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I am a Ph.D. student at the University of Washington, working with Jingwei Hu.
I grew up in Moscow, Russia. At 17 I moved to Boston to attend Boston University. My first academic interest was economics but I switched to math mid-way. In 2017 I spent a semester in Auckland, New Zealand, where I took my first proof based-math class. In 2019 I graduated from BU but stayed another year for a Masters degree in computer science, graduating in 2020. I started my PhD in pure math at the University of Washington in 2020, working on algebraic topology, but switched to applied math in 2022 after the first internship at Google. Since then I have worked on applications of deep learning and interacting particle systems to the Landau equation and to sampling.
- Scientific computing: solve high-dimensional PDEs using interacting particle systems and neural networks.
- Math formalization: accelerate mathematics research with Lean and AI.
- [Jan. 2025] Gave two talks at JMM 2025 on sampling and Lean.
- [Nov. 2024] Submitted a paper on image editing with diffusion models to CVPR 2025.
- [Sep. 2024] Finished my third internship at Google, working on detection of defective TPUs using maching learning.
- [Jun. 2024] Participated in the SLMath summer school on interacting particle systems.
- [May 2024] Released pre-print Transport based particle methods for the Fokker-Planck-Landau equation.
- [Feb. 2024] Passed my general exam.
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