Mark Riedl is an Associate Professor in the Georgia Tech School of Interactive Computing and director of the Entertainment Intelligence Lab. Mark's research focuses on the intersection of artificial intelligence, virtual worlds, and storytelling. The principle research question Mark addresses through his research is: how can intelligent computational systems reason about and autonomously create engaging experiences for users of virtual worlds and computer games.

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.

Devi Parikh is an Assistant Professor in the School of Interactive Computing at Georgia Tech, and a Research Scientist at Facebook AI Research (FAIR). From 2013 to 2016, she was an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. From 2009 to 2012, she was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC), an academic computer science institute affiliated with University of Chicago.

Pinar Keskinocak is the William W. George Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. She is also co-founder and director of the Center for Health and Humanitarian Systems. Previously, she served as the College of Engineering ADVANCE Professor and as interim associate dean for faculty development and scholarship. Prior to joining Georgia Tech, she worked at IBM T.J. Watson Research Center. She received her Ph.D. in Operations Research from Carnegie Mellon University, and her M.S. and B.S.

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.

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.

Rebecca "Beki" Grinter is a Professor of Interactive Computing in the College of Computing & (by courtesy) the Scheller College of Business at the Georgia Institute of Technology. Her research focuses on improving the experience of computing by understanding the human experience in the building and using of technologies. Her work contributes to the fields of human-computer interaction, ubiquitous computing, and computer supported cooperative work. She has also worked in the areas of robotics, networking, security, and software engineering.

Dr. Matthew Gombolay is the Anne and Alan Taetle Assistant Professor of Interactive Computing at the Georgia Institute of Technology. He received a B.S. in Mechanical Engineering from the Johns Hopkins University in 2011, a S.M. in Aeronautics and Astronautics from MIT in 2013, and a Ph.D. in Autonomous Systems from MIT in 2017. Gombolay's research interests span robotics, AI/ML, human-robot interaction, and operations research.

Carl DiSalvo is an Associate Professor in the Digital Media Program in the School of Literature, Media, and Communication at the Georgia Institute of Technology. At Georgia Tech he directs the Public Design Workshop: a design research studio that explores socially engaged design and civic media. 

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.