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. Mark's primary research contributions are in the area of artificial intelligence approaches to automated story generation and interactive storytelling for entertainment, education, and training. Narrative is a cognitive tool used by humans for communication and sense-making. The goal of my narrative intelligence research is to discover new computational algorithms and models that can facilitate the development of intelligent computer systems that can reason about narrative in order to be better communicators, entertainers, and educators. Additionally, Mark has explored the following research topics: virtual cinematography in 3D virtual worlds; player modeling; procedural generation of computer game content; computational creativity; human creativity support; intelligent virtual characters; mixed-initiative problem solving; and discourse generation. Mark earned a Ph.D. degree in 2004 from North Carolina State University. From 2004-2007, Mark was a Research Scientist at the University of Southern California Institute for Creative Technologies where he researched and developed interactive, narrative-based training systems. Mark joined the Georgia Tech College of Computing in 2007 where he continues to study artificial intelligence approaches to story generation, interactive narratives, and adaptive computer games. His research is supported by the NSF, DARPA, the U.S. Army, Google, and Disney. Mark was the recipient of a DARPA Young Faculty Award and an NSF CAREER Award.

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.

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. She has held visiting positions at Cornell University, University of Texas at Austin, Microsoft Research, MIT, Carnegie Mellon University, and Facebook AI Research. She received her M.S. and Ph.D. degrees from the Electrical and Computer Engineering department at Carnegie Mellon University in 2007 and 2009 respectively. She received her B.S. in Electrical and Computer Engineering from Rowan University in 2005. Her research interests include computer vision and AI in general and visual recognition problems in particular. Her recent work involves exploring problems at the intersection of vision and language, and leveraging human-machine collaboration for building smarter machines. She has also worked on other topics such as ensemble of classifiers, data fusion, inference in probabilistic models, 3D reassembly, barcode segmentation, computational photography, interactive computer vision, contextual reasoning, hierarchical representations of images, and human-debugging.

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. She has published over 80 scholarly articles, served as Papers Chair (2006) & Best Papers Chair (2010) for the ACM Conference on Human Factors in Computing Systems (CHI), the premier conference for human-computer interaction. In 2013 she was elected to the CHI Academy. In 2010 she was recognized as a Distinguished Alumna of the University of California, Irvine. Before joining the faculty at Georgia Tech, she was a Member of Research Staff in the Computer Science Laboratory of Xerox PARC and a Member of Technical Staff in the Software Production Research Department of Bell Laboratories. She was also a visiting scholar at Rank Xerox EuroPARC. She holds a Ph.D. and M.S. in Information and Computer Science both from the University of California, Irvine, and a B.Sc. (Hons) in Computer Science from the University of Leeds. Affiliations GVU Center

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. Between defending his dissertation and joining the faculty at Georgia Tech, Gombolay served as a technical staff member at MIT's Lincoln Laboratory transitioning his research for the U.S. Navy, earning him an R&D 100 Award for his development of "Human-Machine Collaborative Optimization via Apprenticeship Scheduling" (COVAS). His publication record includes a best paper award from American Institute for Aeronautics and Astronautics, and he was selected as a DARPA Riser in 2018. Dr. Gombolay's research has been highlighted in media outlets such as CNN, PBS, NBC, CBS, Harvard Business Review, Gizmodo, and national public radio

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.

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.

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.