Alexander (Sasha) Davydov earned his Ph.D. in Mechanical Engineering at UC Santa Barbara in 2025. He received bachelors degrees in Mechanical Engineering and in Mathematics at the University of Maryland in 2020. He is the recipient of a Best Student Paper Finalist Award at ACC 2022, the O. Hugo Schuck Best Paper Award in 2023, and the 2024 IEEE Control Systems Letters Outstanding Paper Award for his work on robustness of neural networks. His work has been supported by the NSF Graduate Research Fellowship, the UCSB Chancellor's Fellowship, and the Air Force Office for Scientific Research.
WEBSITE(S)| Personal Website | Ken Kennedy Institute
Research Areas
Modern data-driven engineering problems at the intersection of control, machine learning, and optimization. Robust nonlinear control theory and modern machine learning methods to enable reliable control of complex engineering systems.
Education
Ph.D. in mechanical engineering at the University of California, Santa Barbara (UCSB)
B.S. in mechanical engineering from the University of Maryland (UMD)
B.S. in mathematics from the University of Maryland (UMD)
Honors & Awards
2024 - IEEE Control Systems Letters Outstanding Paper Award
2023 - AACC O. Hugo Schuck Best Paper Award
2022 - ACC Best Student Paper Award Finalist
2021 - NSF Graduate Research Fellowship
2020 - UCSB Chancellor’s Fellowship