Karen M. Feigh is a Professor at Georgia Tech's Daniel Guggenheim School of Aerospace Engineering with a courtesy appointment in the School of Interactive Computing. As the director of the Georgia Tech Cognitive Engineering Center, she leads a research and education program focused on the computational cognitive modeling and design of cognitive work support systems and technologies to improve the performance of socio-technical systems. She is responsible for undergraduate and graduate level instruction in the areas of flight dynamics, human reliability analysis methods, human factors, human-automation interaction and cognitive engineering. Feigh has over 14 years of relevant research and design experience in fast-time air traffic simulation, ethnographic studies, airline operation control centers, synthetic vision systems for helicopters, expert systems for air traffic control towers, human extra-vehicular activities in space, and the impact of context on undersea warfighters. Recently her work has focused on human-autonomy teaming and the human experience of machine learning across a number of domains.

Feigh has served as both Co-PI and PI on a number of FAA, NIA, ONR, NSF and NASA sponsored projects. As part of her research, Feigh has published 35 scholarly papers in the field of Cognitive Engineering with primary emphasis on the aviation industry. She serves as an Associate Editor for the Journal of Cognitive Engineering and Decision Making. She previously served as the Chair to the Human Factor and Ergonomics Society’s Cognitive Engineering and Decision Making Technical Group, and on the National Research Council’s Aeronautics and Space Engineering Board (ASEB).

Dr. Yong Cho, MSCE '97, has returned to CEE as an associate professor. Cho comes to Georgia Tech most recently from the University of Nebraska-Lincoln, and the University of Wisconsin-Platteville, where he taught construction engineering, construction management, and architectural engineering after earning his doctorate at the University of Texas in 2000. A 2011 recipient of the NSF Early Career Award, his research interests include construction automation, robotics, and transportation. He is leading the development of a new paradigm in these research areas by challenging the current understanding of science/engineering technologies in construction and sustainable built environments. Among the challenges he is investigating are robotizing several critical construction and maintenance tasks and disaster relief efforts.

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.

Stephen Balakirsky is the Chief Scientist for the Aerospace, Transportation & Advanced Systems Laboratory at the Georgia Tech Research Institute (GTRI), and the Director of Technical Initiatives at the Petit Institute for Bioengineering and Bioscience (IBB) at Georgia Tech.

Balakirsky’s research interests include robotic architectures, planning, bio-automation, robotic standards, and autonomous systems testing. His work in knowledge driven robotics couples real-time sensors and knowledge repositories to allow for flexibility and agility in robotic systems ranging from assembly and manufacturing systems to surveillance and logistics systems. The framework promotes software reuse and the ability to detect and correct for execution errors.

Previously, Balakirsky worked as a project manager at the National Institute of Standards and Technology (NIST) and was a senior research engineer at the Army Research Laboratory (ARL). At ARL, Balakirsky performed mobile robotics research in several areas, including command and control, mapping, human-computer interfaces, target tracking, vision processing and tele-operated control.