Maksim Podkorytov
Computer Science Ph.D. Student at Florida State University
Tallahassee, Florida, United States
Summary
🤩
Rockstar🎓
Top SchoolMaksim Podkorytov is a Ph.D. computer scientist with 13 years of software and research experience, blending deep algorithmic training from MSU with systems and ML work at universities and industry. He has contributed to scalable distributed systems—from MPI-based reservoir simulation at Rock Flow Dynamics to OLAP tooling at Facebook—and now focuses on deep learning for NLP during his doctoral work at Florida State. Maksim’s research on polystore databases and data integration produced publications at venues like ICDE, while his backend contributions to PyTorch’s static runtime show practical expertise optimizing high-performance ML infrastructure. Comfortable across C++, Python, databases and large-scale data systems, he pairs rigorous academic thinking with hands-on performance engineering.
13 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Florida State UniversityUniversity of Texas at San AntonioHigh School, Physics and Mathematics, 4.9/5.0, High School, Physics and Mathematics, 4.9/5.0 at Advanced Educational Scientific Center of M.V.Lomonosov Moscow State University (Kolmogorov School)Lomonosov Moscow State University
English, Russian
Stackoverflow
236reputation
704reached
1answer
2questions
Github Skills (16)
tensorrt10
pytorch10
c-language10
tensor10
tensorflow10
cprogramming-language10
operation10
python9
machine-learning9
deep-learning9
autograd8
gpu8
numpy7
geode6
configurations6
Programming languages (7)
Github contributions (5)
pytorch/pytorch
Mar 2022 - Jan 2023
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:
Back-end Developer / ML Engineer
Back-end Developer / ML EngineerContributions:74 reviews, 34 commits, 48 PRs in 10 months
Contributions summary:Maksim primarily contributed to the static runtime component of PyTorch, focusing on implementing and optimizing operations within the static runtime environment. Their work included adding support for new features (e.g., aten::max, aten::mean), modifying existing code, and adding NNC codegen for aten::div to improve performance. They were also responsible for modifications to the internal code for view start, schema checks, and testing, indicative of a backend focus with a strong understanding of the project's internals and performance characteristics.
pythongpu-accelerationdeep-learninggpunumpy
tenpercent/xformers
Feb 2024 - Jan 2025
Hackable and optimized Transformers building blocks, supporting a composable construction.
Contributions:1 review, 1 PR, 107 pushes in 11 months
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