Welcome to University of Michigan alum Alex Gorodetsky (B.S.E. AE ‘10), who has returned to the Aerospace Department as Assistant Professor.
Professor Gorodetsky’s research interests include using applied mathematics and computational science to enable autonomous decision making under uncertainty. He recalls discovering an initial interest in his current research area: “While doing undergraduate research at UM into simulated combustion, I learned how important and cool computation can be; one could interact and study a world of your own creation just by using a laptop.” Developing computational algorithms appealed to Gorodetsky because they allow “someone with very little resources [to] simulate and learn about physical systems without using expensive or complex experimental systems. At the same time, computational simulations are often more realistic than pure theory allows.”
This initial research experience with computational science inspired Dr. Gorodetsky to continue his studies at the Massachusetts Institute of Technology (MIT), where he earned his Ph.D. in Aeronautics and Astronautics with a focus in algorithms for stochastic optimal control and estimation in dynamical systems. Professor Gorodetsky recalls how he found his interest in autonomous decision-making under uncertainty at MIT:
“In graduate school at MIT I continued learning about how to use computational simulations to predict and analyze complex systems. I began by performing research in uncertainty quantification, which deals with quantifying how uncertain inputs in a simulation model affect its output. Eventually, I wanted to make decisions based on such quantified uncertainty. Autonomous systems are a perfect application for decision making under uncertainty and I have pursued these topics ever since.”
At the University of Michigan, Professor Gorodetsky looks forward to continuing to develop computational algorithms for enabling autonomous systems. His personal research goals are “to eventually be able to specify some high-level goals for a system and have it automatically discover how to achieve them,” so that the system can “combine known knowledge, for example the physical laws surrounding the flow of fluids, with data that is obtained through interacting and sensing its environment.” Looking to the future, his hope is that “rather than building systems and telling them how to act to achieve their goals, my algorithms can be used to enable them to learn and act for themselves.”
On returning to Ann Arbor, Dr. Gorodetsky remarks: “It is a bit surreal to be back at UM but in a good way! I am excited about the opportunity to contribute to the same community that helped forge both my personal life and professional career. I think that I have a valuable perspective into student life and the undergrad experience of being an Aero major at U-M. I hope to use this perspective to mentor students and help them achieve their goals.”
Michigan Aerospace Engineering