Ratan obtained his PhD in Neuroscience from the Indian Institute of Science, Bangalore (India) with Prof. SP Arun and completed his postdoctoral research at the Massachusetts Institute of Technology with Profs. Nancy Kanwisher and James J DiCarlo.​ He leads the Murty Vision, Cognition, and Computation Lab at Georgia Tech.

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Ratan's research goal is to understand the neural codes and algorithms that support human vision.

Christopher J. MacLellan is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology, where he leads the Teachable AI Lab (TAIL; https://tail.cc.gatech.edu). His work on cognitive systems aims to advance our understanding of how people teach and learn and to build AI systems that can teach and learn like people do and in ways that are compatible with people. He explores the development of computational models of learning and how these models can support the development of AI technologies, such as intelligent tutoring systems and medical decision support systems, at scale.

He also investigates how data collected about how people learn and make decisions can be leveraged to drive the development of better cognitive models and computational learning systems. Chris has been a principal investigator on multiple sponsored project awards with DARPA, the U.S. Army, ONR, and NSF. He has also received external recognition for his work, such as the 2022 EAAI Now and Future AI Educator award as well as being named on the 2021 Technical.ly RealLIST of technologists building Philadelphia’s future.  

Prior to his position at Georgia Tech, Chris was an Assistant Professor of Information Science and Computer Science (by co-appointment) at Drexel University. Before that, he completed his PhD in Human-Computer Interaction at Carnegie Mellon University's School of Computing, where he was a fellow in the Program for Interdisciplinary Education Research (PIER).

The products of his work have immediate implications for AI-powered technology development. For example, through his work with the NSF-funded AI ALOE Institute, Chris is developing tools that let teachers build AI-powered tutors by naturally teaching an AI agent rather than programming. His work also has many broader implications, such as enabling doctors to support the development of AI-powered diagnoses tools where few training examples are available (DARPA-funded POCUS project) and for creating personal assistant agents that can engage in collaborative learning to support more effective human-machine teaming (ARL-funded STRONG project).

Research Areas: 

Artificial Intelligence; Cognitive Systems; Cognitive and Learning Sciences; Human-Computer Interaction; Learning Technology.

Neha Kumar is an Associate Professor jointly appointed at the Sam Nunn School of International Affairs and the School of Interactive Computing at Georgia Tech. Her research lies at the intersection of human-computer interaction and global sustainable development, with a focus on global health and community informatics. Her work contributes feminist perspectives to the design and integration of emerging technologies across marginalized contexts in the Global South. 

Her research has been recognized by multiple ACM Best Paper and Honorable Mention awards. Neha received the College of Computing's Lockheed Inspirational Young Faculty Award (2017) and the Lockheed Excellence in Teaching Award (2019). She currently serves as the President of ACM SIGCHI. She earned her Ph.D. in Information Management Systems from UC Berkeley, Master’s degrees in Computer Science and Education from Stanford University, and Bachelor’s in Computer Science and Applied Math from UC Berkeley.

I am an Assistant Professor at the School of Interactive Computing in the College of Computing. I am also affiliated with the Georgia Tech Research Institute and serve as an Associate Director of ML@GT which is the machine learning center recently created at Georgia Tech. Previously I was a Research Scientist at SRI International Sarnoff in Princeton, and before that received my Ph.D. in 2010 with Professor Ron Arkin as my advisor. I lead the RobotIcs Perception and Learning (RIPL) lab. My areas of research specifically focus on the intersection of learning methods for sensor processing and robotics, developing novel machine learning algorithms and formulations towards solving some of the more difficult perception problems in these areas. I am especially interested in moving beyond supervised learning (un/semi/self-supervised and continual/lifelong learning) as well as distributed perception (multi-modal fusion, learning to incorporate information across a group of robots, etc.).

Jennifer Gahee Kim is an Assistant Professor in the School of Interactive Computing at the Georgia Institute of Technology. She holds a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign. Dr. Kim’s research interests lie in human-computer interaction and digital health, where she investigates how social and health information systems can be designed to promote diversity, advocacy, and empathy. With her research, she is especially passionate about impacting the lives of neurodiverse people and the communities around them.

Research Areas:
Human-Computer Interaction (HCI); Computer-Supported Cooperative Work (CSCW); Digital Health; Neurodiversity

Josiah Hester works broadly in computer engineering, with a special focus on wearable devices, edge computing, and cyber-physical systems. His Ph.D. work focused on energy harvesting and battery-free devices that failed intermittentently. He now focuses on sustainable approaches to computing, via designing health wearables, interactive devices, and large-scale sensing for conservation. 
   
His work in health is focused on increasing accessibility and lowering the burden of getting preventive and acute healthcare. In both situations, he designs low-burden, high-fidelity wearable devices that monitor aspects of physiology and behavior, and use machine learning techniques to suggest or deliver adaptive and in-situ interventions ranging from pharmacological to behavioral. 
   
His work is supported by multiple grants from the NSF, NIH, and DARPA. He was named a Sloan Fellow in Computer Science and won his NSF CAREER in 2022. He was named one of Popular Science's Brilliant Ten, won the American Indian Science and Engineering Society Most Promising Scientist/Engineer Award, and the 3M Non-tenured Faculty Award in 2021. His work has been featured in the Wall Street Journal, Scientific American, BBC, Popular Science, Communications of the ACM, and the Guinness Book of World Records, among many others.

Professor Hays's research interests span computer vision, graphics, robotics, and machine learning. Before joining Georgia Tech, he was the Manning assistant professor of computer science at Brown University. James was a post-doc at Massachusetts Institute of Technology and received his Ph.D. from Carnegie Mellon University in 2009. James received his B.S. in Computer Science from Georgia Tech in 2003.

I'm an assistant professor at Georgia Institute of Technology. Before joining Georgia Tech, I was a research scientist at Google and Disney Research Pittsburgh. I received my Ph.D. in Computer Science from the Georgia Institute of Technology in 2015. My advisor was Dr. C. Karen Liu. I have a B.S. degree in Computer Science from KAIST in 2009. I am interested in character animation, robotics, and artificial intelligence.