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.

Sarah Li will join the Daniel Guggenheim School of Aerospace Engineering in January 2025. Her research advances multi-agent models and algorithms to overcome challenges facing future air and space mobility systems. Her research lies at the intersection of game theory, stochastic control, and optimization to enable optimal and safe decision-making of autonomous systems in interactive settings. Sarah earned her Ph.D. in Aeronautics and Astronautics from the University of Washington and her B.A.Sc. in Engineering Physics from the University of British Columbia. She is currently a postdoctoral scholar at ETH Zurich in Information Technology and Electrical Engineering. She was a 2020 Zonta International Amelia Earhart Fellow and a 2022 University of Washington Condit Graduate Fellow. During her Ph.D., she interned with Microsoft Research to develop supply chain games and Loon to develop multi-disciplinary design optimization for stratospheric balloons.

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

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

Young-Hui Chang is a professor in the School of Biological Sciences, Associate Dean of Faculty for College of Sciences, and director of research in the Georgia Tech Comparative Neuromechanics Lab where he studies the neuromechanics of movement in humans and other animals. Chang’s aim is to understand fundamental principles by which we control our movements as we move through our physical environment. This requires knowledge of the neural control of movement, the biomechanics of our musculoskeletal system, and the physics of our environmental interactions. The team also studies how our body adapts to acute and chronic changes. This involves processes of motor learning that are involved in everything from clinical rehabilitation to elite sports performance.

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.

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.