Michael Panchenko
Co-Founder at Oraios AI
Munich, Bavaria, Germany
Summary
🤩
Rockstar🎓
Top SchoolMichael Panchenko is a Co-Founder and AI researcher with seven years of experience building production-grade ML systems, cloud data pipelines, and CI/CD infrastructure from research prototypes to industry deployments. Trained as a theoretical physicist and mathematician (PhD and dual MS degrees from LMU Munich), he combines deep analytical rigor with fast learning—having completed two master's programs simultaneously and learned five languages. He has led applied research in computer vision, earth observation, reinforcement learning and LLMs at appliedAI and contributed to production-focused libraries such as the popular Tianshou RL toolkit, improving type safety and maintainability. At Oraios AI he now focuses on AI consulting and internal products, bridging high-quality software engineering with cutting-edge model research. Outside of work he teaches university-level analysis to motivated high-schoolers and pursues climbing, skiing and paragliding in the Alps.
7 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD Theoretical and Mathematical Physics, Doctor of Philosophy - PhD Theoretical and Mathematical Physics at Ludwig-Maximilians-Universität München
German, Russian, English, Spanish, French
Stackoverflow
431reputation
43kreached
6answers
0questions
Github Skills (21)
pytorch10
python10
data-structure10
refactor10
typehinting10
deep-learning10
data-structures10
refactoring10
type-checking10
documentation8
cicd8
unit-testing8
lru6
aws-cloudformation6
pipeline6
Programming languages (11)
Github contributions (5)
thu-ml/tianshou
Jul 2023 - Jan 2025
An elegant PyTorch deep reinforcement learning library.
Role in this project:
Backend Developer
Backend DeveloperContributions:6 releases, 428 reviews, 107 PRs in 1 year 6 months
Contributions summary:Michael's commits primarily focus on improving the type safety, reducing code duplication, and enhancing documentation within the `tianshou` library. They introduce and refine typing strategies, particularly the `BatchProtocol`, to improve IDE support and catch potential bugs. The changes affect core data structures like `Batch` and the trainer interfaces, with a focus on code clarity and maintainability. The user's work also involves formatting and dependency management, along with a reorganization of test dependencies and adjustments to the CI pipeline.
deep-reinforcement-learningbenchmarknpgtd3reinforcement
appliedAI-Initiative/accsr
Aug 2020 - Oct 2022
Lightweight library for accessing data and configuration
Contributions:22 reviews, 113 commits, 6 PRs in 2 years 3 months
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