Thad Starner is a Professor at the Georgia Institute of Technology's School of Interactive Computing. Thad was perhaps the first to integrate a wearable computer into his everyday life as an intelligent personal assistant. Starner's work as a Ph.D. student would help found the field of Wearable Computing. His group's prototypes and patents on mobile MP3 players, mobile instant messaging and e-mail, gesture-based interfaces, and mobile context-based search foreshadowed now commonplace devices and services. Thad has authored over 100 scientific publications with over 100 co-authors on mobile Human Computer Interaction (HCI), pattern discovery, human power generation for mobile devices, and gesture recognition, and he is a founder and current co-chair of the IEEE Technical Committee on Wearable Information Systems. His work is discussed in public forums such as CNN, NPR, the BBC, CBS's 60 Minutes, The New York Times, Nikkei Science, The London Independent, The Bangkok Post, and The Wall Street Journal.

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.

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.

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.

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.

Aaron Young is an Associate Professor in Mechanical Engineering and is interested in designing and improving powered orthotic and prosthetic control systems for persons with stroke, neurological injury or amputation. His previous experience includes a post-doctoral fellowship at the University of Michigan in the Human Neuromechanics Lab working with exoskeletons and powered orthoses to augment human performance. He has also worked on the control of upper and lower limb prostheses at the Center for Bionic Medicine (CBM) at the Rehabilitation Institute of Chicago. His master's work at CBM focused on the use of pattern recognition systems using myoelectric (EMG) signals to control upper limb prostheses. His dissertation work at CBM focused on sensory fusion of mechanical and EMG signals to enable an intent recognition system for powered lower limb prostheses for use by persons with a transfemoral amputation.

W. Hong Yeo is a TEDx alumnus and biomechanical engineer. Since 2017, Yeo is an assistant professor of the George W. Woodruff School of Mechanical Engineering and Program Faculty in Bioengineering at the Georgia Institute of Technology. Before joining Georgia Tech, he has worked at Virginia Commonwealth University Medicine and Engineering as an assistant professor from 2014-2016. Yeo received his BS in mechanical engineering from INHA University, South Korea in 2003 and he received his Ph.D. in mechanical engineering and genome sciences at the University of Washington, Seattle in 2011. From 2011-2013, he worked as a postdoctoral research fellow at the Beckman Institute and Frederick Seitz Materials Research Laboratory at the University of Illinois at Urbana-Champaign. His research focuses on the fundamental and applied aspects of nanomechanics, biomolecular interactions, soft materials, and nano-microfabrication for nanoparticle biosensing and unusual electronic system development, with an emphasis on bio-interfaced translational nanoengineering. is an Editorial Board Member of Scientific Reports (Nature Publishing Group) and Scientific Pages of Bioengineering, and Review Editor of Frontiers of Materials (Frontiers Publishing Group). He serves as a technical committee member for IEEE Electronic Components and Technology Conference and Korea Technology Advisory Group at Korea Institute for Advancement of Technology. He has published more than 40 peer-reviewed journal articles, and has three issued and more than five pending patents. His research has been funded by MEDARVA Foundation, Thomas F. and Kate Miller Jeffress Memorial Trust, CooperVision, Inc., Korea Institute of Materials Science, Commonwealth Research Commercialization, and State Council of Virginia. Yeo is a recipient of a number of awards, including BMES Innovation and Career Development Award, Virginia Commercialization Award, Blavatnik Award Nominee, NSF Summer Institute Fellowship, Notable Korean Scientist Awards, and Best Paper/Poster Awards at ASME conferences.

I am an engineer and neuroscientist focused on how the brain and body cooperate to allow us to move. Fundamental abilities like standing and walking appear effortless until we–or someone we love–loses that ability. Movement is impacted in a wide range of diseases because it involves almost all parts of the brain and body, and their interactions with the environment. How we move is also highly individualized, changing across our lifetimes as a function of our experiences, and adapting in different situations. As such, assessing and treating movement impairments remains highly challenging. My approach is to dissect the complexities of how we move in health and disease by bridging what may seem to be disparate fields across engineering, neuroscience, and physiology. Our current application areas are Parkinson’s disease, stroke, aging and cerebral palsy, and we are interested in extending our work toward mild cognitive impairment and concussion.

My lab uses robotics, computation, and artificial intelligence to identify new physiological principles of sensing and moving that are enabling researchers to personalize rehabilitation and medicine. Primarily, we study people in the lab, studying brain and muscle activity in relationship to the body’s biomechanics in standing and walking. We use and develop robotic devices for assessing and assisting human movement, while interpreting brain and muscle activity to personalize the interactions. Our novel computer simulations of muscle, neurons, and joints establish a virtual platform for predicting how movements change in disease and improve with interventions. Recently, we have demonstrated the critical role of cognitive function motor impairment that may increase fall risk, suggesting that how we move and how we think may be closely related. Current projects include developing physiologically-inspired controllers to enable exoskeletons to enhance user balance, identifing individual differences that predict response to gait rehabilitation in stroke survivors, and developing more precise and physiologically-based methods to interpret clinical motor test outcomes.

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.