Dr. Gunter is an Assistant Professor in Aerospace Engineering at the Georgia Institute of Technology. He received his B.S. in mechanical engineering from Rice University, and later his M.S. and Ph.D. in aerospace engineering from the University of Texas at Austin, specializing in orbital mechanics. Prior to joining Georgia Tech, Dr. Gunter was on the faculty of the Delft University of Technology (TU-Delft) in the Netherlands, as a member of the Physical and Space Geodesy section. His research activities involve various aspects of spacecraft missions and their applications, such as investigations into current and future laser altimetry missions, monitoring changes in the polar ice sheets using satellite data, applications of satellite constellations/formations, and topics surrounding kinematic orbit determination. He has been responsible for both undergraduate and graduate courses on topics such as satellite orbit determination, Earth and planetary observation, scientific applications of GPS, and space systems design. He is currently a member of the AIAA Astrodynamics Technical Committee, and also serves as the Geodesy chair for the Fall AGU Meeting Program Committee. He has received a NASA group achievement award for his work on the GRACE mission, and he is also a former recipient of a NASA Earth System Science Graduate Fellowship. He is a member of the American Institute of Aeronautics and Astronautics (AIAA), the American Geophysical Union (AGU), and the International Association of Geodesy (IAG).

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).

Yongxin Chen was born in Ganzhou, Jiangxi, China. He received his BSc in Mechanical Engineering from Shanghai Jiao Tong university, China, in 2011, and a Ph.D. degree in Mechanical Engineering, under the supervision of Tryphon Georgiou, from University of Minnesota in 2016. He is currently an Assistant Professor in the School of Aerospace Engineering at Georgia Institute of Technology. Before joining Georgia Tech, he had a one-year Research Fellowship in the Department of Medical Physics at Memorial Sloan Kettering Cancer Center with Allen Tannenbaum from 2016.8 to 2017.8 and was an Assistant Professor in the Department of Electrical and Computer Engineering at Iowa State University from 2017.8 to 2018.8. He received the George S. Axelby Best Paper Award (IEEE Transaction on Automatic Control) in 2017 for his joint work "Optimal steering of a linear stochastic system to a final probability distribution, Part I" with Tryphon Georgiou and Michele Pavon.

Professor Yezzi was born in Gainsville, Florida and grew up in Minneapolis, Minnesota. He obtained both his Bachelor's degree and his Ph.D. in the Department of Electrical Engineering at the University of Minnesota with minors in mathematics and music. After completing his Ph.D., he continued his research as a post-Doctoral Research Associate at the Laboratory for Information and Decision Systems at Massachusetts Institute of Technology in Boston, MA. His research interests fall broadly within the fields of image processing and computer vision. In particular he is interested in curve and surface evolution theory and partial differential equation techniques as they apply to topics within these fields (such as segmentation, image smoothing and enhancement, optical flow, stereo disparity, shape from shading, object recognition, and visual tracking). Much of Dr. Yezzi's work is particularly tailored to problems in medical imaging, including cardiac ultrasound, MRI, and CT. He joined the Georgia Tech faculty in the fall of 1999 where he has taught courses in DSP and is working to develop advanced courses in computer vision and medical image processing. Professor Yezzi consults with industry in the areas of visual inspection and medical imaging. His hobbies include classical guitar, opera, and martial arts.

Erik I. Verriest received the degree of 'Burgerlijk Electrotechnisch Ingenieur' from the State University of Ghent, Ghent, Belgium in 1973, and the M.Sc. and Ph.D. degrees from Stanford University in 1975 and 1980, respectively. He was employed by the Control Systems Laboratory and the Hybrid Computation Centre, Ghent, Belgium, where he worked on process simulation and control in 1973-74. His doctoral research at Stanford was on the algebraic theory and balancing for time varying linear systems and array algorithms. He joined the faculty of Electrical and Computer Engineering at Georgia Tech in 1980. He spent the 1991-92, 1993-94 and 1994-95 academic years at Georgia Tech Lorraine. He has contributed to the application of the theory of systems over finite fields in cryptography, data compression, sensitivity analysis of array algorithms with applications in estimation and control, algorithms for optical computing. More recently he contributed to the theory of periodic and hybrid systems, delay - differential systems, model reduction for nonlinear systems, and control with communication constraints. He served on several IPC's and is a member of the IFAC Committee on Linear Systems.

Patricio Vela was born in Mexico City, Mexico and grew up in California. He earned his bachelor of science degree in 1998 and his doctorate in 2003 at the California Institute of Technology, where he did his graduate research on geometric nonlinear control androbotics. Dr. Vela came to Georgia Tech as a post-doctoral researcher in computer vision and joined the ECE faculty in 2005. His research interests lie in the geometric perspectives to control theory and computer vision. Recently, he has been interested in the role that computer vision can play for achieving control-theoretic objectives of (semi-)autonomous systems. His research also covers control of nonlinear systems, typically robotic systems.

Sam Coogan received the B.S. degree in Electrical Engineering from Georgia Tech and the M.S. and Ph.D. degrees in Electrical Engineering from the University of California, Berkeley. In 2015, he was a postdoctoral research engineer at Sensys Networks, Inc., and in 2012 he spent time at NASA's Jet Propulsion Lab. Before joining Georgia Tech in 2017, he was an assistant professor in the Electrical Engineering department at UCLA from 2015–2017. His awards and recognitions include the 2020 Donald P Eckman Award from the American Automatic Control Council recognizing "an outstanding young engineer in the field of automatic control", a Young Investigator Award from the Air Force Office of Scientific Research in 2019, a CAREER Award from the National Science Foundation in 2018, and the Outstanding paper award for the IEEE Transactions on Control of Network Systems in 2017.

Dr. Tsiotras holds the David & Andrew Lewis Endowed Chair in the School of Daniel Guggenheim School of Aerospace Engineering at Georgia Tech. He is also associate director at the Institute for Robotics and Intelligent Machines. His current research interests include nonlinear and optimal control and their connections with AI, planning, and decision-making, emphasizing autonomous ground, aerial, and space vehicles applications. He has published more than 350 journal and conference articles in these areas. Prior to joining the faculty at Georgia Tech, Dr. Tsiotras was an assistant professor of mechanical and aerospace engineering at the University of Virginia. He has also held visiting appointments with the MIT, JPL, INRIA, Rocquencourt, the Laboratoire de Automatique de Grenoble, and the Ecole des Mines de Paris (Mines ParisTech). Dr. Tsiotras is a recipient of the NSF CAREER award, the IEEE Technical Excellence Award in Aerospace Controls, the Outstanding Aerospace Engineer Award from Purdue, the Sigma Xi President and Visitor's Award for Excellence in Research, as well as numerous other fellowships and scholarships. He is currently the chief editor of the Frontiers in Robotics & AI, in the area of space robotics, and an associate editor for the Dynamic Games and Applications journal. In the past, he has served as an associate editor for the IEEE Transactions on Automatic Control, the AIAA Journal of Guidance, Control, and Dynamics, the IEEE Control Systems Magazine, and the Journal of Dynamical and Control Systems. He is a Fellow of the AIAA, IEEE, and AAS.

Evangelos Theodorou earned his Diploma in Electronic and Computer Engineering from the Technical University of Crete (TUC), Greece in 2001. He has also received a MSc in Production Engineering from TUC in 2003, a MSc in Computer Science and Engineering from University of Minnesota in spring of 2007 and a MSc in Electrical Engineering on dynamics and controls from the University of Southern California(USC) in Spring 2010. In May of 2011 he graduated with his Ph.D., in Computer Science at USC. After his Ph.D., he became a Postdoctoral Research Associate with the department of Computer Science and Engineering, University of Washington, Seattle. In July 2013 he joined the faculty of the school of Aerospace Engineering at Georgia Institute of Technology as Assistant Professor. His theoretical research spans the areas of control theory, machine learning, information theory and statistical physics. Applications involve autonomous planning and control in robotics and aerospace systems, bio-inspired control and design.

Spyros Reveliotis is a professor in the Stewart School of Industrial & Systems Engineering at Georgia Tech. Dr. Reveliotis' research interests are primarily in discrete event systems theory and its applications, especially in the control of flexibly automated workflows and the traffic management of multi-agent systems evolving over graphs. He also has an active interest in machine learning theory and its applications. Dr. Reveliotis is an IEEE Fellow, and a member of INFORMS. Dr. Reveliotis completed his Ph.D. studies in industrial engineering at the University of Illinois at Urbana-Champaign. He also holds a B.Sc. degree in Electrical Engineering from the National Technical University of Athens, Greece, and an M.Sc. degree in Computer Systems Engineering from Northeastern University.