Prof. Singh has a joint appointment with the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University.

Prof. Singh started at Cornell University as an Assistant Professor in 2013 and was promoted with tenure to Associate Professor with joint appointments in the Mechanical Engineering and Biomedical Engineering. At Cornell, he served as the Associate Director of the NIH T32 training grant on Immuno-engineering, executive council of the Center for Immunology, and the Cornell (Ithaca) – Weill Cornell Medicine (NYC) Academic Integration initiative. Prior to joining Cornell, he completed his postdoctoral training in cell mechanobiology, cell-matrix interactions, and stem cell engineering at Georgia Tech in Mechanical Engineering.

Richard Simmons is currently a Principal Research Engineer and Fellow at Georgia Tech’s Strategic Energy Institute (SEI) where he directs cross-cutting energy projects with an emphasis on clean electric power, vehicle efficiency and alternative fuels. Simmons is also director of the Energy Policy and Innovation Center (EPICenter) whose objective is to perform research and outreach in energy policy and innovation with a distinctively regional perspective. He is also a part-time instructor in Georgia Tech’s Woodruff School of Mechanical Engineering, with a specialization in design, mechatronics and thermal systems. 

Simmons received his BS from Georgia Tech, and MS and Ph.D. from Purdue, all in Mechanical Engineering. He is a licensed professional engineer (PE) with more than 20 years of RD&D experience in automotive, advanced materials, and alternative energy and fuels. 

From 2009 to 2012, he served a prestigious American Association for the Advancement of Science S&T (Science and Technology) Policy Fellowship at the U.S. Department of State, providing technical analysis on international policy issues related to renewable energy. He has recently authored numerous publications including an open-access eBook entitled “Understanding the Global Energy Crisis” (Purdue Press, 2014), several book chapters and journal articles related to advanced energy technologies, transportation energy technology, and future energy policy strategies.

Yao Xie is a Coca-Cola Foundation Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech, which she joined in 2013 as an Assistant Professor. She also serves as Associate Director of Machine Learning and Data Science of the Center for Machine Learning. From September 2017 until March 2023 she was the Harold R. and Mary Anne Nash Early Career Professor. She was a Research Scientist at Duke University from 2012 to 2013. 

Her research lies at the intersection of statistics, machine learning, and optimization in providing theoretical guarantees and developing computationally efficient and statistically powerful methods for problems motivated by real-world applications. 

She is currently an Associate Editor for IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, Journal of the American Statistical Association: Theory and Methods, Sequential Analysis: Design Methods and Applications, INFORMS Journal on Data Science, and an Area Chair of NeurIPS and ICML.

Dr. Justin Romberg is the Schlumberger Professor and the Associate Chair for Research in the School of Electrical and Computer Engineering and the Associate Director for the Center for Machine Learning at Georgia Tech.

Dr. Romberg received the B.S.E.E. (1997), M.S. (1999) and Ph.D. (2004) degrees from Rice University in Houston, Texas. From Fall 2003 until Fall 2006, he was a Postdoctoral Scholar in Applied and Computational Mathematics at the California Institute of Technology. He spent the Summer of 2000 as a researcher at Xerox PARC, the Fall of 2003 as a visitor at the Laboratoire Jacques-Louis Lions in Paris, and the Fall of 2004 as a Fellow at UCLA's Institute for Pure and Applied Mathematics. In the Fall of 2006, he joined the Georgia Tech ECE faculty. In 2008 he received an ONR Young Investigator Award, in 2009 he received a PECASE award and a Packard Fellowship, and in 2010 he was named a Rice University Outstanding Young Engineering Alumnus. He is currently on the editorial board for the SIAM Journal on the Mathematics of Data Science, and is a Fellow of the IEEE.

His research interests lie on the intersection of signal processing, machine learning, optimization, and applied probability.

Dr. Lewis A. Wheaton received his Ph.D. in Neuroscience and Cognitive Sciences from the University of Maryland, College Park in 2005. He was a fellow at the National Institutes of Health (Medical Neurology Branch, 2001-2005) studying neural function and recovery of motor control after stroke. In mid-2005 he was awarded a post-doctoral fellowship at the Baltimore Veterans Affairs Medical Center (Maryland) where he performed neuroscience research in aging and stroke motor control in Veterans.

In 2008, Dr. Wheaton joined the School of Applied Physiology at Georgia Tech as an Assistant Professor. He became tenured in 2014 and is currently an Associate Professor in Biological Sciences. Dr. Wheaton is the Director of the Cognitive Motor Control Laboratory at Georgia Tech, engaged in over $1 million in state and federal research funding focused on understanding aspects of human motor control rehabilitation in aging, stroke and amputation. His lab has employed numerous high school, undergraduate, graduate, and post-doctoral fellows. He is the course director for 4 courses in the School of Biological Sciences (Human Neuroimaging, Movement Disorders, Human Neuroanatomy, and the History of Neuroscience). He has Chaired/Co-Chaired 3 international conferences focused on motor control research and clinical outcomes, obtaining funding by federal and private sources. His research has yielded several manuscript publications in the field of motor control neuroscience, several focused expert reviews, and numerous conference presentations both in the US and abroad.

Dr. Wheaton is also an adjunct Associate Professor in the Department of Rehabilitation at Emory School of Medicine and a Member of the Children’s Center for Neurosciences Research at the Emory Children’s Pediatric Research Center.

Dr. Wheaton earned a BS (Biology) degree at Radford University (VA). He is an active parent volunteer at his children's schools and in the local community.

Valerie Thomas is the Anderson-Interface Chair of Natural Systems and Professor in the H. Milton School of Industrial and Systems Engineering, with a joint appointment in the School of Public Policy. 

Dr. Thomas's research interests are energy and materials efficiency, sustainability, industrial ecology, technology assessment, international security, and science and technology policy. Current research projects include low carbon transportation fuels, carbon capture, building construction, and electricity system development. Dr. Thomas is a Fellow of the American Association for the Advancement of Science, and of the American Physical Society. She has been an American Physical Society Congressional Science Fellow, a Member of the U.S. EPA Science Advisory Board, and a Member of the USDA/DOE Biomass Research and Development Technical Advisory Committee. 

She has worked at Princeton University in the Princeton Environmental Institute and in the Center for Energy and Environmental Studies, and at Carnegie Mellon University in the Department of Engineering and Public Policy.

Dr. Thomas received a B. A. in physics from Swarthmore College and a Ph.D. in theoretical physics from Cornell University.

Physiological and biomechanical mechanisms underlying fine motor skills and their adjustments and adaptations to heightened sympathetic nerve activity, aging or inactivity, space flight or microgravity, neuromuscular fatigue, divided attention, and practice in humans. He uses state-of-the-art techniques in neuroscience, physiology, and biomechanics (e.g., TMS, EEG, fMRI, single motor unit recordings, microneurography, mechanomyography, ultrasound elastography, and exoskeleton robot) in identifying these mechanisms.

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.

Animesh Garg is a Stephen Fleming Early Career Assistant Professor at School of Interactive Computing at Georgia Tech. He leads the People, AI, and Robotics (PAIR) research group. He is on the core faculty in the Robotics and Machine Learning programs. Animesh is also a Senior Researcher at Nvidia Research. Animesh earned a Ph.D. from UC Berkeley and was a postdoc at the Stanford AI Lab. He is on leave from the department of Computer Science at University of Toronto and CIFAR Chair position at the Vector Institute.

Garg earned his M.S. in Computer Science and Ph.D. in Operations Research from UC, Berkeley. He worked with Ken Goldberg at Berkeley AI Research (BAIR). He also worked closely with Pieter Abbeel, Alper Atamturk & UCSF Radiation Oncology. Animesh was later a postdoc at Stanford AI Lab with Fei-Fei Li and Silvio Savarese.

Garg's research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments. His group focuses on understanding structured inductive biases and causality on a quest for general-purpose embodied intelligence that learns from imprecise information and achieves flexibility & efficiency of human reasoning.