Scholar
Michael Psenka
Google Scholar ID: vqYq3egAAAAJ
PhD Student, EECS, UC Berkeley
Citations & Impact
Citations
146
H-index
6
i10-index
4
Publications
11
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Publications: 'Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional' (ICML 2025), 'Learning a Diffusion Model Policy from Rewards via Q-Score Matching' (ICML 2024), 'Representation Learning via Manifold Flattening and Reconstruction' (JMLR 2024), 'Role of Uncertainty in Anticipatory Trajectory Prediction for a Ping-Pong Playing Robot' (2023). Awards: Peter A. Greenberg '77 Memorial Prize for Mathematics (June 2020), Manfred Pyka Memorial Prize for Physics (June 2018), First Place, HackPrinceton (April 2018).
Research Experience
- Worked with Prof. Yi Ma, Prof. Pieter Abbeel, and Prof. Shankar Sastry on research projects.
Education
- University of California, Berkeley, MS/PhD in EECS, 2021-2026, GPA: 4.0, Advisor: Prof. Aditi Krishnapriyan; Princeton University, A.B. in Mathematics, 2017-2021, GPA: 3.6, Minors in Computer Science and Applied Math.
Background
- Research Interests: Mathematical approaches to deep learning algorithms. Professional Field: Artificial Intelligence, Deep Learning Architectures and Algorithms. Brief Introduction: Focuses on developing deep learning models that are both theoretically elegant and practically beneficial.
Miscellany
- Personal Interests: Music (participated in Princeton Pianist Ensemble), Data Science (member of Princeton Data Science)
Co-authors