Michael E. Cao is currently a Postdoctoral Fellow in the Formal methods and Autonomous Control of Transportation Systems Laboratory at the Georgia Institute of Technology
His research involves the safe control and verification of systems with partially unknown dynamics. These unknown dynamics may originate both internally (i.e. model error) or externally (i.e. environmental disturbances), and are approximated via a combination of computationally efficient reachability tools such as mixed monotonicity which enable real-time evaluation, while robust function estimators such as Gaussian Processes provide high-probability confidence bounds on the unknown components.
Email: mcao34[at]gatech.edu
About
Michael received a B.S. in Computer Engineering with a Minor in Robotics in 2018, a M.S. in Electrical Engineering in 2020, and a Ph.D. in Robotics in 2025, which he completed under the supervision of Dr. Samuel Coogan, all from the Georgia Institute of Technology. He has also worked for Sandia National Laboratories, NASA’s Jet Propulsion Lab, and the Johns Hopkins University Applied Physics Lab.