Research Scientist Intern (adv. Yann LeCun) at Meta
San Francisco Bay Area United States
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Summary
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Senior
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Top School
Michael Psenka is a research-focused engineer and EECS PhD candidate at UC Berkeley with eight years of experience bridging mathematical theory and practical machine learning systems. Currently interning with Yann LeCun at Meta, he works on enabling reasoning and planning in real-world video world models that interface with action and control. His background includes provable advances in optimization on tensor manifolds, non-Euclidean multi-view reconstruction, and applied ML systems work—from denormalizing databases and search improvements to a workplace-analytics algorithm and a patent-driven product flow. He has taught and organized large undergraduate courses in discrete math and probability, demonstrating an ability to translate deep theory into clear instruction. Notably, his work consistently seeks to extend pretrained models beyond their initial capabilities through principled, mathematical approaches that scale to embodied and control-aware settings.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Electrical Engineering and Computer Science (EECS), Doctor of Philosophy - PhD, Electrical Engineering and Computer Science (EECS) at University of California, Berkeley
Bachelor of Arts - BA, Mathematics, minors in Computer Science and Applied Math, Graduate, Bachelor of Arts - BA, Mathematics, minors in Computer Science and Applied Math, Graduate at Princeton University
Manopt, a Matlab toolbox for optimization on manifolds
Contributions:10 pushes in 1 month
matlab-toolboxmanoptmatlabtoolboxoptimization
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Michael Psenka - Research Scientist Intern (adv. Yann LeCun) at Meta