Irfan Essa is a Professor in the School of Interactive Computing and Senior Associate Dean in the College of Computing (CoC), at the Georgia Institute of Technology. Professor Essa works in the areas of Computer Vision, Artificial Intelligence, Machine Learning, Robotics, Computer Graphics, and Social Computing, with potential impact on Content Creation, Analysis and Production (e.g., Computational Photography & Video, Image-based Modeling and Rendering, etc.) Human Computer Interaction, Artificial Intelligence, Computational Behavioral/Social Sciences, and Computational Journalism research.He has published over 150 scholarly articles in leading journals and conference venues on these topics and several of his papers have also won best paper awards. He has been awarded the National Science Foundation CAREER Award and was elected an IEEE Fellow. He has held extended research consulting positions with Disney Research and Google Research and also was an Adjunct Faculty Member at Carnegie Mellon's Robotics Institute. He joined Georgia Tech in 1996 after his earning his Master's (1990), Ph.D. (1994), and holding a research faculty position at the Massachusetts Institute of Technology Media Lab (1988-1996).

Jaydev P. Desai, Ph.D, is currently a Professor and BME Distinguished Faculty Fellow in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech. Prior to joining Georgia Tech in August 2016, he was a Professor in the Department of Mechanical Engineering at the University of Maryland, College Park (UMCP). He completed his undergraduate studies from the Indian Institute of Technology, Bombay, India, in 1993. He received his M.A. in Mathematics in 1997, M.S. and Ph.D. in Mechanical Engineering and Applied Mechanics in 1995 and 1998 respectively, all from the University of Pennsylvania. He was also a Post-Doctoral Fellow in the Division of Engineering and Applied Sciences at Harvard University. He is a recipient of several NIH R01 grants, NSF CAREER award, and was also the lead inventor on the "Outstanding Invention of 2007 in Physical Science Category" at the University of Maryland, College Park. He is also the recipient of the Ralph R. Teetor Educational Award. In 2011, he was an invited speaker at the National Academy of Sciences "Distinctive Voices" seminar series on the topic of "Robot-Assisted Neurosurgery" at the Beckman Center. He was also invited to attend the National Academy of Engineering's 2011 U.S. Frontiers of Engineering Symposium. He has over 150 publications, is the founding Editor-in-Chief of the Journal of Medical Robotics Research, and Editor-in-Chief of the Encyclopedia of Medical Robotics (currently in preparation). His research interests are primarily in the area of image-guided surgical robotics, rehabilitation robotics, cancer diagnosis at the micro-scale, and rehabilitation robotics. He is a Fellow of the ASME and AIMBE.

Dr. Dellaert does research in the areas of robotics and computer vision, which present some of the most exciting challenges to anyone interested in artificial intelligence. He is especially keen on Bayesian inference approaches to the difficult inverse problems that keep popping up in these areas. In many cases, exact solutions to these problems are intractable, and as such he is interested in examining whether Monte Carlo (sampling-based) approxIMaTions are applicable in those cases.

Sam Coogan received the B.S. degree in Electrical Engineering from Georgia Tech and the M.S. and Ph.D. degrees in Electrical Engineering from the University of California, Berkeley. In 2015, he was a postdoctoral research engineer at Sensys Networks, Inc., and in 2012 he spent time at NASA's Jet Propulsion Lab. Before joining Georgia Tech in 2017, he was an assistant professor in the Electrical Engineering department at UCLA from 2015–2017. His awards and recognitions include the 2020 Donald P Eckman Award from the American Automatic Control Council recognizing "an outstanding young engineer in the field of automatic control", a Young Investigator Award from the Air Force Office of Scientific Research in 2019, a CAREER Award from the National Science Foundation in 2018, and the Outstanding paper award for the IEEE Transactions on Control of Network Systems in 2017.

I am an Associate Professor in the School of Interactive Computing at Georgia Tech. I received my Ph.D. and B.S. degrees in Computer Science from Carnegie Mellon University, and held positions as a Postdoctoral Associate at the MIT Media Lab and as Assistant Professor at Worcester Polytechnic Institute prior to joining Georgia Tech. I direct the Robot Autonomy and Interactive Learning (RAIL) lab, where we work on developing robots that are able to effectively operate in human environments. My research interests span robotics and artificial intelligence, including semantic reasoning, adjustable autonomy, human computation and cloud robotics. Please visit the RAIL lab website for a description of our latest projects.

Yongxin Chen was born in Ganzhou, Jiangxi, China. He received his BSc in Mechanical Engineering from Shanghai Jiao Tong university, China, in 2011, and a Ph.D. degree in Mechanical Engineering, under the supervision of Tryphon Georgiou, from University of Minnesota in 2016. He is currently an Assistant Professor in the School of Aerospace Engineering at Georgia Institute of Technology. Before joining Georgia Tech, he had a one-year Research Fellowship in the Department of Medical Physics at Memorial Sloan Kettering Cancer Center with Allen Tannenbaum from 2016.8 to 2017.8 and was an Assistant Professor in the Department of Electrical and Computer Engineering at Iowa State University from 2017.8 to 2018.8. He received the George S. Axelby Best Paper Award (IEEE Transaction on Automatic Control) in 2017 for his joint work "Optimal steering of a linear stochastic system to a final probability distribution, Part I" with Tryphon Georgiou and Michele Pavon.

Young-Hui Chang is a professor in the School of Biological Sciences, Associate Dean of Faculty for College of Sciences, and director of research in the Georgia Tech Comparative Neuromechanics Lab where he studies the neuromechanics of movement in humans and other animals. Chang’s aim is to understand fundamental principles by which we control our movements as we move through our physical environment. This requires knowledge of the neural control of movement, the biomechanics of our musculoskeletal system, and the physics of our environmental interactions. The team also studies how our body adapts to acute and chronic changes. This involves processes of motor learning that are involved in everything from clinical rehabilitation to elite sports performance.

Saad Bhamla studies biomechanics across species to engineer knowledge and tools that inspire curiosity.

Saad Bhamla is an assistant professor of biomolecular engineering at Georgia Tech. A self-proclaimed "tinkerer," his lab is a trove of discoveries and inventions that span biology, physics and engineering. His current projects include studying the hydrodynamics of insect urine, worm blob locomotion and ultra-low-cost devices for global health. His work has appeared in the New York Times, the Economist, CNN, Wired, NPR, the Wall Street Journal and more.

Saad is a prolific inventor and his most notable inventions includes a 20-cent paper centrifuge, a 23-cent electroporator, and the 96-cent hearing aid. Saad's work is recognised by numerous awards including a NIH R35 Outstanding Investigator Award, NSF CAREER Award, CTL/BP Junior Faculty Teaching Excellence Award, and INDEX: Design to Improve Life Award. Saad is also a National Geographic Explorer and a TED speaker. Newsweek recognized Saad as 1 of 10 Innovators disrupting healthcare.

Saad is a co-founder of Piezo Therapeutics.

Outside of the lab, Saad loves to go hiking with his partner and two dogs (Ollie and Bella).

Dhruv Batra is an Associate Professor in the School of Interactive Computing at Georgia Tech. His research interests lie at the intersection of machine learning, computer vision, natural language processing, and AI, with a focus on developing intelligent systems that are able to concisely summarize their beliefs about the world with diverse predictions, integrate information and beliefs across different sub-components or `modules' of AI (vision, language, reasoning, dialog), and interpretable AI systems that provide explanations and justifications for why they believe what they believe. In past, he has also worked on topics such as interactive co-segmentation of large image collections, human body pose estIMaTion, action recognition, depth estIMaTion, and distributed optimization for inference and learning in probabilistic graphical models. He is a recipient of the Office of Naval Research (ONR) Young Investigator Program (YIP) award (2016), the National Science Foundation (NSF) CAREER award (2014), Army Research Office (ARO) Young Investigator Program (YIP) award (2014), Virginia Tech College of Engineering Outstanding New Assistant Professor award (2015), two Google Faculty Research Awards (2013, 2015), Amazon Academic Research award (2016), Carnegie Mellon Dean's Fellowship (2007), and several best paper awards (EMNLP 2017, ICML workshop on Visualization for Deep Learning 2016, ICCV workshop Object Understanding for Interaction 2016) and teaching commendations at Virginia Tech. His research is supported by NSF, ARO, ARL, ONR, DARPA, Amazon, Google, Microsoft, and NVIDIA. Research from his lab has been extensively covered in the media (with varying levels of accuracy) at CNN, BBC, CNBC, Bloomberg Business, The Boston Globe, MIT Technology Review, Newsweek, The Verge, New Scientist, and NPR. From 2013-2016, he was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech, where he led the VT Machine Learning & Perception group and was a member of the Virginia Center for Autonomous Systems (VaCAS) and the VT Discovery Analytics Center (DAC). From 2010-2012, he was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), a philanthropically endowed academic computer science institute located on the University of Chicago campus. He received his M.S. and Ph.D. degrees from Carnegie Mellon University in 2007 and 2010 respectively, advised by Tsuhan Chen. In past, he has held visiting positions at the Machine Learning Department at CMU, CSAIL MIT, Microsoft Research, and Facebook AI Research.