Dr. Mazumdar started at the Woodruff School of Mechanical Engineering at Georgia Tech in January of 2019 and currently has a courtesy appointment with the Guggenheim School of Aerospace Engineering. She graduated with her Ph.D. from Massachusetts Institute of Technology and completed a postdoctoral appointment at Sandia National Laboratories in the Diagnostic Science and Engineering group. Her research interests include the design of new diagnostic techniques and sensor systems for studying combustion, multiphase flows, hypersonic flows, and energetic materials. Her group utilizes new composite sensing materials, optical diagnostics, magnetostatics, and system identification methods to study these complex physical phenomena.

Marilyn Smith is a Professor in the School of Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology. She is director of Georgia Tech's Vertical Lift Research Center of Excellence (VLRCOE), where she leads a seven-university team of experts in vertical lift research for the U.S. Army, U.S. Navy and NASA. She has partnered with the Georgia Tech Research Institute (GTRI) to successfully win multiple research funding mechanisms for both organizations that total more than $200 million dollars. As the director of the AE School's Computational Nonlinear Computational Aeroelasticity Lab, Prof. Smith leads an internationally recognized and award-winning research team in the areas of unsteady aerodynamics and computational aeroelasticity using Computational Fluid Dynamics (CFD) across rotary-wing, fixed wing and launch vehicles, as well as sustainable energy. As a member of the NASA FUN3D development team, Prof. Smith contributes to state-of-the-art unstructured algorithm development, in particular for overset, moving frames. As an affiliate of the Aerospace Systems Design Lab (ASDL), she helps to integrate high performance computing with the design process. Prof. Smith is the author or co-author of more than 200 technical publications, and her research products are in active use by the US Government and other organizations, including the Drone Racing League. She is active internationally on three NATO AVT Panels investigating nonlinear gusts behaviors on UAVs and collaboration of experimental/computational aerodynamics. She is on Board of Directors of the Vertical Lift Consortium (VLC) and the Vertical Flight Society (VFS). She is also the Deputy Technical Director for Aeromechanics for the VFS. Prof. Smith has demonstrated her leadership as ARO Dynamic Stall Workshop Chair (2019); 70th AHS Annual Forum Technical Chairperson (2014); 69th AHS Annual Forum Technical Deputy Chairperson (2013); and 2014 Overset Grid Symposium (OGS) Chairperson. She was a member on the first International Aeroelastic Prediction Workshop Organizing Committee and is a member of the OGS organizing committee. Prof. Smith has been a guest expert in aviation for National Geographic, PBS, and NPR, as well as local television and numerous publications.

I am an Assistant Professor at the School of Interactive Computing in the College of Computing. I am also affiliated with the Georgia Tech Research Institute and serve as an Associate Director of ML@GT which is the machine learning center recently created at Georgia Tech. Previously I was a Research Scientist at SRI International Sarnoff in Princeton, and before that received my Ph.D. in 2010 with Professor Ron Arkin as my advisor. I lead the RobotIcs Perception and Learning (RIPL) lab. My areas of research specifically focus on the intersection of learning methods for sensor processing and robotics, developing novel machine learning algorithms and formulations towards solving some of the more difficult perception problems in these areas. I am especially interested in moving beyond supervised learning (un/semi/self-supervised and continual/lifelong learning) as well as distributed perception (multi-modal fusion, learning to incorporate information across a group of robots, etc.).

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.

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.

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.