Harish is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology. He is also a core faculty member of Georgia Tech’s Institute for Robotics and Intelligent Machines (IRIM). His research interests span the areas of robot learning, human-robot interaction, and multi-agent systems. He directs the Structured Techniques for Algorithmic Robotics (STAR) Lab, where he and his team works on structured algorithms that help robots reliably operate and collaborate in unstructured environments alongside humans.

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.).

Alenka Zajic is currently the Ken Byers Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. She has received the B.Sc. and M.Sc. degrees from the University of Belgrade, Belgrade, Serbia, in 2001 and 2003, respectively, and the Ph.D. degree in electrical and computer engineering from the Georgia Institute of Technology, Atlanta, in 2008. Before joining Georgia Tech as an assistant professor, Zajic was a post-doctoral fellow in the Naval Research Laboratory and visiting faculty in the School of Computer Science at the Georgia Institute of Technology. Zajic is the recipient of the following awards: IEEE Atlanta Section Outstanding Engineer Award (2019), The Best Poster Award at the IEEE International Conference on RFID (2018), NSF CAREER Award (2017), Best Paper Award at the 49th Annual IEEE/ACM International Symposium on Microarchitecture (2016), the Best Student Paper Award at the IEEE International Conference on Communications and Electronics (2014), Neal Shepherd Memorial Best Propagation Paper Award (2012), the Best Paper Award at the International Conference on Telecommunications (2008), the Best Student Paper Award at the Wireless Communications and Networking Conference (2007), IEEE Outstanding Chapter Award as a Chair of the Atlanta Chapter of the AP/MTT Societies (2016), LexisNexis Dean's Excellence Award (2016), and Richard M. Bass/Eta Kappa Nu Outstanding Teacher Award (2016). She was an editor for IEEE Transactions on Wireless Communications 2012-2017 and an executive editor for Wiley Transactions on Emerging Telecommunications Technologies 2011-2016 .

Kyriakos G. Vamvoudakis was born in Athens, Greece. He received the Diploma (a 5 year degree, equivalent to a Master of Science) in Electronic and Computer Engineering from Technical University of Crete, Greece in 2006 with highest honors. After moving to the United States of America, he studied at The University of Texas at Arlington with Frank L. Lewis as his advisor and he received his M.S. and Ph.D. in Electrical Engineering in 2008 and 2011 respectively. From May 2011 to January 2012, he was working as an Adjunct Professor and Faculty Research Associate at the University of Texas at Arlington and at the Automation and Robotics Research Institute. During the period from 2012 to 2016 he was a project research scientist at the Center for Control, Dynamical Systems and Computation at the University of California, Santa Barbara. He was an assistant professor at the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech until 2018. He currently serves as an Assistant Professor at The School of Daniel Guggenheim School of Aerospace Engineering at Georgia Tech. His research interests include approxIMaTe dynamic programming, game theory, and optimal control. Recently, his research has focused on cyber-physical security, networked control, smart grid and multi-agent optimization. Dr. Vamvoudakis is the recipient of a 2019 ARO YIP award, a 2018 NSF CAREER award, and of several international awards including the 2016 International Neural Network Society Young Investigator (INNS) Award, the Best Paper Award for Autonomous/Unmanned Vehicles at the 27th Army Science Conference in 2010, the Best Presentation Award at the World Congress of Computational Intelligence in 2010, and the Best Researcher Award from the Automation and Robotics Research Institute in 2011. He is a member of Tau Beta Pi, Eta Kappa Nu and Golden Key honor societies and is listed in Who's Who in the World, Who's Who in Science and Engineering, and Who's Who in America. He has also served on various international program committees and has organized special sessions for several international conferences. He currently is a member of the Technical Committee on Intelligent Control of the IEEE Control Systems Society (TCIC), a member of the Technical Committee on Adaptive Dynamic Programming and Reinforcement Learning of the IEEE Computational Intelligence Society (ADPRLTC), an Associate Editor of the IEEE Computational Intelligence Magazine, an Associate Editor of the Journal of Optimization Theory and Applications, an Editor in Chief of the Communications in Control Science and Engineering, a registered Electrical/Computer engineer (PE) and a member of the Technical Chamber of Greece. He is a Senior Member of IEEE.

Dr. Rehg's research interests include computer vision, computer graphics, machine learning, robotics, and distributed computing. He co-directs the Computational Perception Laboratory (CPL) and is affiliated with the GVU Center, Aware Home Research Institute, and the Center for Experimental Research in Computer Science. In past years he has taught "Computer Vision" (CS 4495/7495) and "Introduction to Probabilistic Graphical Models" (CS 8803). He is currently teaching "Pattern Recognition" (CS 4803) and "Computer Graphics" (CS 4451). Dr. Rehg received the 2005 Raytheon Faculty Fellowship Award from the College of Computing. His paper with Ph.D. student Yushi Jing and collaborator Vladimir Pavlovic was the recipient of a Distinguished Student Paper Award at the 2005 International Conference on Machine Learning. Dr. Rehg currently serves on the Editorial Board of the International Journal of Computer Vision. He was the Short Courses Chair for the International Conference on Computer Vision (ICCV) in 2005 and the Workshops Chair for ICCV 2003. Dr. Rehg consults for several companies and has served as an expert witness. His research is funded by the NSF, DARPA, Intel Research, Microsoft Research, and the Mitsubishi Electric Research Laboratories.

Note: Rehg recently moved to the University of Illinois Urbana-Champaign as the Founder Professor of Computer Science and Industrial and Enterprise Systems Engineering.

I am currently Professor and KUKA Chair for Robotics in the School of Interactive Computing, and the Executive Director of the Institute for Robotics and Intelligent machines at the Georgia Institute of Technology. I am also Emeritus Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign.

David Hu is a fluid dynamicist with expertise in the mechanics of interfaces between fluids such as air and water. He is a leading researcher in the biomechanics of animal locomotion. The study of flying, swimming and running dates back hundreds of years, and has since been shown to be an enduring and rich subject, linking areas as diverse as mechanical engineering, mathematics and neuroscience. Hu's work in this area has the potential to impact robotics research. Before robots can interact with humans, aid in minimally-invasive surgery, perform interplanetary exploration or lead search-and-rescue operations, we will need a fundamental physical understanding of how related tasks are accomplished in their biological counterparts. Hu's work in these areas has generated broad interest across the fields of engineering, biology and robotics, resulting in over 30 publications, including a number in high-impact interdisciplinary journals such as Nature, Nature Materials, Proceedings of the National Academy of Sciences as well as popular journals such as Physics Today and American Scientist. Hu is on editorial board member for Nature Scientific Reports, The Journal of Experimental Biology, and NYU Abu Dhabi's Center for Center for Creative Design of Materials. He has won the NSF CAREER award, Lockheed Inspirational Young Faculty award, and best paper awards from SAIC, Sigma Xi, ASME, as well as awards for science education such as the Pineapple Science Prize and the Ig Nobel Prize. Over the years, Hu's research has also played a role in educating the public in science and engineering. He has been an invited guest on numerous television and radio shows to discuss his research, including Good Morning America, National Public Radio, The Weather Channel, and Discovery Channel. His ant research was featured on the cover of the Washington Post in 2011. His work has also been featured in The Economist, The New York Times, National Geographic, Popular Science and Discover His laboratory appeared on 3D TV as part of a nature documentary by 3DigitalVision, "Fire ants: the invincible army," available on Netflix.

My research integrates my work in complex fluids and granular media and the biomechanics of locomotion of organisms and robots to address problems in nonequilibrium systems that involve interaction of matter with complex media. For example, how do organisms like lizards, crabs, and cockroaches cope with locomotion on complex terrestrial substrates (e.g. sand, bark, leaves, and grass). I seek to discover how biological locomotion on challenging terrain results from the nonlinear, many degree of freedom interaction of the musculoskeletal and nervous systems of organisms with materials with complex physical behavior. The study of novel biological and physical interactions with complex media can lead to the discovery of principles that govern the physics of the media. My approach is to integrate laboratory and field studies of organism biomechanics with systematic laboratory studies of physics of the substrates, as well as to create mathematical and physical (robot) models of both organism and substrate. Discovery of the principles of locomotion on such materials will enhance robot agility on such substrates

Erturk began at Georgia Tech in May 2011 as an Assistant Professor, he was promoted to Associate Professor with tenure in 2016 and became a full Professor in 2019. Prior to joining Georgia Tech, he worked as a Research Scientist in the Center for Intelligent Material Systems and Structures at Virginia Tech (2009-2011). His postdoctoral research interests included theory and experiments of smart structures for applications ranging from aeroelastic energy harvesting to bio-inspired actuation. His Ph.D. dissertation (2009) was centered on experimentally validated electromechanical modeling of piezoelectric energy harvesters using analytical and approxIMaTe analytical techniques. Prior to his Ph.D. studies in Engineering Mechanics at Virginia Tech, Erturk completed his M.S. degree (2006) in Mechanical Engineering at METU with a thesis on analytical and semi-analytical modeling of spindle-tool dynamics in machining centers for predicting chatter stability and identifying interface dynamics between the assembly components.

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.