Location
3053 François-Xavier Bagnoud Aerospace Building
1320 Beal Avenue Ann Arbor, MI 48109-2140
Phone
Primary Website
Biography
Alex Gorodetsky is an Associate Professor of Aerospace Engineering at the University of Michigan. His research interests include using applied mathematics and computational science to enhance autonomous decision making under uncertainty and for developing new tools for high-fidelity simulation. He is especially interested in controlling systems, like autonomous aircraft, that must act in complex environments that are often represented by expensive computational simulations. Toward this goal, he pursues research in wide-ranging areas including uncertainty quantification, statistical inference, machine learning, numerical analysis, function approximation, control, and optimization.
Prior to coming to the University of Michigan, Alex was the John von Neumann Postdoctoral Research Fellow at Sandia National Laboratories in Albuquerque, New Mexico. At Sandia, Alex worked in the Optimization and Uncertainty Quantification Group on algorithms for propagating uncertainty through physical systems described with computationally expensive simulations.
Education
- Ph.D., Aeronautics and Astronautics, Massachusetts Institute of Technology, February 2017
- S.M., Aeronautics and Astronautics, Massachusetts Institute of Technology, June 2012
- B.S.E., Aerospace Engineering, University of Michigan, June 2010
Research Interests
Algorithms for decision making under uncertainty:
– Uncertainty quantification
– Bayesian inference
– Statistical Learning
– Numerical analysis, tensor methods and their usage for high-fidelity solver development.
– Stochastic control and optimization
Applications:
– Computational physics
– Space propulsion systems and plasma systems
– Autonomous systems
Professional Service
- Society for Industrial and Applied Mathematics (SIAM)
- American Institute of Aeronautics and Astronautics (AIAA)
- Institute of Electrical and Electronics Engineers (IEEE)
Awards
- John von Neumann Postdoctoral Research Fellowship in Computational Science, 2016
- Air Force Office of Scientific Research Young Investigator Program, 2018
- NSF Career Award, 2023
Teaching
Inference Estimation and learning; Aircraft Dynamics; Control Systems; Optimal Control and Trajectory Optimization
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