Glen Chou joined Georgia Tech as an assistant professor with a joint appointment in the School of Cybersecurity & Privacy and the School of Aerospace Engineering in November 2024. He directs the Trustworthy Robotics Lab, which designs principled algorithms that can enable general-purpose robots and autonomous systems to operate capably, safely, and securely, while remaining resilient to real-world failures and uncertainty. To achieve this, his research leverages control theory and machine learning, while connecting to optimization, computer vision, formal methods, planning, human-robot interaction, and statistics. Glen is interested in broad applications of autonomy, including robotic manipulation, vision-based navigation, aerospace, and large-scale cyber-physical systems more generally.

Glen is from Northern California. He holds dual B.S. degrees in EECS and ME from UC Berkeley, as well as an M.S. and Ph.D. in ECE from the University of Michigan. Prior to joining Georgia Tech, Glen was a postdoc at MIT CSAIL.

Tom Sammon focuses on implementing lean manufacturing practices and helping companies develop capital equipment applications.

Ratan is an Assistant Professor of Cognition and Brain Science in the School of Psychology at Georgia Tech, and the Director of the Murty Lab (murtylab.com). He obtained his PhD from Indian Institute of Science (IISc) Bangalore and was a postdoctoral researcher in the Kanwisher and DiCarlo labs at MIT before moving to Georgia Tech. Research in the Murty Lab aims to uncover the neural codes and algorithms that enable us to see. The central theme of the lab's work is to integrate biological vision with artificial models of vision. The lab combines the benefits of closed-loop experimental testing (using 3T/7T human functional-MRI) with cutting-edge computational methods (like deep neural networks, generative algorithms, and AI interpretability) toward a new computationally precise understanding of human vision. This research also guides the development of neurally mechanistic biologically constrained models aimed to uncover a better understanding of the neurobiological changes that underlie perceptual abnormalities such as agnosias.

Jun Ueda received his B.S., M.S., and Ph.D. degrees from Kyoto University, Japan, in 1994, 1996, and 2002 all in Mechanical Engineering. From 1996 to 2000, he was a Research Engineer at the Advanced Technology Research and Development Center, Mitsubishi Electric Corporation, Japan. He was an Assistant Professor of Nara Institute of Science and Technology, Japan, from 2002 to 2008. During 2005-2008, he was a visiting scholar and lecturer in the Department of Mechanical Engineering, Massachusetts Institute of Technology. He joined the G. W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technology as an Assistant Professor in 2008 where he is currently a Professor. He received Fanuc FA Robot Foundation Best Paper Award in 2005, IEEE Robotics and Automation Society Early Academic Career Award in 2009, Advanced Robotics Best Paper Award in 2015, and Nagamori Award in 2021. 

Anqi Wu is an Assistant Professor at the School of Computational Science and Engineering (CSE), Georgia Institute of Technology. She was a Postdoctoral Research Fellow at the Center for Theoretical Neuroscience, the Zuckerman Mind Brain Behavior Institute, Columbia University. She received her Ph.D. degree in Computational and Quantitative Neuroscience and a graduate certificate in Statistics and Machine Learning from Princeton University. Anqi was selected for the 2018 MIT Rising Star in EECS, 2022 DARPA Riser, and 2023 Alfred P. Sloan Fellow. Her research interest is to develop scientifically-motivated Bayesian statistical models to characterize structure in neural data and behavior data in the interdisciplinary field of machine learning and computational neuroscience. She has a general interest in building data-driven models to promote both animal and human studies in the system and cognitive neuroscience.

Dr. Gregory S. Sawicki is the Interim Executive Director of the Institute for Robotics and Intelligent Machines and Professor and Joseph Anderer Faculty Fellow at Georgia Tech with appointments in the George W. Woodruff School of Mechanical Engineering and the School of Biological Sciences. He holds a B.S. from Cornell University ('99) and a M.S. in Mechanical Engineering from University of California-Davis ('01). Dr. Sawicki completed his Ph.D. in Human Neuromechanics at the University of Michigan, Ann-Arbor ('07) and was an NIH-funded Post-Doctoral Fellow in Integrative Biology at Brown University ('07-'09). Dr. Sawicki was a faculty member in the Joint Department of Biomedical Engineering at NC State and UNC Chapel Hill from 2009-2017. In summer of 2017, he joined the faculty at Georgia Tech with appointments in Mechanical Engineering 3/4 and Biological Sciences 1/4.

Education

Masters of Science, Computer Science, Georgia Institute of Technology, 2022

Bachelors of Science, Mechanical Engineering, Georgia Institute of Technology, 2020

Research Expertise

Robot Planning and Control, Embodied Artificial Intelligence, Laboratory Automation, Software Engineering

Selected Publications

Bowles-Welch, A., Byrnes, W., Kanwar, B., Wang, B., Joffe, B., Casteleiro Costa, P., Armenta, M., Xu, J., Damen, N., Zhang, C., Mazumdar, A., Robles, F., Yeago, C., Roy, K., Balakirsky, S. (2021). Artificial Intelligence Enabled Biomanufacturing of Cell Therapies. Georgia Tech Research Institute Internal Research and Development (IRAD) Journal

Byrnes, W., Ahlin, K., Rains, G., & McMurray, G. (2019). Methodology for Stress Identification in Crop Fields Using 4D Height Data. IFAC-PapersOnLine, 52(30), 336–341. https://doi.org/10.1016/j.ifacol.2019.12.562

Byrnes, W., Kanwar, B., Damen, N., Wang, B., Bowles-Welch, A. C., Roy, K., & Balakirsky, S. (2023). Process Development and Manufacturing: A NEEDLE-BASED AUTOSAMPLER FOR BIOREACTOR CELL MEDIA COLLECTION. Cytotherapy, 25(6), S172.

Wang, B., Kanwar, B., Byrnes, W., Costa, P. C., Filan, C., Bowles-Welch, A. C., ... & Roy, K. (2023). Process Development and Manufacturing: DIGITAL TWIN-ENABLED FEEDBACK-CONTROLLED AUTOMATION WITH INTEGRATED PROCESS ANALYTICS FOR BIOMANUFACTURING OF CELL THERAPIES. Cytotherapy, 25(6), S206-S207.

Professional Activities

STEM@GTRI Program Mentor

IEEE Member

During his graduate work at UC, Berkeley, Simon sought to uncover general principles of animal locomotion that reveal control strategies underlying the remarkable stability and maneuverability of movement in nature. His work has demonstrated the importance animals’ natural dynamics for maintaining stability in the absence of neural feedback. His research emphasizes the importance of placing neural control in the appropriate dynamical context using mathematical and physical models. He has collaborated with researchers at four other institutions to transfer these principles to the design of the next generation of bio-inspired legged robots. 

Simon received his Ph.D. in Integrative Biology at UC, Berkeley and has been a Hertz Fellow since 2002. His work has led to fellowships and awards from the National Science Foundation, the University of California, the Woods Hole Marine Biological Institute, the American Physical Society, the Society of Integrative and Comparative Biology, and the International Association of Physics Students. He is also currently affiliated the new Center for Interdisciplinary Bio-Inspiration in Education and Research (CIBER) at Berkeley.

Yue Chen is an assistant professor in the Department of Biomedical Engineering, GT/Emory. He received his Ph.D. degree in Mechanical Engineering from Vanderbilt University, M.S. in Mechanical Engineering from Hong Kong Polytechnic University, and a B.S. in Vehicle Engineering from Hunan University. His research focused on designing, modeling, and control of continuum robots and apply them in medicine.