Nancey Green Leigh is a Professor in the School of City and Regional Planning and adviser for the economic development planning, working with masters and doctoral students. Maintaining an active research program, Leigh is currently leading a project entitled "Workers, Firms and Industries in Robotic Regions," funded by the National Science Foundation's Robotics Initiative. She previously led a large scale research effort by three universities focused on sustainable industrial systems for urban regions. Both of these efforts as well as other funded research (brownfields, urban land and manufacturing, resilient infrastructure) contribute to Leigh's long term focus on advancing sustainable development for local and regional economies. As Associate Dean for Research, Leigh is focused on strengthening the research impact of the College of Design. She develops and administers competitive initiatives to support individual and collaborative research by college faculty and affiliated researchers. She oversees the college's seven major research units. She also is engaged in building research connections within Georgia Tech between the College of Design, other colleges and Interdisciplinary Research Institutes, as well as to external funders and collaborators in the public, private and nonprofit sectors. Leigh has published more than 60 articles and four books, Routledge Handbook of International Planning Education (2019 with S.P. French, S. Guhathakurta, and B. Stiftel), Planning Local Economic Development, 6th edition (2017 with E.J. Blakely) adopted for courses in a wide array of universities; Economic Revitalization: Cases and Strategies for City and Suburb (2002 with J. Fitzgerald); and Stemming Middle Class Decline: The Challenge to Economic Development Planning (1994). She was co-editor of the Journal of Planning Education and Research from 2012 to 2016, and was elected a Fellow of the American Institute of Certified Planners in 2008.

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

Animesh Garg is a Stephen Fleming Early Career Assistant Professor at School of Interactive Computing at Georgia Tech. He leads the People, AI, and Robotics (PAIR) research group. He is on the core faculty in the Robotics and Machine Learning programs. Animesh is also a Senior Researcher at Nvidia Research. Animesh earned a Ph.D. from UC Berkeley and was a postdoc at the Stanford AI Lab. He is on leave from the department of Computer Science at University of Toronto and CIFAR Chair position at the Vector Institute.

Garg earned his M.S. in Computer Science and Ph.D. in Operations Research from UC, Berkeley. He worked with Ken Goldberg at Berkeley AI Research (BAIR). He also worked closely with Pieter Abbeel, Alper Atamturk & UCSF Radiation Oncology. Animesh was later a postdoc at Stanford AI Lab with Fei-Fei Li and Silvio Savarese.

Garg's research vision is to build the Algorithmic Foundations for Generalizable Autonomy, that enables robots to acquire skills, at both cognitive & dexterous levels, and to seamlessly interact & collaborate with humans in novel environments. His group focuses on understanding structured inductive biases and causality on a quest for general-purpose embodied intelligence that learns from imprecise information and achieves flexibility & efficiency of human reasoning.

Lu Gan joined the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology as an Assistant Professor in January 2024. She leads the Lu's Navigation and Autonomous Robotics (Lunar) Lab at Georgia Tech, and is on the core faculty of the Institute for Robotics and Intelligent Machines. Her research interests include robot perception, robot learning, and autonomous navigation. Her group explores the use of computer vision, machine learning, estimation, probabilistic inference, kinematics and dynamics to develop autonomous systems in ground, air, and space applications.

She holds a B.S. in Automation from the University of Electronic Science and Technology of China, an M.S. in Control Engineering from Beihang University, and received her M.S. and Ph.D. in Robotics from the University of Michigan, Ann Arbor. Before joining Georgia Tech, she had a two-year appointment as a Postdoctoral Scholar at the Graduate Aerospace Laboratories of the California Institute of Technology and the Center for Autonomous Systems and Technologies at Caltech.

Eric Feron is a professor of Electrical, Computer, and Mechanical Engineering. He is the director of the Robotics, Intelligent Systems, and Control (RISC) Laboratory. He recently joined the KAUST CEMSE Division from the Georgia Institute of Technology. Prior to his time at Georgia Tech, he was an active faculty member in MIT's Aeronautics and Astronautics department from 1993 until 2005. Feron’s career in academia began in Paris, France, where he obtained his B.S. and M.S. from École Polytechnique and École Normale Superieure, respectively. He later completed his Ph.D. in aerospace engineering at Stanford University, U.S. 

Feron's research interests center around the use of elementary concepts of control systems, optimization and computer science to address key issues in modern robotic systems. More specifically, aerobatic control of uncrewed aerial vehicles, multi-agent operations, including air traffic control systems and safety-critical software system certification. Feron is also interested in geometric control systems and control theory in general. Among his latest projects, there are a fractal drone, a few positioning systems, a wheel nature could have invented, and a self-reproducing 3D printer. 

Feron has always taught at least one course per semester since the onset of his academic career. Feron believes teaching offers a fantastic outlet to communicate display his past research and inspire his new research projects with the thoughts of his classroom students. He has taught subjects as diverse as cyber-physical systems, control systems, operations research, linear programming, software engineering, and flight mechanics. Feron is a strong proponent and author of quality online education products. He also believes in communicating knowledge through all available mechanisms, including analytical and experimental, acknowledging the multiple learning modalities preferred by students, undergraduate and graduate.

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).

Irfan Essa is a Professor in the School of Interactive Computing and Senior Associate Dean in the College of Computing (CoC), at the Georgia Institute of Technology. Professor Essa works in the areas of Computer Vision, Artificial Intelligence, Machine Learning, Robotics, Computer Graphics, and Social Computing, with potential impact on Content Creation, Analysis and Production (e.g., Computational Photography & Video, Image-based Modeling and Rendering, etc.) Human Computer Interaction, Artificial Intelligence, Computational Behavioral/Social Sciences, and Computational Journalism research.He has published over 150 scholarly articles in leading journals and conference venues on these topics and several of his papers have also won best paper awards. He has been awarded the National Science Foundation CAREER Award and was elected an IEEE Fellow. He has held extended research consulting positions with Disney Research and Google Research and also was an Adjunct Faculty Member at Carnegie Mellon's Robotics Institute. He joined Georgia Tech in 1996 after his earning his Master's (1990), Ph.D. (1994), and holding a research faculty position at the Massachusetts Institute of Technology Media Lab (1988-1996).

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.

Jaydev P. Desai, Ph.D, is currently a Professor and BME Distinguished Faculty Fellow in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech. Prior to joining Georgia Tech in August 2016, he was a Professor in the Department of Mechanical Engineering at the University of Maryland, College Park (UMCP). He completed his undergraduate studies from the Indian Institute of Technology, Bombay, India, in 1993. He received his M.A. in Mathematics in 1997, M.S. and Ph.D. in Mechanical Engineering and Applied Mechanics in 1995 and 1998 respectively, all from the University of Pennsylvania. He was also a Post-Doctoral Fellow in the Division of Engineering and Applied Sciences at Harvard University. He is a recipient of several NIH R01 grants, NSF CAREER award, and was also the lead inventor on the "Outstanding Invention of 2007 in Physical Science Category" at the University of Maryland, College Park. He is also the recipient of the Ralph R. Teetor Educational Award. In 2011, he was an invited speaker at the National Academy of Sciences "Distinctive Voices" seminar series on the topic of "Robot-Assisted Neurosurgery" at the Beckman Center. He was also invited to attend the National Academy of Engineering's 2011 U.S. Frontiers of Engineering Symposium. He has over 150 publications, is the founding Editor-in-Chief of the Journal of Medical Robotics Research, and Editor-in-Chief of the Encyclopedia of Medical Robotics (currently in preparation). His research interests are primarily in the area of image-guided surgical robotics, rehabilitation robotics, cancer diagnosis at the micro-scale, and rehabilitation robotics. He is a Fellow of the ASME and AIMBE.

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.