Ivan Kharitonov
Senior ML Engineer Research - Reinforcement Learning at Next Step Fusion
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolIvan Kharitonov is a Senior ML Engineer and researcher in reinforcement learning with 9 years of engineering experience and an M.Sc. in Electrical Engineering complemented by top-tier ML training. Based in London, he has spent the last several years building perception, multi-object tracking, and trajectory prediction systems for autonomous driving, leading teams to productionize uncertainty-aware deep learning models and in-house datasets. He now applies RL to control and simulation of fusion devices, blending classical control theory from his early automotive work with modern model-based and model-free RL techniques. An active contributor to Yandex School of Data Analysis’s Practical_RL course, he has hands-on experience improving MCTS implementations and seminar materials that bridge research and application. His background in embedded automotive electronics and ROS2 LIDAR pipelines gives him a rare end-to-end perspective from sensors to control algorithms.
9 years of coding experience
11 years of employment as a software developer
Robotics Technology/Technician, Robotics Technology/Technician at Formula Student Germany - Waymo workshopData mining in actionComputer Science, Computer Science at Yandex School of Data AnalysisSpecialist Electrical Engineering - RADARs GNSS telecommunication systems, Specialist Electrical Engineering - RADARs GNSS telecommunication systems at Bauman Moscow State Technical University
English
Github Skills (6)
deep-reinforcement-learning10
pytorch10
reinforcement-learning10
python9
courses-resource9
jupyter-notebook9
Programming languages (8)
Github contributions (5)
yandexdataschool/Practical_RL
Apr 2018 - Apr 2020
A course in reinforcement learning in the wild
Role in this project:
ML Engineer
ML EngineerContributions:3 reviews, 45 commits, 10 PRs in 2 years 1 month
Contributions summary:Ivan primarily contributed to the reinforcement learning course materials, with commits focused on adding and updating seminar notebooks. Their work involved visualizing results and fixing comments within the seminar notebooks. Furthermore, the user updated and fixed MCTS (Monte Carlo Tree Search) implementation, demonstrating an understanding of reinforcement learning algorithms.
pytorchgit-coursedeep-learningreinforcement-learningwild
kharitonov-ivan/multi-object-tracking-in-python
Jan 2021 - Jul 2021
Python implementation of multi object tracking algorithms including PMBM (Poisson Multi Bernoulli Mixture filter)
Contributions:43 reviews, 271 commits, 7 PRs in 5 months
filtermulti-object-trackingphdpmbmtracker
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