusion.

The critical perspective aligns with critiques from disability studies. Unlike medical sociology, which emerged through the medical model of disease, disability studies emerged from disability rights activism and scholarship. Rather than viewing disability as pathological, this field sees disability as a variation of the human condition rooted in social barriers and exclusionary environments. Instead of seeking cures, researchers focus on increasing accessibility, human rights and autonomy for disabled people.

A contemporary figure in this field was Alice Wong, a disability rights activist and medical sociologist who died in November 2025. Her work amplified disabled voices and helped shaped how the public understood disability justice and access to technology.

Structural Forces Shape Health and Illness

By focusing on social and structural influences on health, medical sociology has contributed significantly to programs addressing issues like segregation, discrimination, poverty, unemployment and underfunded schools.

For example, sociological research on racial health disparities invite neighborhood interventions that can help improve overall quality of life by increasing the availability of affordable nutritious foods in underserved neighborhoods or initiatives that prioritize equal access to education. At the societal level, large-scale social policies such as guaranteed minimum incomes or universal health care can dramatically reduce health inequalities.

Medical sociology has also expanded the understanding of how health care policies affect health, helping ensure that policy changes take into account the broader social context. For example, a key area of medical sociological research is the rising cost of and limited access to health care. This body of work focuses on the complex social and organizational factors of delivering health services. It highlights the need for more state and federal regulatory control as well as investment in groups and communities that need care the most.

Modern medical sociology ultimately considers all societal issues to be health issues. Improving people’s health and well-being requires improving education, employment, housing, transportation and other social, economic and political policies.

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

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Moderated by IMS Executive Director Eric Vogel, the panel explored how innovation, regulation, economics and clinical realities intersect to shape the future of medical devices. 

The panel featured Jon Duke, physician and director of the Center for Health Analytics and Informatics at Georgia Tech Research Institute; Matthew Flavin, assistant professor in the School of Electrical and Computer Engineering; HyunJoo Oh, assistant professor in the schools of Industrial Design and Interactive Computing; and Lokesh Guglani, pediatric pulmonologist and clinician-researcher at Children’s Healthcare of Atlanta. 

Vogel opened the event by highlighting the gap between technological novelty and real-world medical adoption. 

“About 75% of medical device start-ups never achieve commercial success or make it to market, and some industry estimates push this higher,” Vogel said. “Even those that reach the market often fail to gain meaningful adoption. This may be because technologists optimize for platforms five or 10 years out and are rewarded by novelty, whereas clinicians demand reliability, interpretability, and outcomes that hold up with real patients, real workflows, and real liability.”

Throughout the discussion, panelists examined the balance between rapid innovation and clinical safety, noting that the level of invasiveness often determines how bold developers can be.

“We must remember that in medicine—and especially when we're dealing with human lives—there's a significant asymmetry of the harm that could be done,” said Guglani. “Even a small change or an oversight at the design level of a medical device can have significant downstream repercussions for patients and create liability for institutions and providers.”

Flavin and Duke added that excessive conservatism, particularly around non-invasive wearable, can also slow potentially life-changing advancements. 

All panelists agreed that breakthrough technology alone is not enough to ensure clinical adoption. Usability, workflow fit, and time efficiency often determine whether clinicians adopt a device. Tools that require lengthy calibration or add to a clinician’s already tight schedule rarely succeed. Even when a technology integrates well, reimbursement barriers can prevent adoption. 

 “A lot of technologies come out, but then if the clinic is using them and is not being reimbursed for the time spent, that creates a bottleneck,” said Guglani.

Economic constraints also shape who benefits from innovation. Children with rare diseases, stroke survivors, and other small or heterogeneous patient groups often struggle to attract investors, even when their needs are urgent.

The panelists also discussed the dual role of regulatory and manufacturing standards. Good Manufacturing Practice (GMP) requirements ensures consistent, safe production, but force teams to lock designs earlier than ideal, adding cost and slowing iteration. These requirements protect patients but also function as an economic filter for many early-stage technologies.

The conversation then turned to data, AI, and the education of future innovators. Despite massive amounts of health data, many clinically important areas remain data‑scarce. Wearable devices, such as smart watches, may help close these gaps, but AI models remain limited by the quality of input data. 

When asked about preparing the next generation of MedTech innovators, panelists emphasized the importance of “interface literacy” or the ability to collaborate across disciplinary boundaries and understand how design decisions cascade into real clinical environments.  

“You really do have to be able to be interdisciplinary,” said Duke. “Now of course what makes things go is not often the knowledge of the domain, but the person’s role or connectivity into the system.”

Vogel closed by emphasizing that successful medical technology development requires “ongoing, honest collaboration” across fields. The Boundaries and Breakthroughs series will continue that mission in February with a panel on the future of the electric grid.

Despite the nursery rhyme about three blind mice, mouse eyesight is surprisingly sensitive. Studying how mice see has helped researchers discover unprecedented details about how individual brain cells communicate and work together to create a mental picture of the visual world.

I am a neuroscientist who studies how brain cells drive visual perception and how these processes can fail in conditions such as autism. My lab “listens” to the electrical activity of neurons in the outermost part of the brain called the cerebral cortex, a large portion of which processes visual information. Injuries to the visual cortex can lead to blindness and other visual deficits, even when the eyes themselves are unhurt.

Understanding the activity of individual neurons – and how they work together while the brain is actively using and processing information – is a long-standing goal of neuroscience. Researchers have moved much closer to achieving this goal thanks to new technologies aimed at the mouse visual system. And these findings will help scientists better see how the visual systems of people work.

The Mind in the Blink of an Eye

Researchers long thought that vision in mice appeared sluggish with low clarity. But it turns out visual cortex neurons in mice – just like those in humans, monkeys, cats and ferrets – require specific visual features to trigger activity and are particularly selective in alert and awake conditions.

My colleagues and I and others have found that mice are especially sensitive to visual stimuli directly in front of them. This is surprising, because mouse eyes face outward rather than forward. Forward-facing eyes, like those of cats and primates, naturally have a larger area of focus straight ahead compared to outward-facing eyes.

This finding suggests that the specialization of the visual system to highlight the frontal visual field appears to be shared between mice and humans. For mice, a visual focus on what’s straight ahead may help them be more responsive to shadows or edges in front of them, helping them avoid looming predators or better hunt and capture insects for food.

Importantly, the center of view is most affected in aging and many visual diseases in people. Since mice also rely heavily on this part of the visual field, they may be particularly useful models to study and treat visual impairment.

A Thousand Voices Drive Complicated Choices

Advances in technology have greatly accelerated scientific understanding of vision and the brain. Researchers can now routinely record the activity of thousands of neurons at the same time and pair this data with real-time video of a mouse’s face, pupil and body movements. This method can show how behavior interacts with brain activity.

It’s like spending years listening to a grainy recording of a symphony with one featured soloist, but now you have a pristine recording where you can hear every single musician with a note-by-note readout of every single finger movement.

Using these improved methods, researchers like me are studying how specific types of neurons work together during complex visual behaviors. This involves analyzing how factors such as movement, alertness and the environment influence visual activity in the brain.

For example, my lab and I found that the speed of visual signaling is highly sensitive to what actions are possible in the physical environment. If a mouse rests on a disc that permits running, visual signals travel to the cortex faster than if the mouse views the same images while resting in a stationary tube – even when the mouse is totally still in both conditions.

In order to connect electrical activity to visual perception, researchers also have to ask a mouse what it thinks it sees. How have we done this?

The last decade has seen researchers debunking long-standing myths about mouse learning and behavior. Like other rodents, mice are also surprisingly clever and can learn how to “tell” researchers about the visual events they perceive through their behavior.

For example, mice can learn to release a lever to indicate they have detected that a pattern has brightened or tilted. They can rotate a Lego wheel left or right to move a visual stimulus to the center of a screen like a video game, and they can stop running on a wheel and lick a water spout when they detect the visual scene has suddenly changed.

Mice can also use visual cues to focus their visual processing to specific parts of the visual field. As a result, they can more quickly and accurately respond to visual stimuli that appear in those regions. For example, my team and I found that a faint visual image in the peripheral visual field is difficult for mice to detect. But once they do notice it – and tell us by licking a water spout – their subsequent responses are faster and more accurate.

These improvements come at a cost: If the image unexpectedly appears in a different location, the mice are slower and less likely to respond to it. These findings resemble those found in studies on spatial attention in people.

My lab has also found that particular types of inhibitory neurons – brain cells that prevent activity from spreading – strongly control the strength of visual signals. When we activated certain inhibitory neurons in the visual cortex of mice, we could effectively “erase” their perception of an image.

These kinds of experiments are also revealing that the boundaries between perception and action in the brain are much less separate than once thought. This means that visual neurons will respond differently to the same image in ways that depend on behavioral circumstances – for example, visual responses differ if the image will be successfully detected, if it appears while the mouse is moving, or if it appears when the mouse is thirsty or hydrated.

Understanding how different factors shape how cortical neurons rapidly respond to visual images will require advances in computational tools that can separate the contribution of these behavioral signals from the visual ones. Researchers also need technologies that can isolate how specific types of brain cells carry and communicate these signals.

Data Clouds Encircling the Globe

This surge of research on the mouse visual system has led to a significant increase in the amount of data that scientists can not only gather in a single experiment but also publicly share among each other.

Major national and international research centers focused on unraveling the circuitry of the mouse visual system have been leading the charge in ushering in new optical, electrical and biological tools to measure large numbers of visual neurons in action. Moreover, they make all the data publicly available, inspiring similar efforts around the globe. This collaboration accelerates the ability of researchers to analyze data, replicate findings and make new discoveries.

Technological advances in data collection and sharing can make the culture of scientific discovery more efficient and transparent – a major data informatics goal of neuroscience in the years ahead.

If the past 10 years are anything to go by, I believe such discoveries are just the tip of the iceberg, and the mighty and not-so-blind mouse will play a leading role in the continuing quest to understand the mysteries of the human brain.

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

Current cybersecurity approaches have been shown to be insufficient in blocking sophisticated attacks aimed at networked robotic motion-control systems.

To address this gap, Jun Ueda, Professor and ASME Fellow in the George W. Woodruff School of Mechanical Engineering at Georgia Tech, has been awarded approximately $700,000 by the National Science Foundation to establish methods to enhance cybersecurity for networked motion-control system. The research will focus on the unique geometric vulnerabilities in networked robotic systems and stealthy false data injection attacks that exploit geometric coordinate transformations to maintain mathematical consistency in robotic dynamics while altering physical world behavior.

Using an interdisciplinary approach that will combine research methodology from system dynamics, control, communication, differential geometry and cybersecurity engineering, Ueda hopes to establish new mathematical tools for analyzing robotic security and develop safer networked robotic systems that successfully repel system intrusion, manipulation attacks, and attacks that mislead operators. 

This article refers to NSF Program Foundational Research in Robotics (FRR) Award # 2112793 
A Geometric Approach for Generalized Encrypted Control of Networked Dynamical Systems

That question matters as artificial intelligence (AI) spreads into everything from customer service to self-driving cars. These autonomous agents often have human names — Alexa or Claude, for example — and speak conversationally, but too much familiarity can backfire. Earlier this year, OpenAI scaled down its “sycophantic” ChatGPT model, which could cause problems for users with mental health issues. 

New research from Georgia Tech suggests that users may like more personable AI, but they are more likely to obey AI that sounds robotic. While following orders from Siri may not be critical, many AI systems, such as robotic guide dogs, require human compliance for safety reasons. 

These surprising findings are from research by Sidney Scott-Sharoni, who recently received her Ph.D. from the School of Psychology. Despite years of previous research suggesting people would be socially influenced by AI they liked, Scott-Sharoni’s research showed the opposite. 

“Even though people rated humanistic agents better, that didn't line up with their behavior,” she said. 

Likability vs. Reliability 

Scott-Sharoni ran four experiments. In the first, participants answered trivia questions, saw the AI’s response, and decided whether to change their answer. She expected people to listen to agents they liked.

“What I found was that the more humanlike people rated the agent, the less they would change their answer, so, effectively, the less they would conform to what the agent said,” she noted.

Surprised, Scott-Sharoni studied moral judgments with an AI voice agent next. For example, participants decided how to handle being undercharged on a restaurant bill. 

Once again, participants liked the humanlike agent better but listened to the robotic agent more. The unexpected pattern led Scott-Sharoni to explore why people behave this way.

Bias Breakthrough

Why the gap? Scott-Sharoni’s findings point to automation bias — the tendency to see machines as more objective than humans.

Scott-Sharoni continued to test this with a third experiment focused on the prisoner’s dilemma, where participants cooperate with or retaliate against authority. In her task, participants played a game against an AI agent. 

“I hypothesized that people would retaliate against the humanlike agent if it didn’t cooperate,” she said. “That’s what I found: Participants interacting with the humanlike agent became less likely to cooperate over time, while those with the robotic agent stayed steady.”

The final study, a self-driving car simulation, was the most realistic and troubling for safety concerns. Participants didn’t consistently obey either agent type, but across all experiments, humanlike AI proved less effective at influencing behavior.

Designing the Right AI

The implications are pivotal for AI engineers. As AI grows, designers may cater to user preferences — but what people want isn’t always best.

“Many people develop a trusting relationship with an AI agent,” said Bruce Walker, a professor of psychology and interactive computing and Scott-Sharoni’s Ph.D. advisor. “So, it’s important that developers understand what role AI plays in the social fabric and design technical systems that ultimately make humans better. Sidney's work makes a critical contribution to that ultimate goal.” 

When safety and compliance are the point, robotic beats relatable.

Georgia Tech’s Executive Vice President for Research search committee has selected three finalists. Each candidate will visit campus and present a seminar sharing their broad vision for the Institute's research enterprise. The seminars are open to all faculty, students, and staff across the campus community. Interested individuals can attend in person or register to participate via Zoom (pre-registration is required).    

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The new institutes focus on expanding breakthroughs in neuroscience and space, two areas where research and federal funding are anticipated to remain strong. Both fields are poised to influence research in everything from healthcare and ethics to exploration and innovation. This expansion of Georgia Tech’s research enterprise represents the Institute’s commitment to research that will shape the future.

“At Georgia Tech, innovation flourishes where disciplines converge. With the launch of the Space Research Institute and the Institute for Neuroscience, Neurotechnology, and Society, we’re uniting experts across fields to take on some of humanity’s most profound questions. Even as we are tightening our belts in anticipation of potential federal R&D budget actions, we also are investing in areas where non-federal funding sources will grow and where big impacts are possible,” said Executive Vice President for Research Tim Lieuwen. "These institutes are about advancing knowledge — and using it to improve lives, inspire future generations, and help shape a better future for us all.”

Both INNS and SRI grew out of faculty-led initiatives shaped by a strategic planning process and campus-wide collaboration. Their evolution into formal institutes underscores the strength and momentum of Georgia Tech’s interdisciplinary research enterprise. 

Georgia Tech’s 11 IRIs support collaboration between researchers and students across the Institute’s seven colleges, the Georgia Tech Research Institute (GTRI), national laboratories, and corporate entities to tackle critical topics of strategic significance for the Institute as well as for local, state, national, and international communities.

"IRIs bring together Georgia Tech researchers making them more competitive and successful in solving research challenges, especially across disciplinary boundaries,” said Julia Kubanek, vice president of interdisciplinary research. “We're making these new investments in neuro- and space-related fields to publicly showcase impactful discoveries and developments led by Georgia Tech faculty, attract new partners and collaborators, and pursue alternative funding strategies at a time of federal funding uncertainty."

The Space Research Institute

The Space Research Institute will connect faculty, students, and staff who share a passion for space exploration and discovery. They will investigate a wide variety of space-related topics, exploring how space influences and intersects with the human experience. The SRI fosters a collaborative community including scientific, engineering, cultural, and commercial research that pursues broadly integrated, innovative projects.

SRI is the hub for all things space-related at Georgia Tech. It connects the Institute’s schools, colleges, research institutes, and labs to lead conversations about space in the state of Georgia and the world. Working in partnership with academics, business partners, philanthropists, students, and governments, Georgia Tech is committed to staying at the forefront of space-related innovation.   

The SRI will build upon the collaborative work of the Space Research Initiative, the first step in formalizing Georgia Tech’s broad interdisciplinary space research community. The Initiative brought together researchers from across campus and was guided by input from Georgia Tech stakeholders and external partners. It was led by an executive committee including Glenn Lightsey, John W. Young Chair Professor in the Daniel Guggenheim School of Aerospace Engineering; Mariel Borowitz, associate professor in the Sam Nunn School of International Affairs; and Jennifer Glass, associate professor in the School of Earth and Atmospheric Sciences. Beginning July 1, W. Jud Ready, a principal research engineer in GTRI’s Electro-Optical Systems Laboratory, will serve as the inaugural executive director of the Space Research Institute.

To receive the latest updates on space research and innovation at Georgia Tech, join the SRI mailing list. 

The Institute for Neuroscience, Neurotechnology, and Society

The Institute for Neuroscience, Neurotechnology, and Society (INNS) is dedicated to advancing neuroscience and neurotechnology to improve society through discovery, innovation, and engagement. INNS brings together researchers from neuroscience, engineering, computing, ethics, public policy, and the humanities to explore the brain and nervous system while addressing the societal and ethical dimensions of neuro-related research.

INNS builds on a foundation established over a decade ago, which first led to the GT-Neuro Initiative and later evolved into the Neuro Next Initiative. Over the past two years, this effort has culminated in the development of a comprehensive plan for an IRI, guided by an executive committee composed of faculty and staff from across Georgia Tech. The committee included Simon Sponberg, Dunn Family Associate Professor in the School of Physics and the School of Biological Sciences; Christopher Rozell, Julian T. Hightower Chaired Professor in the School of Electrical and Computer Engineering; Jennifer Singh, associate professor in the School of History and Sociology; and Sarah Peterson, Neuro Next Initiative program manager. Their leadership shaped the vision for a research community both scientifically ambitious and socially responsive.

INNS will serve as a dynamic hub for interdisciplinary collaboration across the full spectrum of brain-related research — from biological foundations to behavior and cognition, and from fundamental research to medical innovations that advance human flourishing. Research areas will encompass the foundations of human intelligence and movement, bio-inspired design and neurotechnology development, and the ethical dimensions of a neuro-connected future. 

By integrating technical innovation with human-centered inquiry, INNS is committed to ensuring that advances in neuroscience and neurotechnology are developed and applied ethically and responsibly. Through fostering innovation, cultivating interdisciplinary expertise, and engaging with the public, the institute seeks to shape a future where advancements in neuroscience and neurotechnology serve the greater good. INNS also aims to deepen Georgia Tech’s collaborations with clinical, academic, and industry partners, creating new pathways for translational research and real-world impact.

An internal search for INNS’s inaugural executive director is in the final stages, with an announcement expected soon.

Join our mailing list to receive the latest updates on everything neuro at Georgia Tech.

Their findings, published this month in the journal Science, help explain how small particle pollution — think industrial emissions and car exhaust, wildfires and burning wood for heat and cooking — can lead to Lewy body dementia, a devastating disease that causes toxic clumps of protein to destroy nerve cells in the brain. 

"Epidemiological studies have suggested a strong link between air pollution and dementia, but what sets this study apart is that we also provide a convincing biological mechanism,” says Pengfei Liu, assistant professor School of Earth and Atmospheric Sciences and one of the study’s co-authors. “This collaborative work shows that fine particulate matter from different geographic regions consistently triggers a specific stain of misfolded protein that drives Lewy body dementia." 

The work has “profound implications” for helping scientists and policy makers better understand measures to prevent this type of dementia, which is among the most common forms of the disease and affects millions of people around the world.

Along with Liu, the research team from Georgia Tech includes Rodney Weber, professor in the School of Earth and Atmospheric Sciences; Minhan Park, a postdoctoral research fellow co-advised by Liu and Weber; Bin Bai, a graduate student in Liu’s lab; and Ma Cristine Faye Denna, a graduate student in Weber’s lab.

“Figuring out how exposure to atmospheric aerosols might be linked to dementia, and what mechanisms are involved, is a complex and challenging problem — and as this study shows, it takes a large team with many different areas of expertise,” Weber adds.

Learn more:

• Science: Lewy body dementia promotion by air pollutants
• Johns Hopkins Medicine newsroom
• Columbia University newsroom
• Press: The Guardian

Imagine stepping into a space the size of multiple football fields — only instead of turf and goalposts, it’s filled with science. Every inch is alive with posters, equipment demos, and researchers sharing the latest breakthroughs.  

In his lab, Quiroz engineers the invisible through proteins, cells, and genes to understand what is fundamentally happening inside the cell. The five-year-old lab, soon to celebrate its first cohort of graduates, brings together bioengineers, neuroscientists, chemists, and biologists working at the intersection of disciplines. His work is about impact today and for generations to come, driven by a motivation to build bridges between fields, ideas, and people. Guided by a high-risk, high-reward mentality, Quiroz’s research opens countless potential paths, advancing his field, defining new ones, and inspiring the next generation to develop the technologies of tomorrow.

Quiroz was recently featured on BME's Holy Shift! Podcast, where he revealed how his lab engineers the invisible — proteins, cells, and genes — to understand and treat diseases like Alzheimer’s. 

Listen to the full episode here >>

“I realized from the International Baccalaureate program in high school that I really liked research and writing about my findings, so I wanted to hit the ground running,” Barrow said. “A couple of the other schools I considered didn’t have as fully developed a program as Georgia Tech.”

Since her first year at the Institute, Barrow has worked in School of Psychology Professor Eric Schumacher’s cognitive neuroscience lab, where she is now the lab manager. Her experience enabled her to work in three other labs over three summers. These research opportunities prepared Barrow, now in her final semester, to apply for neuroscience Ph.D. programs. She hopes to study computational psychiatry, which applies basic neuroscience concepts to computational modeling, enabling better predictions and diagnoses of neurodegenerative disorders, like MS, and clinical disorders.

Barrow is one of more than 100 Georgia Tech undergraduates who conduct neuroscience research every year. They lend their perspective to nearly 70 labs across campus, which are often led by faculty in the Institute for Neuroscience, Neurotechnology, and Society (INNS).

Connecting Across Campus

Students work in labs in almost all seven of the Institute’s Colleges, but they can also conduct research at places like Emory University or the Shepherd Center. 

“Having the chance to engage in hands-on scientific discovery in a research laboratory is often a richer, deeper experience than a classroom,” said Schumacher, who also directs the undergraduate neuroscience program. “Making those discoveries is why scientists are interested in science, so giving undergraduates an opportunity to do that is critical for a successful program.”

Finding the right lab is paramount in this process. As director of undergraduate research in neuroscience, Katharine McCann helps connect students to the right research opportunities, whether by emailing labs to see if there are openings or coordinating a networking night for students to meet researchers in labs.

“One of the reasons undergraduate neuroscience research is so robust at Georgia Tech is that there's neuroscience research happening in nearly every College on campus,” said McCann. “Most of our students are placed in the College of Sciences or the College of Engineering, but we have students who are in the College of Computing and the Ivan Allen College of Liberal Arts, too.” 

The undergraduate presence is just as much of a benefit to the lab, according to Schumacher. Often, these students bring a new outlook, as well as solid basic science skills that reinvigorate a lab’s energy. 

Embedding Research in Everything

Neuroscience is one of the most interdisciplinary majors on campus. Students take courses ranging from biology to computation, and because they gain both broad knowledge and deep research experience, neuroscience has become one of Georgia Tech’s fastest-growing majors. This combination prepares them for careers in science, technology, and even fields such as medicine and dentistry.

“For neuroscience, we require students to take chemistry, physics, math, and biology, so they’re well-rounded critical thinkers,” said Tim Cope, a professor in the School of Biological Sciences andthe Wallace H. Coulter Department of Biomedical Engineering. Cope previously ran the neuroscience undergraduate program and now directs the neuroscience and neurotechnology Ph.D. program. “Neuroscience is one of the most pressing societal topics right now. Not a day goes by in our lives that there's not something in the news about addiction, depression, or Parkinson’s, and these neuroscience students could be at the forefront of improving people’s lives.”

Building the Future of Neuroscience 

Fourth-year neuroscience student Lynn Kim joined biological sciences Professor Young-Hui Chang’s Comparative Neuromechanics Lab in her first year. She studied how the nervous system adapts to a novel gravity environment through a reduced gravity simulator that mirrors the body weight support system. For her thesis, she explored the role of vision in coordinating sense and motor function, analyzing changes in movements, muscle activity, and cognitive perception of gravity.

“I believe my projects will provide valuable insights to both neuroscience research and applied rehabilitation science, while preparing me to pursue a career dedicated to improving patient outcomes through research,” Kim said.

Georgia Tech leads in neuroscience research at every level. From students who are performing their first experiments to interdisciplinary institutes like INNS, Georgia Tech is building a neuroscience pipeline that starts early and runs deep.

“When people think of robots, they usually imagine something like The Terminator or RoboCop: big, rigid, and made of metal,” said Hong Yeo, the G.P. “Bud” Peterson and Valerie H. Peterson Professor in the George W. Woodruff School of Mechanical Engineering. “But what we’re developing is the opposite. These artificial muscles are soft, flexible, and responsive — more like human tissue than machine.”

Yeo’s latest study, published in Materials Horizons, explores AI-powered muscles made from lifelike materials paired with intelligent control systems. The technology learns from the body and adapts in real time, creating motion that feels natural, responsive, and safe enough to support recovery.
 

Muscles That Think, Materials That Feel

Traditional robotics relies on steel, wires, and motors, but rarely captures the nuances of human motion. Yeo’s research takes a different approach. He uses hierarchically structured fibers, which are flexible materials built in layers, much like muscle and tendon. They can sense, adapt, and even “remember” how they’ve moved before.

Yeo trains machine learning algorithms to adjust those pliable materials in real time with the right amount of force or flexibility for each task.

“These muscles don’t only respond to commands,” Yeo said. “They learn from experience. They can adapt and self-correct, which makes motion smoother and more natural.”

The result of that research is deeply human. For someone recovering from a stroke or limb loss, each deliberate movement rebuilds not just strength — it rebuilds confidence, independence, and a sense of self.

 

A Glove That Gives Freedom Back

One of the first real-world applications is a prosthetic glove powered by artificial muscles (published in ACS Nano, 2025), a device that behaves more like a helping hand than a mechanical tool. Traditional prosthetics rely on rigid motors and preset motions, but Yeo’s design mirrors the natural give-and-take of real muscle.

Inside the glove, thin layers of stretchable fibers and sensors contract, twist, and flex in sync with the wearer’s intent. The glove can fine-tune grip strength, reduce tremors, and respond instantly to the user’s movements, bringing dexterity back to everyday life.

That kind of precision matters most in the smallest tasks: fastening a button, lifting a glass, holding a child’s hand.

“These aren’t just movements,” Yeo said. “They’re freedoms.”

For Yeo, the idea of restoring freedom through movement has driven his research from the very beginning.
 

A Mission Rooted in Loss

Yeo's work is deeply personal. His path to biomedical engineering began with loss — the sudden death of his father while Yeo was still in college. That moment reshaped his sense of purpose, redirecting his focus from machines that move to technologies that heal.

“Initially, I was thinking about designing cars,” he said. “But after my father’s death, I kind of woke up. Maybe I could do something that helps save someone’s life.”

That purpose continues to guide his lab’s work today, building technologies that help people recover what they’ve lost.

Achieving that vision, however, means tackling some of engineering’s toughest challenges.
 

Soft Machines, Hard Problems

Creating lifelike muscles isn’t easy. They need to be soft but strong, responsive but safe. And they must avoid triggering the body’s immune system. That means building materials that can survive inside the body — and learn to belong there.

“We always think about not only function, but adaptability,” Yeo said. “If it’s going to be part of someone’s body, it has to work with them, not against them.”

His team calibrates these synthetic fibers like precision instruments — tested, adjusted, and re-tuned until they operate in sync with the body’s natural movements. Over time, they develop a kind of “muscle memory,” adapting fluidly to changing conditions. That dynamic adaptability, Yeo explained, is what separates a machine from a prosthetic that truly feels alive.
 

From Collaboration to Innovation

Solving problems this complex requires more than one discipline. It takes an entire ecosystem of collaboration. Yeo’s lab brings together experts in mechanical engineering, materials science, medicine, and computer science to design smarter, safer devices.

“You can’t solve this kind of problem in isolation,” he said. “We need all of it — polymers, artificial intelligence, biomechanics — working together.”

That collaborative model is supported by the National Science Foundation (NSF), the National Institutes of Health, and Georgia Tech’s Institute for Matter and Systems. In 2023, Yeo received a $3 million NSF grant to train the next generation of engineers building smart medical technology.

His team now works closely with healthcare providers and industry partners to bring these devices out of the lab and into patients’ lives.


The Future You Can Feel

The future of robotics, according to Yeo, won’t be defined by power or complexity but by feel.

“If it feels foreign, people won’t use it,” he said. “But if it feels like part of you, that’s when it can truly change lives.”

It’s the opposite of The Terminator, where machines replace us. Yeo is designing these machines to help us reclaim ourselves.

Understanding the brain is key to unlocking human health and flourishing. The need has never been more urgent, but this challenge is too vast for any single discipline to solve alone.

That’s why Georgia Tech recently launched the Institute for Neuroscience, Neurotechnology, and Society (INNS). A step toward a more connected, collaborative future, INNS brings together experts from across Georgia Tech’s seven colleges and the Georgia Tech Research Institute (GTRI) to study the brain in ways that connect scientific discovery with technological innovation and real-world societal needs.

INNS supports research that crosses traditional academic boundaries. As an Interdisciplinary Research Institute (IRI), it builds community, fosters collaboration, and fills critical gaps in education, professional development, and research infrastructure.

“Georgia Tech has a long-standing culture of interdisciplinary collaboration — it’s in our DNA,” says INNS Executive Director Chris Rozell. Rozell also serves as Julian T. Hightower Chaired Professor in the School of Electrical and Computer Engineering. “INNS builds on that strength to create a space where breakthroughs in neuroscience and neurotechnology can move from lab to life, impacting real people in real ways.”

A Community Built to Collaborate

INNS is home to a growing network of faculty, students, and research centers spanning the full spectrum of Georgia Tech’s research expertise. This diversity is not just a feature, it’s the foundation.

That foundation was laid over decades of growth, vision, and grassroots momentum. Georgia Tech welcomed its first neuroscience-focused faculty member in 1990, sparking a steady expansion of brain-related research across campus. As more faculty joined and new focus areas emerged, a vibrant, cross-disciplinary community began to take shape.

In 2014, that community organized under the name GT Neuro, a grassroots initiative that united researchers who shared a passion for understanding the brain. This collective energy led to new educational programs, including the launch of Georgia Tech’s undergraduate neuroscience major in the College of Sciences.

“Our undergraduate students absolutely love teaching others about Neuroscience,” said Christina Ragan, director of Outreach for the Undergraduate Neuroscience Program and senior academic professional in the School of Biological Sciences. “I'm really excited to explore ways for INNS to connect our neuroscience community at Tech with the public.”

By 2023, the Neuro Next Initiative launched to bring together leaders from across campus and chart a strategic path forward — the result of nearly two years of community-driven planning to formalize and expand Georgia Tech’s neuroscience ecosystem. 

“The launch of INNS has built on the momentum of the Neuro Next Initiative, which ignited crucial conversations and fostered new collaborations between researchers at GTRI and Georgia Tech faculty,” says Tabitha Rosenbalm, GTRI senior research engineer. “The remarkable demonstration at Interface Neuro — witnessing a quadriplegic man walk and communicate thanks to innovative research — underscores the transformative breakthroughs possible when academic and applied researchers unite. INNS is uniquely positioned to serve as a catalyst, propelling Atlanta, Georgia Tech, and GTRI as national leaders in neurotechnology, driving advancements in both human health and engineering innovation.”

INNS is also helping shape the future of education. A new interdisciplinary Ph.D. program in neuroscience and neurotechnology welcomed its first cohort this fall, and INNS is poised to support it with professional development, research opportunities, and community engagement.

Breaking Boundaries to Advance Brain Science

Whether it’s developing neurotechnologies, designing therapeutic environments, or exploring the ethical implications of brain research, INNS is here to support work that spans fields and impacts lives.

“To responsibly address the societal and human impacts of advances in neuroscience and neurotechnology, we first need to understand them,” said Margaret Kosal, professor and director of Graduate Students in the Ivan Allen College of Liberal Arts. “That requires real and substantive collaboration beyond traditional engineering or biology labs.”

One example of INNS in action is the Smart Transitional Home Lab, a project funded by the inaugural INNS/Shepherd Center Seed Grant. This initiative brings together experts in architecture, inclusive design, neuroengineering, and rehabilitation to prototype environments that actively support stroke recovery, blending rigorous research with human-centered design.

“The establishment of INNS creates a powerful platform where diverse minds, from neuroscience to architecture to rehabilitation, can converge around a shared mission to advance human health,” says Hui Cai, professor in the School of Architecture, executive director of the SimTigrate Design Center, and co-leader of the project. “It enables interdisciplinary work with the potential to transform lives and redefine how we design for healing and recovery.”

“From whole brain recordings, to mapping the connectome, to the incredible advances in artificial intelligence, it's never been a more exciting time to study the mind and brain,” says Bob Wilson, director of the Center of Excellence for Computation and Cognition and associate professor in the School of Psychology. “I'm extremely excited for INNS to act as a central hub, building the neuroscience community at Georgia Tech and beyond.”

Join Us

INNS is more than an institute, it’s a growing, vibrant community of researchers, educators, students, and partners. Together, we’re working to understand the brain, develop technologies that improve lives, and ensure those innovations serve society responsibly.

Whether you're a student, researcher, policymaker, or simply curious about the brain, INNS is your gateway to interdisciplinary neuroscience at Georgia Tech. Get involved at neuro.gatech.edu.

A joint initiative of the Colleges of Sciences, Computing, and Engineering, the program aims to educate students and advance the field of neuroscience through an interdisciplinary approach. It integrates neuroscience research with technological development to explore all levels of nervous system function. 

“Our first Ph.D. students represent a wide range of professional and research interests in neuroscience and neurotechnology,” says Tim Cope, program director and professor in the School of Biological Sciences and Wallace H. Coulter Department of Biomedical Engineering. “The student-centered program is built on the strength of our exceptional researchers and educators. I am watching with excitement as our faculty and new students create a dynamic community of learning and collaboration that is dedicated to neuroscience discovery.”

Ph.D. program pioneers

Yvonne Milligan, a Kennesaw, Georgia native, is one of the program’s first students. Her research focuses on the nervous system and how it interacts with ovarian cancer.

For Milligan, choosing the program was an easy decision.

“Georgia Tech encourages forward-thinking,” she says. “As someone interested in various industry roles, I liked the support available for all career paths, not just academia.”

Abigail Holberton, a Georgia Tech alumna (BME 2022) from Dacula, Georgia, is also a member of the inaugural cohort. She studies in vitro and in vivo mild traumatic brain injury, examining the role of intracellular signals between cells. She joined the program to deepen her expertise in cellular and molecular neuroscience.

“Being part of the first class is a great honor as I hope to help pave the way for future scientists and engineers to explore neuroscience and neurotechnology,” she says. “I am very excited to learn about some of the most cutting-edge techniques in neuroscience from pioneers in the field.”

Georgia Tech and neuroscience

The Ph.D. program complements Georgia Tech’s B.S. in Neuroscience degree, one of the fastest-growing undergraduate majors at the Institute, as well as the recently launched Institute for Neuroscience, Neurotechnology, and Society. 

“Together, the new doctoral degree program, the undergraduate neuroscience program — now in its eighth year — and the Institute for Neuroscience, Neurotechnology, and Society will strengthen Georgia Tech’s core commitment to developing leaders who advance technology and improve the human condition,” says David M. Collard, senior associate dean in the College of Sciences and professor in the School of Chemistry and Biochemistry. 

“Strengthened by the launch of our new Ph.D. program, Georgia Tech takes another big step forward as a top-tier destination for neuroscience,” Cope adds. “The program fosters an exciting environment for research and training — built on the strength of our faculty’s leading-edge work and their genuine enthusiasm for mentoring the next generation of neuroscientists.” 

A team of Georgia Tech researchers wanted to ease that struggle, and robotic exoskeletons offered a promising path. Their findings point to a simple but powerful shift: exoskeletons that adapt to people, rather than forcing people to adapt to the machine. Using artificial intelligence (AI) to learn the rhythm of patients’ strides in real time, the team showed how these devices can reduce strain and increase efficiency. They also demonstrated how the technology can help restore confidence for stroke survivors. 

The Robot Finds the Rhythm

A robotic exoskeleton is a wearable device that helps people move with mechanical support. Traditional exoskeletons require endless manual adjustments — turning knobs, calibrating settings, and tweaking controls. 

“It can be frustrating, even nearly impossible, to get it right for each person,” said Aaron Young, associate professor in the George W. Woodruff School of Mechanical Engineering. “With AI, the exoskeleton figures out the mapping itself. It learns the timing of someone’s gait through a neural network, without an engineer needing to hand-tune everything.”

The software monitors each step, instantly updates, and fine-tunes the support it provides. Over time, the exoskeleton aligns its movements with the unique gait of the person wearing it. In this study, the research team used a hip exoskeleton, which provides torque at the hip joint — in other words, adding power to help stroke survivors walk or move their legs more easily.
 

Taking Smarter Steps

Walking after a stroke can be tough and unpredictable. A patient’s stride can change from one day to the next, and even from one step to the next. Most exoskeletons aren’t built for that kind of variation. They are designed around the steady, even gait of healthy young adults, which can leave stroke survivors feeling more unsteady than supported.

Young’s breakthrough, detailed in IEEE Transactions on Robotics, is a neural network — a type of AI that learns patterns much like the human brain does. Sensors at the hip pick up how someone is moving, and the network translates those signals into just the right boost of power to support each step. It quickly figures out a person’s unique walking pattern. But lead clinician Kinsey Herrin said the AI’s learning doesn’t stop there. It keeps adjusting as the patient walks, so the exoskeleton can stay in sync even during stride shifts.

“The speed really surprised us,” Young said. “In just one to two minutes of walking, the system had already learned a person’s gait pattern with high accuracy. That’s a big deal, to adapt that quickly and then keep adapting as they move.”

Tests showed the system was far more accurate than the standard exoskeleton. It reduced errors in tracking stroke patients’ walking patterns by 70%.

Young emphasized that this research is about more than metrics. “When you see someone able to walk farther without becoming exhausted, that’s when you realize this isn’t just about robotics — it’s about giving people back a measure of independence,” he said.
 

Adapting Anywhere

Every exoskeleton comes with its own set of sensors, so the data they collect can look completely different from one device to the next. A neural network trained on one machine often stumbles when it’s moved to another. To get around that, Young’s team designed software that works like a universal adapter plug — no matter what device it’s connected to, it converts the signals into a form the AI can use. After just 10 strides of calibration, the system cut error rates by more than 75%.

“The goal is that someone could strap on a device, and, within a minute, it feels like it was built just for them,” Young said.


A Step Toward the Future

While the study centered on stroke survivors, the implications are far broader. The same adaptive approach could support older adults coping with age-related muscle weakness, people with conditions like Parkinson’s or osteoarthritis, or even children with neurological disabilities. 
Young and his team are now running clinical trials to measure how well the AI-powered exoskeleton supports people in a wide range of everyday activities.

“There’s no such thing as an ‘average’ user,” Young said. “The real challenge is designing technology that can adapt to the full spectrum of human mobility.”

If Georgia Tech’s exoskeleton can rise to that challenge, the promise goes well beyond the lab. It could mean a world where technology doesn’t just help people walk — it learns to walk with them.

Inseung Kang, who holds a B.S., M.S., and Ph.D. from Georgia Tech, is the paper’s lead author and now an assistant professor of mechanical engineering at Carnegie Mellon University. He explained that the real promise is in what comes next. 

“We’ve developed a system that can adjust to a person’s walking style in just minutes. But the potential is even greater. Imagine an exoskeleton that keeps learning with you over your lifetime, adjusting as your body and mobility change. Think of it as a robot companion that understands how you walk and gives you the right assistance every step of the way.”

 

Aaron Young is affiliated with Georgia Tech’s Institute for Robotics and Intelligent Machines.

This research was primarily funded by a grant (DP2HD111709-01) from the National Institutes of Health New Innovator Award Program. Georgia Tech researchers have created the first lung-on-a-chip with a functioning immune system, allowing it to respond to infections much like a real human lung. The breakthrough, published in Nature Biomedical Engineering, provides a more accurate way to study diseases, test therapies, and reduce reliance on animal models. With potential applications in conditions from influenza to cancer, the technology opens the door to personalized medicine that predicts how individual patients will respond to treatment.

A new wearable electronic device that can be inserted inside any shoe may be able to address this challenge. The device, developed by Georgia Tech researchers, is made of more than 170 thin, flexible sensors that measure foot pressure — a key metric for determining whether someone is off-balance. The sensor collects pressure data, which the researchers could eventually use to predict which changes lead to falls.

The researchers presented their work in the paper, “Flexible Smart Insole and Plantar Pressure Monitoring Using Screen-Printed Nanomaterials and Piezoresistive Sensors.” It was the cover paper in the August edition of ACSApplied Materials & Interfaces. 

Pressure Points

Smart footwear isn’t new — but making it both functional and affordable has been nearly impossible. W. Hong Yeo’s lab has made its reputation on creating malleable medical devices. The researchers rely on the common commercial practice of screen-printing electronics to screen-print sensors. They realized they could apply this printing technique to address walking difficulties.

“Screen-printing is advantageous for developing medical devices because it's low-cost and scalable,” said Yeo, the Peterson Professor and Harris Saunders Jr. Professor in the George W. Woodruff School of Mechanical Engineering. “So, when it comes to thinking about commercialization and mass production, screen-printing is a really good platform because it's already been used in the electronics industry.”

Making the device accessible to the everyday user was paramount for Yeo’s team. A key innovation was making sure the wearable is thin enough to be comfortable for the wearer and easy to integrate with other assistive technologies. The device uses Bluetooth, enabling a smartphone to collect data and offer the future possibility of integrating with existing health monitoring applications.

Possibilities for real-world adaptation are promising, thanks to these innovations. Lightweight and small, the wearable could be paired with robotics devices to help stroke and Parkinson’s patients and the elderly walk. The high number of sensors could make it easier for researchers to apply a machine learning algorithm that could predict falls. The device could even enable professional athletes to analyze their performance.

Regardless of how the device is used, Yeo intends to keep its cost under $100. So far, with funding from the National Science Foundation, the researchers have tested the device on healthy subjects. They hope to expand the study to people with gait impairments and, eventually, make the device commercially available. 

“I'm trying to bridge the gap between the lack of available devices in hospitals or medical practices and the lab-scale devices,” Yeo said. “We want these devices to be ready now — not in 10 years.”

With its low-cost, wireless design and potential for real-time feedback, this smart insole could transform how we monitor and manage walking difficulties — not just in clinical settings, but in everyday life. 

To address these challenges, three Georgia Tech researchers have received a $3.2 million Research Project Grant (R01) from the National Institutes of Health's (NIH) National Institute on Aging (NIA).

Leading the study is Gregory Sawicki, Joseph Anderer Faculty Fellow and professor in the George W. Woodruff School of Mechanical Engineering and School of Biological Sciences. He is joined by Woodruff School colleagues Aaron Young, associate professor, and Kinsey Herrin, principal research scientist, along with partners at the Institute for Human & Machine Cognition (IHMC) and Northeastern University. Together, they will study how aging impacts lower-limb joint mechanics, muscle function, and the energy cost of walking.

Read the full story on the George W. Woodruff School of Mechanical Engineering website.

Tests in highly controlled environments for bipedal robots and varied terrain in quadrupeds show promise, but the costs and complexity required to equip these robots with the sensors needed to navigate create a huge barrier to deployment at scale. In contrast, low-profile multilegged robots with redundant contacts eliminate the need for costly visual and LIDAR systems and are poised to be deployed commercially in the agricultural sector.

These multilegged locomoting systems, though less complex and costly, come with their own technological challenges that impact speed and vertical maneuverability due to the robotic design’s high degree degrees of freedom and visual sensing limitations due to height in relation to environment. To address these challenges, Juntao He, a Ph.D. student in the group of Daniel Goldman, Professor in the School of Physics at Georgia Tech, led a pair of research papers that paves the way to make these bots able to move faster and climb higher in challenging environments. The work is in collaboration with Baxi Chong, now assistant professor at The Pennsylvania State University, as well as others in Goldman’s lab, in a multidisciplinary collaboration to improve these cost-effective little bots.

To enhance speed on varied terrain, the researchers used a multilegged segmented robot equipped with three motors for pitch and yaw and leg tip mounted force sensors onboard each segment. Inspired by the movement of centipedes, the team added vertical body undulation coordinated with horizontal undulation and leg stepping. The additional vertical movement mitigates the environmental elements that impact forward motion, allowing the robot to move across multiple surfaces without a loss of speed.

 The many-legged robot demonstrates impressive 2.5D mobility in unstructured environments with minimal sensing. What’s next? Our goal is to integrate greater intelligence into the robot, enabling it to make decisions and navigate effectively 
in the open world. - Juntao He

To enable greater vertical obstacle navigation, Goldman’s team used the same robotic setup with the addition of tactile antenna to investigate impediments and a control system that integrates data from the antenna and the force sensors on the legs. This integrated data prompts the robot to adjust head placement and optimize the vertical undulation waves to climb the probed object. Using this efficient sensor system, the team’s robot reliably scaled obstacles five times its height in a controlled laboratory setting and performed equally well in outdoor testing. The team is working with Georgia Tech Commercialization and Goldman’s startup, Ground Control Robotics, Inc.*

-Christa M. Ernst
Research Communications Program Manager
Klaus Advance Computing Building 1120E | 266 Ferst Drive | Atlanta GA | 30332
Topic Expertise: Robotics | Data Sciences | Semiconductor Design & Fab
christa.ernst@research.gatech.edu

Publications Referenced
Probabilistic Approach to Feedback Control Enhances Multilegged Locomotion on Rugged Landscapes
Tactile sensing enables vertical obstacle negotiation for elongate many-legged robots

*Disclaimer: Daniel Goldman has an equity interest in Ground Control Robotics, Inc. (GCR). GCR develops robots for locomotion in complex environments.  GCR may potentially benefit financially from the research findings on locomoting systems presented here. 

Before launching its prototype, a research team within Georgia Tech’s School of Interactive Computing, led by Professor Bruce Walker and Assistant Professor Sehoon Ha, is working to improve its methods and designs based on research within blind and visually impaired (BVI) communities.

“There’s been research on the technical aspects and functionality of robotic guide dogs, but not a lot of emphasis on the aesthetics or form factors,” said Avery Gong, a recent master’s graduate who worked in Walker’s lab. “We wanted to fill this gap.”

Training a guide dog can cost up to $50,000, and while there are nonprofit organizations that can cover these costs for potential owners, there is still a gap between the amount of available guide dogs and BVI individuals who need them. Not all BVI individuals are able to care for a dog and feed it. The dog also has fewer than 10 working years before it needs replacement.

Gong co-authored a paper on the design implications of the robotic guide dog that was presented at the 2025 International Conference on Robotics and Automation (ICRA) in Atlanta in May.

The consensus among the study’s participants indicates they prefer a robotic guide dog that:

• resembles a real dog and appears approachable
• has a clear identifier of being a guide dog, such as a vest
• has built-in GPS and Bluetooth connectivity
• has control options such as voice command
• has soft textures without feeling furry
• has long battery life and self-charging capability

“A lot of people said they didn’t want the dog to look too cute or appealing because it would draw too much attention,” said Aviv Cohav, another lead author of the paper and recent master’s graduate.

“Many people have issues with taking their guide dog to places, whether it’s little kids wanting to play with the dog or people not liking dogs or people being scared of them, and that reflects on the owners themselves. We wanted to look at what would be a good balance between having a functional robot that wouldn’t scare people away or be a distraction.”

The researchers also had to consider the perspectives of sighted individuals and how society at large might view a robotic guide dog.

An example of this is the amount of noise the dog makes while walking. The owner needs to hear the dog is active, but the clanky sound many off-the-shelf robots make could create disturbances in indoor spaces that amplify sounds. To offset the noise, the team developed algorithms that allow the robot to move more quietly.

Walker and his lab have examined similar scenarios that must take public perception into account.

“We like to think of Georgia Tech as going the extra mile,” Walker said. “Let’s not just make a robot, but a robot that’s going to fit into society.

“To have impact, the technologies we produce must be produced with society in mind. This is a holistic design that considers the users and all the people with whom the users interact.”

Taery Kim, a computer science Ph.D. student, began working on the concept of a robotic guide dog when she came to Georgia Tech in 2022. She and Ha, her advisor, have authored papers on building the robot’s navigation and safety components. 

“When I started, I thought it would be as simple as giving the guide dog a command to take me to Starbucks or the grocery store, and it would just take me,” Kim said. “But the user must give waypoint directions — ‘go left here,’ ‘turn right,’ ‘go forward,’ ‘stop.’ Detailed commands must be delivered to the dog.”

While a real dog has naturally enhanced senses of hearing and smell that can’t be replicated, technology can provide interconnected safety features during an emergency. The researchers envision a camera system equipped with a 360-degree field of view, computer vision algorithms that detect obstacles or hazards, and voice recognition that recognizes calls for help. An SOS function could automatically call 911 at the owner’s request or if the owner is unresponsive.

Kim said the robot should also have explainability features to enhance communication with the owner. For example, if the robot suddenly stops or ignores an owner’s commands, it should tell the owner that it’s detecting a hazard in their path.

Manufacturing a robot at scale would initially be expensive, but the researchers believe the cost would eventually be offset because of its longevity. BVI individuals may only need to purchase one during their lifetime.

To introduce a prototype, the multidisciplinary research team recognizes that it needs to enlist experts from other fields to adequately address the various implications and research gaps inherent in the project.

Walker said the teams welcome additional partners who are keen to tackle challenges ranging from design and engineering to battery life to human-robot interaction.

Team member J. Taery Kim was supported by the National Science Foundation's Graduate Research Fellowship Program (NSF GRFP) under Grant No. DGE-2039655.

The Georgia Tech-Shepherd Center Seed Grant Program is part of an ongoing partnership between the two institutions that started in 2023 with the goal of advancing rehabilitative patient care and research.

“The seed grant program is intended to stimulate new interdisciplinary research collaborations by providing seed funding to obtain preliminary data or prototypes necessary for the submission of an external grant or industry opportunities,” says Deborah Backus, vice president of Research and Innovation at Shepherd Center. “As two leading research institutions, we know the potential for advancing rehabilitation therapies is even greater when we work together. We look forward to the solutions, treatments, and therapies that emerge from these initial seed grants.” 

Experts from both institutions evaluated and scored seed grant applications based on the research’s innovation, approach, and potential for training opportunities, as well as its anticipated impact, prospects for commercial translation, and strategy for securing continued funding. This year, each awardee team received close to $50,000.

“We are very excited to launch this new seed grant program, which will spur ideas and propel research forward,” said Michelle LaPlaca, professor in the Coulter Department of Biomedical Engineering and the Georgia Tech lead of the Collaborative. “The complementary expertise of Georgia Tech and Shepherd Center researchers, combined with the motivation to find solutions for individuals with neurological injury and disability, is a winning formula for innovation.”

"Offering new hope for neurorehabilitation patients requires bringing together interdisciplinary researchers to explore new and creative ideas,” adds Chris Rozell, Julian T. Hightower Chaired professor in the School of Electrical and Computer Engineering and the inaugural executive director of the Institute of Neuroscience, Neurotechnology, and Society (INNS) at Georgia Tech. “I'm excited to see the talent at these world class institutions coming together to develop new solutions for these complex problems."

This year’s seed grants were awarded to the following projects:

• Proof of Concept Development of the Recovery Cushion – Stephen Sprigle, professor, School of Industrial Design and School of Mechanical Engineering, Georgia Tech; Jennifer Cowhig, research physical therapist, Shepherd Center.
• Paving a Smooth Path from Hospital to Home: A Feasibility Study of an Integrated Smart Transitional Home Lab to Support Stroke Rehabilitation Patients’ Transition to Home – John Morris, senior clinical research scientist, Shepherd Center; Hui Cai, professor in the School of Architecture, executive director of the SimTigrate Design Center, Georgia Tech.
• A Comparative Analysis of Lower-Limb Exoskeleton Technology for Non-Ambulatory Individuals with Spinal Cord Injury – Maegan Tucker, assistant professor, School of Electrical and Computer Engineering and School of Mechanical Engineering, Georgia Tech; Nicholas Evans (AP 2023), clinical research scientist, Shepherd Center.
• Improving Accessibility and Precision in Neurorehabilitation at the Point of Care with AI-Driven Remote Therapeutic Monitoring Solutions – Brad Willingham, clinical research scientist, director of Multiple Sclerosis Research, Shepherd Center; May Dongmei Wang, professor, Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech.

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

Christopher Rozell, Julian T. Hightower Chaired Professor in the School of Electrical and Computer Engineering, will serve as the inaugural executive director of Georgia Tech’s new Institute for Neuroscience, Neurotechnology, and Society (INNS). 

READ THE ARTICLE

Is it possible to upload the consciousness of your mind into a computer? – Amreen, age 15, New Delhi, India

The concept, cool yet maybe a little creepy, is known as mind uploading. Think of it as a way to create a copy of your brain, a transmission of your mind and consciousness into a computer. There you would live digitally, perhaps forever. You’d have an awareness of yourself, you’d retain your memories and still feel like you. But you wouldn’t have a body.

Within that simulated environment, you could do anything you do in real life – eating, driving a car, playing sports. You could also do things impossible in the real world, like walking through walls, flying like a bird or traveling to other planets. The only limit is what science can realistically simulate.

Doable? Theoretically, mind uploading should be possible. Still, you may wonder how it could happen. After all, researchers have barely begun to understand the brain.

Yet science has a track record of turning theoretical possibilities into reality. Just because a concept seems terribly, unimaginably difficult doesn’t mean it’s impossible. Consider that science took humankind to the Moon, sequenced the human genome and eradicated smallpox. Those things too were once considered unlikely.

As a brain scientist who studies perception, I fully expect mind uploading to one day be a reality. But as of today, we’re nowhere close.

Living in a Laptop

The brain is often regarded as the most complex object in the known universe. Replicating all that complexity will be extraordinarily difficult.

One requirement: The uploaded brain needs the same inputs it always had. In other words, the external world must be available to it. Even cloistered inside a computer, you would still need a simulation of your senses, a reproduction of the ability to see, hear, smell, touch, feel – as well as move, blink, detect your heart rate, set your circadian rhythm and do thousands of other things.

But why is that? Couldn’t you just exist in a pure mental bubble, inside the computer without sensory input?

Depriving people of their senses, like putting them in total darkness, or in a room without sound, is known as sensory deprivation, and it’s regarded as a form of torture. People who have trouble sensing their bodily signals – thirst, hunger, pain, an itch – often have mental health challenges.

That’s why for mind uploading to work, the simulation of your senses and the digital environment you’re in must be exceptionally accurate. Even minor distortions could have serious mental consequences.

For now, researchers don’t have the computing power, much less the scientific knowledge, to perform such simulations.

Scanning billions of pinheads

The first task for a successful mind upload: Scanning, then mapping the complete 3D structure of the human brain. This requires the equivalent of an extraordinarily sophisticated MRI machine that could detail the brain in an advanced way. At the moment, scientists are only at the very early stages of brain mapping – which includes the entire brain of a fly and tiny portions of a mouse brain.

In a few decades, a complete map of the human brain may be possible. Yet even capturing the identities of all 86 billion neurons, all smaller than a pinhead, plus their trillions of connections, still isn’t enough. Uploading this information by itself into a computer won’t accomplish much. That’s because each neuron constantly adjusts its functioning, and that has to be modeled, too.

It’s hard to know how many levels down researchers must go to make the simulated brain work. Is it enough to stop at the molecular level? Right now, no one knows.

2045? 2145? Or Later?

Knowing how the brain computes things might provide a shortcut. That would let researchers simulate only the essential parts of the brain, and not all biological idiosyncrasies. It’s easier to manufacture a new car knowing how a car works, compared to attempting to scan and replicate an existing car without any knowledge of its inner workings.

However, this approach requires that scientists figure out how the brain creates thoughts – how collections of thousands to millions of neurons come together to perform the computations that make the human mind come alive. It’s hard to express how very far we are from this.

Here’s another way: Replace the 86 billion real neurons with artificial ones, one at a time. That approach would make mind uploading much easier. Right now, though, scientists can’t replace even a single real neuron with an artificial one.

But keep in mind the pace of technology is accelerating exponentially. It’s reasonable to expect spectacular improvements in computing power and artificial intelligence in the coming decades.

One other thing is certain: Mind uploading will certainly have no problem finding funding. Many billionaires appear glad to part with lots of their money for a shot at living forever.

Although the challenges are enormous and the path forward uncertain, I believe that one day, mind uploading will be a reality. The most optimistic forecasts pinpoint the year 2045, only 20 years from now. Others say the end of this century.

But in my mind, both of these predictions are probably too optimistic. I would be shocked if mind uploading works in the next 100 years. But it might happen in 200 – which means the first person to live forever could be born in your lifetime.

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

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The study, “TopoNets: High-Performing Vision and Language Models With Brain-Like Topography,” was awarded a spotlight at this year’s International Conference on Learning Representations (ICLR), a distinction given to only 2 percent of papers. The research was led by graduate student Mayukh Deb alongside School of Psychology Assistant Professor Apurva Ratan Murty.

Thirty-two of Tech’s computing, engineering, and science faculty represented the Institute at ICLR 2025, which is globally renowned for sharing cutting-edge research. 

“We started with this idea because we saw that AI models are unstructured, while brains are exquisitely organized,” says first-author Deb. “Our models with internal structure showed more than a 20 percent boost in efficiency with almost no performance losses. And this is out-of-the-box — it’s broadly applicable to other models with no extra fine-tuning needed.”

For Murty, the research also underscores the importance of a rapidly growing field of research at the intersection of neuroscience and AI. “There's a major explosion in understanding intelligence right now,” he says. “The neuro-AI approach is exciting because it helps emulate human intelligence in machines, making AI more interpretable.”

“In addition to advancing AI, this type of research also benefits neuroscience because it informs a fundamental question: Why is our brain organized the way it is?,” Deb adds. “Making AI more interpretable helps everyone.”

Brain-inspired blueprints

In the brain, neurons form topographic maps: neurons used for comparable tasks are closer together. The researchers applied this concept to AI by organizing how internal components (like artificial neurons) connect and process information. 

This type of organization has been tried in the past but has been challenging, Murty says. “Historically, rules constraining how the AI could structure itself often resulted in lower-performing models. We realized that for this type of biophysical constraint, you simply can’t map everything — you need an algorithmic solution.”

“Our key insight was an algorithmic trick that gives the same structure as brains without enforcing things that models don't respond well to,” he adds. “That breakthrough was what Mayukh (Deb) worked on.” 

The algorithm, called TopoLoss, uses a loss function to encourage brain-like organization in artificial neural networks, and it is compatible with many AI systems capable of understanding language and images. 

“The resulting training method, TopoNets, is very flexible and broadly applicable,” Murty says. “You can apply it to contemporary models very easily, which is a critical advancement when compared to previous methods.” 

Neuro-AI innovations

Murty and Deb plan to continue refining and designing brain-inspired AI systems. “All parts of the brain have some organization — we want to expand into other domains,” Deb says. “On the neuroscience side of things, we want to discover new kinds of organization in brains using these topographic systems.”

Deb also cites possibilities in robotics, especially in situations like space exploration where resources are limited. “Imagine running a model inside a robot with limited power,” he says. “Structured models can help us achieve 80 percent of performance with just 20 percent of energy consumption, saving valuable energy and space. This is still experimental, but it's the direction we are interested in exploring.”

“This success highlights the potential of a new approach, designing systems that benefit both neuroscience and AI — and beyond,” Murty adds. “We can learn so much from the human brain, and this project shows that brain-inspired systems can help current AI be better. We hope our work stimulates this conversation.”

Imagine you’re driving to the Atlanta airport to pick up a friend. They call to say they’re in the terminal — but they’re not sure which one. North, maybe? You head that direction through the maze of roads around the airport.

Then they call back. They’re actually in the South Terminal. So you make a quick mental adjustment and switch your route to arrive at the correct side of the airport.

You had a plan. You received new information. You quickly changed your destination. 
The question Prince has studied is this: How does that process happen in the brain?

A new research paper in Nature Communications is offering insights into that decision-making. And it could help scientists as they work to better understand when brain disorders such as Parkinson’s and Alzheimer’s impair those processes.

Read the full story on the College of Engineering website.

“When I finished rehabilitation, my doctors and therapist and, most importantly, the insurance company said, ‘For someone with your condition, we feel like you've made all the improvement that you will, have a nice life,’” said Burkhart, who was left with limited feeling and mobility below the neck after a 2010 diving accident injured his spinal cord. “That didn't sit well with me.” 

Hoping even a fraction of hand mobility would increase his independence, Burkhart turned to a clinical research trial on a brain-computer interface (BCI) designed to detect movement signals in the brain and send them to a computer to stimulate the arm muscles, bypassing the spinal cord in the hopes of restoring movement.

“I had had four and a half years of never thinking my hand was going to move again,” he recalled. When testing to see if he qualified for the study, researchers stimulated his hand muscles. “I saw my hand move, and that was all I needed to know — I was ready to risk it all for something that may or may not work.” 

Burkhart’s story is one of many that reveal the deeply personal side of neurotechnology research. Centering lived experiences like his is central to the mission of the Institute for Neuroscience, Neurotechnology, and Society (INNS), a new Interdisciplinary Research Institute launching this July at Georgia Tech.

“If we want to build neurotechnology that truly serves people, their voices should be part of the scientific process from the very beginning,” said Chris Rozell, a professor in the School of Electrical and Computer Engineering and one of the many researchers at Georgia Tech working to understand and advance BCIs. “Hearing from individuals who live with these devices helps guide more ethical, inclusive, and effective research. The entire field benefits from inclusive conversations like these.” 

Life With a Brain Implant

Burkhart and three others recently shared their stories live on the Ferst Center stage at “Wired Lives: Personal Stories of Brain-Computer Interfaces, an event organized by Georgia Tech’s Neuro Next Initiative. Their stories gave over 200 attendees a rare, honest glimpse into the realities of neurological conditions and the path to brain-computer interface research.

“I was at a crossroads in my life at 47 years old,” said Brandan Mehaffie, who told his story of living with early-onset Parkinson’s disease. “I was trying to figure out, do I continue with the status quo and watch my career dwindle into nothing? Watch my life with my family, my kids, not being able to go on hikes or family vacations?” 

Mehaffie eventually qualified for deep brain stimulation (DBS) treatment, a procedure where a pacemaker-like device is implanted into the brain to provide electrical stimulation. “It changed my life for the better in ways that I can't even tell you.”

When former U.S. Air Force Sgt. Jennifer Walden’s doctor told her about a clinical trial testing DBS as an epilepsy treatment, she jumped at the chance. “The 48 hours after those seizures are 48 hours where you don't want to live anymore.” Walden explained that her response to medication had dwindled after years of traditional treatment, increasing the frequency and severity of her seizures. “I feared suicide. It's something I didn't want to do, but if something happened in those 48 hours to end my life, I didn't care,” she said.

“I am now probably 99% seizure-free,” she beamed as she recalled her response to DBS on stage. “I don't know how I got so lucky in life, but I don't take it for granted.”

Common themes in their stories were resilience, hope, and a deep desire to give back.

“When I joined the study, it had no physical benefit to me, but that's not why I joined it,” said Scott Imbrie, who experienced a major spinal cord injury and participates in a clinical BCI study at the University of Chicago. “I decided to have invasive brain surgery and have electrodes implanted on my brain to help other people.”

A New Approach to Interdisciplinary Research

Timed alongside the InterfaceNeuro conference at Georgia Tech, the gathering offered a rare opportunity for scientists, engineers, and clinicians to engage directly with the lived experiences of individuals using brain-computer interfaces — a perspective often missing from traditional research settings.

“It makes you think about how we ethically conduct research and how we recruit and interface with patients,” said Eric Cole, a postdoctoral researcher at Emory University, who was reminded that many patients participating in BCI research have been on a long, difficult journey before interacting with researchers. “We should remember to take their experiences seriously and respect them. They're giving up something for research — that part we should always remember.”

“Wired Lives” was one in a series of events highlighting the lived experience of individuals with neurological conditions organized by the Neuro Next Initiative, which has served as the precursor to INNS.

“A core mission of INNS is to consider how neuroscience and neurotechnology impact people’s lives,” said Jennifer Singh, associate professor in the School of History and Sociology, a member of NNI’s executive committee, and a co-organizer of the event. “Their stories matter when it comes to the types of science and technology we pursue and how they benefit the human condition. Many scientists and engineers may never encounter people living with neurological conditions outside of events like this. That will be a priority for INNS — to bring the expertise of lived experiences to the research process.”

Ian Burkhart’s lived experience reminded the audience that not every clinical trial has a happy ending. His BCI was ultimately removed after seven years as research funding ran short, taking his newly improved hand mobility with it. Despite this, Burkhart remained positive.

“I'm so glad I was able to take that risk and have that voluntary brain surgery and participate in this type of research because it's defined my life.” Burkhart went on to found the BCI Pioneers Coalition and his own nonprofit because of his research participation. “It gave me a lot of hope for the future, and a lot of hope that these types of devices are going to be able to help people and improve their quality of life.”

This event was produced in partnership with The Story Collider and made possible through support from Blackrock Neurotech and Medtronic.

Georgia Tech recently convened over 200 stakeholders from every corner of the neurotechnology landscape to explore the future of this rapidly evolving field at InterfaceNeuro. Held May 7-8, the conference brought together a dynamic community of neuroscientists, neuroengineers, clinicians, industry leaders, and individuals with lived experiences to align cutting-edge research with clinical needs and societal impact.

“One of our primary goals was to create a space where people from different backgrounds could come together, share their perspectives, and learn from one another,” said Chris Rozell, professor in Georgia Tech’s School of Electrical and Computer Engineering and one of the conference’s organizers. “That kind of exchange is essential for advancing the field.”

Originally founded by Rice University’s Neuroengineering Initiative in 2023, InterfaceNeuro made its Atlanta debut with the theme “Integrating Brain, Body, and Machine for Next-Gen Intelligent Interfaces.” The conference featured a curated program of keynote talks, panel discussions, research posters, and informal networking sessions designed to foster knowledge exchange and catalyze new partnerships.

Speakers and attendees alike represented the full spectrum of neuroscience and neurotechnology experts, from bench scientists and device engineers to caregivers and patients. According to conference attendee Simone Russo, it was that breadth and diversity of the conference that made the conference worthwhile. 

“It was like talking to everybody at different levels, bridging the clinical side to the caregiving side, to the very basic research,” said Russo, a postdoctoral researcher in the Walter H. Coulter Department of Biomedical Engineering (BME). “That’s something that doesn't usually happen.”

Themed sessions were sponsored by several centers across Georgia Tech and Emory University, including the McCamish Parkinson’s Disease Innovation Program, the Neural Engineering Center, the Building Reliable Advances and Innovations in Neurotechnology (BRAIN) Center, and the Center for Advanced Motor Bioengineering and Research. Organized by Georgia Tech’s Neuro Next Initiative, the meeting was a testament to Atlanta’s expanding leadership in neuroscience and neurotechnology.

“This conference reflected the kind of community we’re building at Georgia Tech — one that’s deeply interdisciplinary, inclusive, and focused on real-world impact,” said Garrett Stanley, BME professor, director of the McCamish Parkinson's Disease Innovation Program, and one of the conference’s co-organizers. “With the launch of the Institute for Neuroscience, Neurotechnology, and Society this July, we’re creating a lasting home for this momentum to grow.”

It was April 2022, one year before her PhD defense. She’d been crossing the street near her apartment when the young driver turned right while looking left.

“He never saw me,” says Jeong, at the time a member of Annabelle Singer’s lab in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. “The next thing I know, I’m on the ground looking up at the sky. I was fully conscious the whole time.”

Worried about brain damage, she lifted her arm up just to see if she could do it. Her arm was fine. So was her brain. But there was 6,000 pounds of SUV on her leg. She had tire marks on her body. The driver’s little brother leapt out from the passenger side to check on Jeong and she remembered that he was crying.

“I realized this was just as traumatic for them as it was for me,” says Jeong, who remained calm throughout the ordeal partly because the boy’s tears had triggered something deep within her. Jeong conjured empathetic superpowers she’d acquired in a compassion-based meditation program at Emory. That kept her tranquil through the pain.

The accident left her with broken bones in her shattered leg, requiring surgery and months of physical therapy. Today she can climb flights of stairs with no problem. Nonetheless, the accident left its mark, inspiring a career path that she never really expected. 

Read the full story here >>

“We tend to think of our skin as being this impermeable barrier that’s just enclosing our body,” said Matthew Flavin, assistant professor in the School of Electrical and Computer Engineering. “Our skin is constantly in flux with the gases that are in our environment and our atmosphere.”

Led by the Georgia Institute of Technology, Northwestern University, and the Korea Institute of Science and Technology (KIST), researchers have developed a novel wearable device that can monitor the flux of vapors through the skin, offering new insights into skin health and wound healing. This technology, detailed in a recent Nature publication, represents a significant advancement in the field of wearable bioelectronics.

“You could think of this being used where a Band-Aid is being used,” said Flavin, one of the lead authors of the study. The compact, wireless device is the first wearable technology able to continuously and precisely measure water vapor, volatile organic compounds, and carbon dioxide fluxes in the skin in real time. Because increases in these factors are associated with infection and delayed healing, Flavin notes that this kind of wireless monitoring “could give clinicians a new tool to understand the properties of the skin.”

The Measurement Barrier

Our skin is our first line of defense against environmental hazards. Measuring how effectively it protects us from harmful pollutants or infections has been a significant challenge, especially over extended periods.

“The vapors coming from your skin are in very, very low concentration,” explained Flavin. “If we just put a sensor next to your skin, it would be almost impossible to control that measurement.”

The new device features a small chamber that condenses and measures vapors from the skin using specialized sensors hovering above the skin. A low-energy, bi-stable mechanism periodically refreshes the air in the chamber, allowing for continuous measurements communicated to a smartphone or tablet through Bluetooth.

“There are other devices that can measure certain parts of what we're talking about here,” said Flavin, “but they are not feasible for a wearable device, can't do this continuously, and are not able to get all the information that our device can get.”

Scratching the Surface

By tracking the skin's water vapor flux, also known as transepidermal water loss, the device can assess skin barrier function and wound healing. This capability is particularly valuable for tracking the healing process in diabetic patients, who often have sensory issues that complicate wound monitoring. “What you see in diabetes is that even after the wound looks like it's healed, there's still a persistent impairment of that barrier,” said Flavin. This new non-invasive device tracks those properties. 

“There are many areas where people don't have great access to healthcare, and there aren’t doctors monitoring wound healing processes,” Flavin added. “Something that can be used to monitor that remotely could make care more accessible to people with these conditions.”

The device’s wearable nature also makes it ideal for studying the long-term effects of exposure to environmental hazards like wildfires or chemical fumes on skin function and overall health.

Though the applications in health are numerous, the research team is continuing to explore different ways to use the device. “This measurement modality is very new and we're still learning what we can do with it,” saidJaeho Shin, a senior researcher at KIST and a co-leader of the study. “It's a new way of measuring what's inside the body.” 

“This is a great example of the kind of technology that can emerge from research at the interface between engineering science and medical practice,” said John Rogers, a materials science professor at Northwestern and another co-leader of the study. “The capabilities provided by this device will not only improve patient care, but they will also lead to improved understanding of the skin, the skin microbiome, the processes of wound healing, and many others.”

As a new faculty member and a member of Georgia Tech’s Neuro Next Initiative, a burgeoning interdisciplinary research hub for neuroscience, neurotechnology, and society, Flavin attributes the success of this research to its interdisciplinary nature.

“A broad challenge we have in these fields of research is that they integrate a lot of different areas. One of the reasons I came to Georgia Tech is because it's a place where you have access to all those different areas of expertise.”

DOI: https://doi.org/10.1038/s41586-025-08825-2

Funding: Querrey-Simpson Institute for Bioelectronics and the Center for Advanced Regenerative Engineering (CARE), Northwestern University; National Research Foundation of Korea; National Institutes of Health (NIH), National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Biomedical Imaging and Bioengineering.

The School of Psychology, led by Professor and Chair Tansu Celikel, has launched a new podcast series titled “Deep Dive into Brain and Behavior” — or D2B2. This cutting-edge podcast is created almost entirely by artificial intelligence (AI), and will spotlight the approximately 150 research publications authored by the School’s experts each year. 

Each episode of D2B2 will guide listeners through a recently published paper, distilling complex scientific findings into clear, engaging, easy-to-understand content. The goal is to make the latest in psychology and neuroscience more accessible to students, researchers, and anyone else who is simply curious about how the brain works. Celikel believes this is key to bridging the gap between science and the public. “Scientific papers are full of jargon and can be difficult to understand,” he says. “We want to use this podcast to reach a wider audience.” 

What makes D2B2 particularly innovative is its use of AI to generate nearly all of its content. The episodes are structured with minimal human input using a generative AI developed by Google called NotebookLM. It is a relatively new tool that simplifies research papers and creates a dialogue between an AI-generated host and reporter. However, before episodes air, the original research authors carefully review the content to ensure accuracy. 

The podcast is produced at virtually no cost and is available to the public for free. “Imagine a future where every scientific publication is freely accessible, not behind a paywall,” Celikel says. “And, imagine it is presented in a way that appeals to all levels of expertise — from novices to experts — from teenagers to seasoned practitioners.” He also hopes it will improve the education system by making scientific information more readily available to anyone who wants to learn. 

Celikel believes the podcast will enhance the School’s visibility and provide a platform for showcasing its researchers and research opportunities. He also views it as a valuable tool for keeping alumni connected with the School.

Deep Dive into Brain and Behavior is available on the School’s YouTube channel, with new episodes released every two weeks. The podcast will also soon be available on Apple Podcasts and Spotify.

“Don’t miss out — subscribe now to stay updated on the latest discoveries!” Celikel says.

“This is a meaningful prize that honors the longstanding impact of two Russian scientists, Anatol Feldman and Mark Latash. They founded the ISMC and were influential in building a community of scientists in the United States and Canada focused on motor systems research following in the tradition of Bernstein,” says Nichols, who retired from the School of Biological Sciences in 2023. “Receiving this prize is thrilling. It’s a cap on my career.”

Nichols will receive the award during ISMC’s biennial meeting this summer.  

From basic research to potential treatments

Nichols began his decades-long career researching the spinal cord, a key component of the central nervous system that relays information between the brain and periphery (muscles, joints, skin, etc.). He notes that the spinal cord is more than a simple communications highway; it contains neural networks that can exert some control. 

“When we walk across the room, the spinal cord — not the brain — generates and sends detailed messages to our muscles. The brain simply says, ‘It’s time to walk across a room and avoid this or that obstacle.’ The spinal cord contains the machinery to do so,” explains Nichols.

Nichols' research initially centered on understanding how sensory information from the periphery is used by the spinal cord and brain to control movement. More recently, his focus shifted to possible real-world applications of his findings. 

For example, Nichols collaborated with Dena Howland of the University of Louisville on research grants from the National Institutes of Health (NIH) and the Department of Veterans Affairs (VA) that are centered on understanding spinal cord injury.

“Had it not been for my collaboration with Dena over the past 11 years, my work would have remained limited to the fundamental science of how the spinal cord and brain function. Our translational project has broadened the scope and impact of my research,” he adds.

According to Nichols, the NIH and VA grants were synergistic: the NIH grant focused on spinal cord function, while the VA grant centered on rehabilitation strategies following spinal cord injury. Through this complementary research, the team uncovered insights about the spinal cord — potentially revealing new treatment pathways to aid motor control recovery after spinal cord injury.

Nichols retired from the Georgia Institute of Technology in 2023 after 16 years of service. Before joining the Institute in 2007 as chair of the School of Applied Physiology (now the School of Biological Sciences), he chaired the Department of Physiology at Emory University. Nichols received a B.S. in Biology from Brown University and a Ph.D. in Physiology from Harvard University.

Computational tools Rahaman developed for his dissertation look for informative patterns between the brain and behavior. Successful tests of his algorithms show promise to help doctors diagnose mental health disorders and design individualized treatment plans for patients.

Unsurprisingly, Rahaman successfully defended his dissertation and is on his way to graduate in a few weeks.

“I've always been fascinated by the human brain and how it defines who we are,” Rahaman said. 

“The fact that so many people silently suffer from neuropsychiatric disorders, while our understanding of the brain remains limited, inspired me to develop tools that bring greater clarity to this complexity and offer hope through more compassionate, data-driven care.”

Rahaman’s dissertation introduces a whole framework focusing on granular factoring. This computing technique stratifies brain data into smaller, localized subgroups. This makes it easier for computers and researchers to study data and find meaningful patterns.

Granular factoring overcomes the challenge of size and heterogeneity in neurological data science. Brain data is sourced from different modes, like neuroimaging, genomics, and behavioral datasets. Each of these sources are very large to study on their own, let alone analyzed at the same time to find hidden inferences. 

Rahaman’s research allows researchers and physicians to move past one-size-fits-all approaches. Instead of manually reviewing tests and scans, algorithms look for patterns and biomarkers in the subgroups that otherwise go undetected, especially ones that indicate neuropsychiatric disorders.

“My dissertation advances the frontiers of computational neuroscience by introducing scalable and interpretable models that navigate brain heterogeneity to reveal how neural dynamics shape behavior,” Rahaman said. 

“By uncovering subgroup-specific patterns, this work opens new directions for understanding brain function and enables more precise, personalized approaches to mental health care.”

Rahaman defended his dissertation on April 14, the final test in completing his Ph.D. in computational science and engineering. He will graduate on May 1 at Georgia Tech’s Ph.D. Commencement. 

After walking across the stage at McCamish Pavillion, Rahaman’s next step in his career is to Amazon where he will work in the generative artificial intelligence (AI) field. 

Graduating from Georgia Tech is the peak of an educational summit spanning over a decade. Rahaman hails from Bangladesh where he graduated from Chittong University of Engineering and Technology in 2013. He attained his master’s from the University of New Mexico in 2019 before starting at Georgia Tech. 

“Munna is an amazingly creative researcher,” said Vince Calhoun, Rahman’s advisor and Distinguished University Professor. Calhoun is the founding director of the Translational Research in Neuroimaging and Data Science Center (TReNDS).

TReNDS is a tri-institutional center spanning Georgia Tech, Georgia State University, and Emory University that develops analytic approaches and neuroinformatic tools. The center aims to translate the approaches into biomarkers that address areas of brain health and disease.    

“His work is moving the needle in our ability to leverage multiple sources of complex biological data to improve understanding of neuropsychiatric disorders that have a huge impact on an individual’s livelihood.”

Read more »

In a joint statement, PTC co-directors Wilbur Lam and Stanislav Emelianov said, “The appointment of Dr. LaPlaca and Dr. Yeo as Peterson Professors exemplifies the vision of Bud and Valerie Peterson — advancing innovation and collaboration through the Pediatric Technology Center to bring breakthrough ideas from the lab to the bedside, improving the lives of children and transforming healthcare.”

LaPlaca is a professor and associate chair for Faculty Development in the Department of Biomedical Engineering, a joint department between Georgia Tech and Emory University. Her research is focused on traumatic brain injury and concussion, concentrating on sources of heterogeneity and clinical translation. Specifically, she is working on biomarker discovery, the role of the glymphatic system, and novel virtual reality neurological assessments.    

“I am thrilled to be chosen as one of the Peterson Professors and appreciate Bud and Valerie Peterson’s dedication to pediatric research,” she said. “The professorship will allow me to broaden research in pediatric concussion assessment and college student concussion awareness, as well as to identify biomarkers in experimental models of brain injury.”

In addition to the research lab, LaPlaca will work with an undergraduate research class called Concussion Connect, which is part of the Vertically Integrated Projects program at Georgia Tech.

“Through the PTC, Georgia Tech and Children’s will positively impact brain health in Georgia’s pediatric population,” said LaPlaca.

Yeo is the Harris Saunders, Jr. Professor in the George W. Woodruff School of Mechanical Engineering and the director of the Wearable Intelligent Systems and Healthcare Center at Georgia Tech. His research focuses on nanomanufacturing and membrane electronics to develop soft biomedical devices aimed at improving disease diagnostics, therapeutics, and rehabilitation.

“I am truly honored to be awarded the Peterson Professorship from the Children’s PTC at Georgia Tech,” he said. “This recognition will greatly enhance my research efforts in developing soft bioelectronics aimed at advancing pediatric healthcare, as well as expand education opportunities for the next generation of undergraduate and graduate students interested in creating innovative medical devices that align seamlessly with the recent NSF Research Traineeship grant I received. I am eager to contribute to the dynamic partnership between Georgia Tech and Children’s Healthcare of Atlanta and to empower innovative solutions that will improve the lives of children.”

The Peterson Professorships honor the former Georgia Tech President and First Lady, whose vision for the importance of research in improving pediatric healthcare has had an enormous positive impact on the care of pediatric patients in our state and region.

The Children’s PTC at Georgia Tech brings clinical experts from Children’s together with Georgia Tech scientists and engineers to develop technological solutions to problems in the health and care of children. Children’s PTC provides extraordinary opportunities for interdisciplinary collaboration in pediatrics, creating breakthrough discoveries that often can only be found at the intersection of multiple disciplines. These collaborations also allow us to bring discoveries to the clinic and the bedside, thereby enhancing the lives of children and young adults. The mission of the PTC is to establish the world’s leading program in the development of technological solutions for children’s health, focused on three strategic areas that will have a lasting impact on Georgia’s kids and beyond.

“ASNR is a great society because of the range and breadth of its work, spanning cellular neuroscientists all the way to people that do massive multicenter phase three clinical drug trials,” says Wheaton, who has been involved in the organization for nearly two decades. “I am excited to serve as its president.”

Wheaton’s research interests initially drew him to ASNR — his research examines changes in the brain following a stroke or upper limb loss in order to inform the design of therapies that promote better limb function and prosthetics; his belief in the organization’s mission led him to join its leadership team. 

“I got involved in the executive board because I appreciated the vision of the society and the opportunities it provides for engaging more people in neurorehabilitation-based research and training the next generation of neurorehabilitation researchers,” he says.

Wheaton was elected ASNR vice president in 2022 and worked during the subsequent three years to develop the organization’s strategic plan. When he assumes the role of ASNR president this April, he will implement that plan. 

“We’re focusing on how to broaden and improve the sense of community within the society,” he shares. “Two of our goals are centered on enhancing our multidisciplinary focus and expanding engagement. We want to bring in not only people from other disciplines — as other disciplines are connected to the goals of neurorehabilitation — but also develop a culture that supports diverse groups of people entering the field.” 

Wheaton recognizes the parallels between his work at ASNR and the College of Sciences: “It is very consistent with many of the things that I've always enjoyed at the College: creating a community that brings people together, that people want to be a part of, and that they see a home for themselves in,” he explains, referencing his efforts as director of the Center for Programs to Increase Engagement in the Sciences (C-PIES) and mentoring students in his research lab. 

About Lewis Wheaton

Wheaton joined the Institute as an assistant professor in the School of Applied Physiology (now the School of Biological Sciences) in 2008. He is currently a professor in Biological Sciences at Georgia Tech, an adjunct professor in the Department of Rehabilitation at the Emory School of Medicine, and a member of the Children’s Center for Neurosciences Research at the Emory Children’s Pediatric Research Center.

Wheaton received a B.S. in biology from Radford University and a Ph.D. in neuroscience and cognitive science from the University of Maryland, College Park. He studied neural function and recovery of motor control after stroke as a fellow at the Medical Neurology Branch of the National Institutes of Health and performed neuroscience research in aging and stroke motor control as a postdoctoral fellow at the Baltimore Veterans Affairs Medical Center in Maryland.

About the American Society of Neurorehabilitation

The American Society of Neurorehabilitation (ASNR) was created in 1990 to advance clinical care and the science of neurorehabilitation and neural repair. The 2025 edition of the ASNR annual meeting will take place in Atlanta in late April.

“I hadn’t seen her in six years, but she recognized me,” said Jeong, a former graduate researcher in the lab of Annabelle Singer in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University.

“I didn’t expect that. Even though my grandmother struggled to remember other family members that she saw all the time, she somehow remembered me,” Jeong added. “It made me wonder how the brain distinguishes between familiar and new experiences.”

That experience inspired Jeong to embark on a deep-dive exploration of spatial learning and memory, which has resulted in a new study published this month in the journal Nature.

In their article, Jeong, Singer, and a team of Georgia Tech researchers explain how the brain rapidly learns and remembers important locations.

“The brain relies on spatial learning to navigate the world, whether it’s finding a shortcut through a new neighborhood or remembering where you parked your car,” said Jeong, the paper’s lead author.

Read the full story here >>

This year, the College of Sciences’ signature research event centered on the intersection of neuroscience, cognition, and artificial intelligence. Specifically, the event highlighted how AI is transforming our understanding of the brain and how neuroscience and psychology are informing new developments in AI — sparking a wave of innovation.

Dean Susan Lozier, who also serves as Betsy Middleton and John Clark Sutherland Chair and as a professor in the School of Earth and Atmospheric Sciences, emphasized the interdisciplinary nature of the event’s panels — which included faculty from several schools across campus, as well as external keynote speakers. 

“This is an exciting time at the College of Sciences and Georgia Tech. We are working at the forefront of so many questions about intelligence — human, artificial, and where the two converge,” says Lozier. “I hope our community found the concepts and ideas raised during Frontiers in Science as inspiring and thought-provoking as I did.”

Intelligence: From AI to the Brain — and Back

During the full day of talks, a dozen faculty members and researchers from the Colleges of Science, Computing, and Engineering shared some of the latest developments in our understanding of biological and artificial intelligence. Morning sessions explored how AI is driving innovations in cognitive science and neuroscience research, unearthing new insights into cognitive function. Afternoon presentations focused on what the brain can tell us about AI and how such information might direct AI advances. 

Presentations led by Ida Momennejad of Microsoft and Hal Greenwald of the Air Force Office of Scientific Research provided industry and government insights — particularly as related to research trends and challenges.

The midday poster session, which featured 90-second presentations by nine students and post-doctoral researchers, gave attendees the opportunity to learn more about the research conducted in Georgia Tech labs. Nikolas McNeal, a Ph.D. scholar in machine learning, and Aishawarya Balwani, a Ph.D. scholar in electrical and computer engineering, were recognized for best posters.

Frontiers in Science concluded with a session dedicated to audience questions, which encouraged reflections on AI’s future in our society and the range of environmental, safety, and philosophical questions raised by transformative technology. 

Cognition and intelligence at Tech

The 2025 edition of Frontiers in Science comes at a pivotal moment at Georgia Tech, as the Institute continues to expand its research and teaching leadership in biological and artificial intelligence. 

Georgia Tech Executive Vice President for Research Tim Lieuwen, who also serves as Regents’ Professor and David S. Lewis, Jr. Chair in the Daniel Guggenheim School of Aerospace Engineering, noted that the Institute is leading the way in AI innovation. He spotlighted some of Georgia Tech’s newest initiatives and programs, including Tech AI — an interdisciplinary hub connecting cutting-edge AI research taking place on campus with AI-driven applications and solutions for our world.

Other recent developments include the creation of the Center of Excellence in Computation Cognition and the Institute for Neuroscience, Neurotechnology, and Society, which builds upon the Neuro Next Initiative. A minor in computation and cognition and a Ph.D. in neuroscience and neurotechnology are two of the latest additions to Georgia Tech’s academic offerings. The latter builds on the B.S. in neuroscience program, currently the fastest-growing undergraduate major at the Institute.

Experience the event in pictures through the College of Sciences’ Flickr account, and discover the highlights via the day’s live publications on Georgia Tech Neuro Next Initiative’s accounts on BlueSky and X.

“This year's Fellows are the embodiment of scientific excellence and service to our communities...their work demonstrates the value of sustained investment in science and engineering,” says Sudip S. Parikh, AAAS chief executive officer and executive publisher of the Science family of journals. 

A self-professed physicist by training and temperament, Goldman’s research investigates how organisms such as centipedes, snakes, worms, and even plant roots navigate the complexities of the natural world. What makes his research unique is that rather than studying organisms in simple environments, he studies them in environments that more closely mimic their natural habitats such as sandy, loose terrain.

The former Dunn Family Professor in the School of Physics, Goldman has also earned the NSF CAREER Award, DARPA Young Investigator Award, an American Physical Society Fellowship, and the Georgia Power Professor of Excellence Award.

“Becoming an AAAS Fellow is an incredible honor,” says Goldman. “However, in many ways I feel I’m just the person representing the results of more than 20 years of effort from my students and post-docs, as well as my mentors who helped me find this incredibly interesting field of study.”

Pioneering robophysical modeling

Nearly 20 years ago, Goldman became fascinated with studying the physics of how a small lizard wriggled through sand. Today, he has carved a unique niche in biological physics, including advancing a robophysical modeling approach incorporating the animal’s motion pattern to supplement understanding of principles related to organism movement. The approach has led to his recent development of limbless and multi-legged robots for use in agricultural efforts and search and rescue.

Now, Goldman directs the CRAB (Complex Rheology and Biomechanics) Lab, which focuses on developing robots beyond traditional bio-inspired robots through a strong physics-based perspective to biological questions.

“As a physicist, I try to find the underlying principle governing certain phenomena,” says Goldman. “We’ve been successful in discovering common patterns of movement and applying a beautiful theoretical framework called ‘gauge kinematics’ where we describe tiny nematode worms, sand swimming lizards, and multi-legged centipedes with the same language.”

The practical applications of Goldman’s research are already paving the way for innovations in robotics ranging from space research to agriculture. Goldman’s startup, Ground Control Robotics, has started building robots that can navigate the difficult terrain of crop fields, identify weeds and other pests, and address challenges like herbicide resistance, labor shortages, and plant disease.

“The journey from studying that small lizard swimming in sand to developing robots for agriculture exemplifies the often-unforeseen pathways of scientific research,” says Goldman. “The principles unlocked by observing these seemingly insignificant creatures have proven crucial in understanding how various organisms and subsequently, robots can effectively move through complex environments.

I can’t wait to see where the efforts of my incredible group members take us next!”

Lateral inhibition is when certain neurons suppress the activity of their neighboring neurons. Imagine an artist drawing, darkening the lines around the contours, highlighting the boundaries between objects and space, or objects and other objects. Comparably, in the visual system, lateral inhibition sharpens the contrast between different visual stimuli.

“This research is really getting at how our visual system not only highlights important things, but also actively suppresses irrelevant information in the background,” said lead researcher Bilal Haider, associate professor in the Wallace H. Coulter Department of Biomedical Engineering. “That ability to filter out distractions is crucial.”

Understanding how these inhibitory mechanisms work could provide insights into why people have trouble filtering out distractions or focusing on what’s important, in conditions like autism or ADHD.

“Our findings may also influence how we design artificial intelligence and neural networks,” said Haider, whose team published its work this month in Nature Neuroscience. “Current AI systems treat all the computing units the same, but the brain has figured out how to assign specialized computing roles.”

Joseph Del Rosario, a former graduate student in the Haider lab, was the lead author. Another key contributor was Hannah Choi, assistant professor in the School of Mathematics, and her Research Group in Mathematical Neuroscience. Their team built computational models to test the biological findings.

“Collaborating with mathematicians to really understand the computational principles underlying these inhibitory processes is a great example of how neuroscience can inform fields like AI,” Haider said.

Read more in the Coulter Department of Biomedical Engineering newsroom.

“In the next step toward establishing Tech’s preeminence in neuroscience, I am excited and privileged to guide this new Ph.D. program,” says Cope, a professor in the School of Biological Sciences and Coulter Department of Biomedical Engineering.

A joint effort across the Colleges of Computing, Engineering, and Sciences, the program will educate students and advance the field of neuroscience through an interdisciplinary approach — ultimately integrating neuroscience research and technological development to study all levels of nervous system function. The program expects to enroll its first graduate students in Fall 2025. 

“This student-centered program, built on the strength of our exceptional researchers and educators, will bring about a major shift,” Cope adds. “Students will gain expertise in neuroscience, backed by Georgia Tech’s commitment to tackling grand challenges through a mix of experimental, engineering, and computational approaches.”

Building on the recently launched Neuro Next Initiative in Research, the established Undergraduate Program in Neuroscience, and the interdisciplinary B.S. in Neuroscience degree in the College of Sciences (currently the fastest growing undergraduate major at Georgia Tech), Cope emphasizes that the program will be a win-win for faculty and students.

“Our neuroscience faculty will help students succeed in their careers while also boosting their own research productivity through mentorship and training,” he explains. “Plus, the program will foster stronger connections within our neuroscience community — nothing builds faculty collaboration and integration like a cohort of graduate students."

“With the addition of the graduate program, we’re completing the three foundational pillars that will elevate Georgia Tech among top neuroscience institutions.”

The search for the Executive Director of the forthcoming Institute of Neuroscience, Neurotechnology, and Society is ongoing.

The interdisciplinary degree is a joint effort across the Colleges of Sciences, Computing, and Engineering. The program expects to enroll its first graduate students in Fall 2025, pending approval by the Southern Association of Colleges and Schools Commission on Colleges.

The Institute Curriculum Committee has also approved a new Minor in Neuroscience, set to become available in the Georgia Tech 2024-2025 Catalog.

B.S. in Neuroscience

The Ph.D. and Minor offerings build on the recently launched Neuro Next Initiative in Research, and the established Undergraduate Program in Neuroscience, respectively.

Approved by the Board of Regents in 2017, the interdisciplinary B.S. in Neuroscience degree in the College of Sciences enrolled more than 400 undergraduate students in 2022, and has been  the fastest growing undergraduate major at Georgia Tech.

The B.S. in Neuroscience is also key to a strong ecosystem of undergraduate neuroscience education across the state, which includes peer programs at Mercer University, Augusta University, Georgia State University, Agnes Scott College, and Emory University.

Ph.D. in Neuroscience and Neurotechnology

The new doctoral degree will provide a path for the rapidly growing pipeline of in-state neuroscience undergraduate students and young alumni — while also welcoming a wider slate of graduate researchers to campus.

The Ph.D. Program’s mission is focused on educating students to advance the field of neuroscience through an interdisciplinary approach, with scientists and engineers of different backgrounds — ultimately integrating neuroscience research and technological development to study all levels of nervous system function.

Biological Sciences Professor Lewis A. Wheaton, who chaired the Ph.D. Program Planning Committee, shares that a cohort model will fuse “experimental and quantitative skill development, creating opportunities for students to work in science and engineering labs to promote collaborations, while also fostering a program and community that’s unique to the state and against national peer offerings.”

Expanding innovation — and impact

Wheaton explains that the new Ph.D. aims to equip graduates for a wide range of employment opportunities and growing specializations, including computational neuroscience, neurorehabilitation, cultural and social neuroscience, neuroimaging, cognitive and behavioral neuroscience, developmental neuroscience, and neurolinguistics.

The new degree will also help meet the country’s growing demand for a neuro-centric workforce. According to the U.S. Bureau of Labor Statistics, job growth for medical scientists (including neuroscientists) tracked around 13% between 2012 and 2022, faster than the average for all tracked occupations.

Wheaton adds that the program will equip neuroscientists to conduct research that can significantly improve lives.

Seeking students

The Planning Committee anticipates a tentative February 1, 2025 application deadline for Fall 2025 enrollments — and encourages students with the following interests to learn more and apply in the coming school year:

• Developing deeper quantitative, computing and/or engineering skills to make scientific discoveries that support innovations in neuroscience
• A clear, comprehensive understanding of the nervous system at all scales from molecular to systems
• Understanding how to use and innovate new tools and approaches to investigate the nervous system at all levels
• Becoming uniquely qualified to translate knowledge across neuroscience and related disciplines to create new knowledge in their professional pursuits

Director search

The participating Colleges will soon conduct a search for a program director, engaging a tenured member of the Georgia Tech faculty to serve as the new program’s administrator. A graduate program committee composed of five faculty members and mentors across the Colleges of Sciences, Computing, and Engineering, will also be created.
 

During their April 2024 meeting, Regents also announced budget approvals and tuition changes for Georgia's 26 member institutions.

The Ph.D. Program Planning Committee included the following faculty:

• Lewis Wheaton (Committee Chair, Biological Sciences)
• Constantine Dovrolis (Computer Science)
• Christopher Rozell (Electrical and Computer Engineering)
• Eric Schumacher (Psychology)
• Garrett Stanley (Biomedical Engineering)
• David Collard (College of Sciences Office of the Dean)

The Institute for Neuroscience, Neurotechnology, and Society (INNS) at Georgia Tech has initiated an internal search for its inaugural executive director. This new Interdisciplinary Research Institute (IRI) will build upon the foundation laid by the Neuro Next Initiative, fostering cutting-edge research and innovation at the intersection of neuroscience, neurotechnology, and societal impact.

At the newly established IRI, the executive director will profoundly shape a unifying vision for neuroscience research and innovation at Georgia Tech, integrating various disciplines and fostering collaboration across campus. They will translate research into practical applications, engage students, and connect them to industry networks. The ideal candidate will have a visionary, innovative, and entrepreneurial leadership style, with experience in leading large-scale, interdisciplinary research initiatives, securing external funding, and promoting large-scale initiatives both internally and externally.

INNS aims to advance our understanding of the brain and nervous system, develop transformative technologies, and address critical societal challenges through interdisciplinary collaboration and engagement. INNS is dedicated to advancing innovative research and educational programs in neuroscience, neurotechnology, and society; fostering a broad and engaged community; and empowering society through public engagement and responsible technology deployment.

Click here to learn more about this position and how to apply.

Farzaneh Najafi, an assistant professor in Georgia Tech’s School of Biological Sciences(SBS) , recently received multiple awards that will enable her to dig deeper into the molecular origins of cognitive processes, with the help of interdisciplinary teams.

“If we want to understand cognition, we really have to start small: at the level of molecules, genes, and the genome, and then work our way up to systems, behavior, and cognition,” says Najafi. “Impactful discoveries happen when people from different disciplines come together and collaborate. That’s how we make real breakthroughs.”

Two of her recent awards stem from the third and final year of the Scialog: Molecular Basis of Cognition initiative. Funded by the Research Corporation for Science Advancement (RCSA), the Frederick Gardner Cottrell Foundation, and the Walder Foundation, this initiative has provided 48 multidisciplinary teams with more than $2.4 million to advance this area of research.

“It’s exciting that Farzaneh has won not just one, but two team-based Scialog awards,” said SBS School Chair Jeffrey (Todd) Streelman. “Solving big problems in neuroscience often requires teams, and Farzaneh is well-placed to apply this in her research program.”

With additional funding from the Whitehall Foundation and Chan Zuckerberg Initiative, Najafi is set to lead several interdisciplinary projects to uncover the role of the cerebellum and neocortex (the brain’s outer layer) across distinct cognitive processes. 

“At the end of the day, the goal is to develop effective therapeutics,” says Najafi, whose work has long aimed to better understand and treat psychiatric and neurological disorders. “To develop targeted treatments, we have to identify the molecules that are at the core of these cognitive processes.”

Deeper than thought

Throughout her career, Najafi has focused on how the brain makes and uses predictions to influence learning and behavior, with a particular focus on an area in the back of the brain called the cerebellum.

“Without those predictions, our perceptions and actions would be significantly delayed, which could impact our survival,” explains Najafi. “Learning happens when we update those predictions to better align with the world around us.”

Najafi will bring that cerebellar expertise to two collaborative teams with the Scialog initiative.

Working with researchers from Stanford University and Case Western Reserve University, one of Najafi’s Scialog projects will focus on how sleep deprivation alters the 3D structure of genetic material in different species’ cerebellum— and investigate potential mechanisms to reverse those changes. 

Her second project, in collaboration with researchers from University of California San Francisco and Duke University, explores how the brain chemical norepinephrine affects cerebellar activity across species. This research aims to understand the cerebellum's role in behavioral flexibility and adaptation, revealing how these chemical signals influence various brain functions.

Working across disciplines

Formed at the October 2024 Scialog meeting, Najafi’s two collaborative teams are part of an RCSA initiativethat unites early career scientists in advancing basic science and developing high-risk, high-reward research projects. The Scialog: Molecular Basis of Cognition initiative, begun in 2022, annually gathered around 50 early career researchers to create collaborative proposals.

“The best part of the Scialog meeting was connecting with people from all kinds of disciplines. They worked with different species, used a variety of experimental and computational tools, and some attendees came from non-neuroscience backgrounds,” says Najafi. “I had no idea that these were the topics I was going to write about — they only came about because of the inspiring conversations I had at the meeting. I really loved the experience.”

Both Scialog teams are highly interdisciplinary, with researchers bringing expertise in different techniques and species to the team. Even within her own lab, Najafi attributes impactful research to interdisciplinary teams.

“The only way to solve big questions in neuroscience is through an interdisciplinary approach,” says Najafi, who is affiliated with two Interdisciplinary Research Institutes (IRI) at Georgia Tech: the Parker H. Petit Institute for Bioengineering and Bioscience and the Neuro Next Initiative, a nascent IRI in neuroscience and society. “What’s great about Georgia Tech is its strong emphasis on interdisciplinary collaboration. With these research institutes, the infrastructure is already in place, and they're actively working to expand it.”

“Professor Greg Sawicki will make a great interim executive director of IRIM. He brings experience with robotics and collaborative research to this role,” said Julia Kubanek, professor and vice president for interdisciplinary research at Georgia Tech. “He'll be a strong partner to faculty, students, and the EVPR team as we explore the future of IRIM and robotics over the next several months."

Sawicki succeeds Seth Hutchinson who will be taking a new position at Northeastern University in Boston. Hutchinson, professor and KUKA Chair for Robotics in Georgia Tech’s College of Computing, has served as executive director of IRIM for six years. During Hutchinson’s tenure as executive director, IRIM expanded its industry outreach activities, developed more consistent communications, and grew its faculty pool at Georgia Tech to include a diverse cohort from across the Colleges of Engineering and Computing and the Georgia Tech Research Institute. 

"I am extremely excited to step into this leadership role for IRIM, maintain our research excellence in the foundational areas of robotics, and proactively leverage opportunities to grow across campus and beyond in novel, creative interdisciplinary directions,” said Sawicki. “This will involve new initiatives to incentivize connections with GTRI and other IRI's on campus, to build new industry partnerships, and continue to strengthen the M.S./Ph.D. program in Robotics by engaging with Schools beyond those with a traditional footprint in robotics education and research.”

Sawicki directs the Human Physiology of Wearable Robotics (PoWeR) Lab where he and his group seek to discover physiological principles underpinning locomotion performance and apply them to develop lower-limb robotic devices capable of improving both healthy and impaired human locomotion. By focusing on the human side of the human-machine interface, his team has begun to create a roadmap for the design of lower-limb robotic exoskeletons that are truly symbiotic – that is, wearable devices that work seamlessly in concert with the underlying physiological systems to facilitate the emergence of augmented human locomotion performance.

Sawicki earned a B.S. in mechanical and aerospace engineering from Cornell University in 1999, an M.S. in mechanical and aeronautical engineering from the University of California - Davis in 2001, and a Ph.D. in neuromechanics at the University of Michigan-Ann Arbor in 2007. Sawicki completed his postdoctoral studies in integrative biology at Brown University in 2009.

Sawicki has been recognized for his interdisciplinary research and teaching, recently receiving a $2.6 million Research Project Grant from the National Institutes of Health (NIH) to study optimization and artificial intelligence to personalize exoskeleton assistance for individuals with symptoms resulting from stroke. * Sawicki was also selected as a 2021 George W. Woodruff School Academic Leadership Fellow, and the 2022 College of Sciences Student Recognition of Excellence in Teaching and the 2023 American Society of Biomechanics Founders’ Award for excellence in research and mentoring. Sawicki has also been featured as an expert voice on exoskeletons and human neuromechanics in numerous print and television news releases.

--Christa M. Ernst

*Joint Award with Aaron Young, Assistant Professor in the Woodruff School of Mechanical Engineering

Though the field has made great progress in the hardware and devices for these assistive technologies, there are limitations in ease of use and in the ability to move from walking to running, from flat ground to slopes and stairs, and across different terrains.  Recent developments to create exoskeleton controllers that are more responsive to the user’s environment via user-based variables such as gait and slope calculations provide rapid yet imprecise outputs. More recent inquiry into data-driven improvements such as vision-based labeling and classification are extremely promising additions in the goal to develop a true synchronous user and device interface. A major hindrance to this data-driven approach is the need for burdensome mounted cameras and on-board computing to allow for real-time in use adjustments to the environmental terrain encountered. 

In order to address these barriers, Aaron Young, Associate Professor in the Woodruff School of Mechanical Engineering and Director of the Exoskeleton and Prosthetic Intelligent Controls (EPIC) Lab, and Dawit Lee, Postdoctoral Scholar at Stanford, have created an artificial intelligence (AI)-based universal exoskeleton controller that uses information from onboard mechanical sensors without the added weight and complexity of mounted vision based systems. The new work, published in Science Advances (Link to Be Added), presents a controller that holistically captures the major variations encountered during community walking in real-time. The team combined data from the Americans with Disabilities Act (ADA) building guidelines that characterize ambulatory terrains in slope level degrees with a gait phase estimator to achieve dynamic switching of assistance types between multiple terrains and slopes and delivery to the user with little to no delay.

In this work, we have created a new, open-source knee exoskeleton design that is intended to support community mobility. Knee assist devices have tremendous value in activities such as sit-to-stand, stairs, and ramps where we use our biological knees substantially to accomplish these tasks. The neat accomplishment in this work is that by leveraging AI, we avoid the need to classify these different modes discretely but rather have a single continuous variable (in this case rise over run of the surface) to enable continuous and unified control over common ambulatory tasks such as walking, stairs, and ramps. We demonstrate that on novel users of the device, we can track both the environment and the user’s gait state with very high accuracy out of the lab in community settings. It is an exciting time in the field as we see more studies, such as this one, showing promise in tackling real-world mobility challenges

    - Aaron Young, Associate Professor in the Woodruff School of Mechanical Engineering and Director of the Exoskeleton and Prosthetic Intelligent Controls (EPIC) Lab

The assistance approach using our intelligent controller, presented in this work, provides users with support at the right timing and with a magnitude that closely matches the varying biomechanical effort they produce as they move through the community. Our assistance approach was preferred for community navigation and was more effective in reducing the user’s energy consumption compared to conventional methods. We also open-sourced the design of the robotic knee exoskeleton hardware and the dataset used to train the models with this publication which allows other researchers to build upon our developments and further advance the field. This work demonstrates an exciting example of AI integration into a wearable robotic system, showcasing its successful outcomes and significant potential.

    - Dawit Lee; Postdoctoral Scholar, Stanford

Using this combination of a universal slope estimator and a gait phase estimator, the team achieved results in the dynamic modulation of exoskeleton assistance that have never been achieved by previous approaches and moves the field closer to creating an adaptive and effective assistive technology that seamlessly integrates into the daily lives of individuals, promoting enhanced mobility and overall well-being. This work also has the potential to enable a mode-specific assistance approach tailored to the user’s specific biomechanical needs.

The human brain is often seen as the world's most complex computer, processing vast amounts of information, learning from experiences, and making complex decisions. Georgia Tech’s Center of Excellence in Computational Cognition (CoCo) was established in 2023 to better understand this “biological computer” using the principles of computation and mathematics.