Sergey Kolesnikov is Head of Applied Research in Singapore with nine years of experience bridging academic deep learning and industrial AI, specializing in reinforcement learning and sequential decision making. He previously led AI research at Tinkoff and now heads applied research at Shadow Startup, translating novel algorithms into production systems. As creator and maintainer of Catalyst and Animus, he pairs open-source leadership with pragmatic engineering — even contributing test coverage to widely used projects like Kaggle's python docker image to improve reproducibility. Trained at MIPT in mathematics and computer science, Sergey blends rigorous theoretic grounding with hands-on delivery across startups, banks, and research labs to move RL from prototype to product.
10 years of coding experience
6 years of employment as a software developer
Moscow Institute of Physics and Technology (State University) (MIPT)
Contributions:7 commits, 1 PR, 6 comments in 6 days
Contributions summary:Sergey's commits primarily focus on creating and updating test files within the `tests` directory. These tests cover functionality within the `catalyst` library, including version verification and the execution of an MNIST example with PyTorch. The user implemented and modified tests to ensure the correct behavior of the library, specifically focusing on the training and evaluation process of a neural network model. The commits reflect an iterative approach, adding new tests and refining existing ones to improve test coverage.
Contributions:31 commits, 29 pushes, 1 branch in 3 months
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Sergey Kolesnikov - Head Of Applied Research at Shadow Startup