teaching

Moscow Institute of Physics and Technology, Phystech School of Applied Mathematics and Informatics, Dolgoprudny, Russia

  • Lectures on Reinforcement Learning in AI master’s program
  • Lectures on Introduction in AI in AI master’s program
  • Scientific advisor of PhD these:
    • Alexey Staroverov (2023, “Methods and algorithms of learnable visual navigation of mobile robots”)
    • Alexey Skynnik (2023, “Reinforcement learning method for navigation tasks”)
  • Scientific advisor of master’s these:
    • Georgy Gorbov (2023, “Adaptive maneur planning in Apollo platform”)
    • Mikhail Melkumov (2023, “Offline reinforcement learning in interactive planning for road intersection scenarios”)
    • Maria Nesterova (2023, “Curriculum reinforcement learning in a multi-agent pathfinding problem for partially observable environments”)
    • Yelisey Pitanov (2023, “Monte-Carlo tree search and reinforcement learning in a multi-agent planning task”)
    • Kristina Sarkisyan (2023, “Language models and prompting in multimodal tasks of agent’s behavior generation”)
    • Leonid Ugadiarov (2023, “Object-oriented decomposition of world model in reinforcement learning”)
    • Igor Shimanogov (2023, “Object-oriented reinforcement learning in game environments”)
    • Eugeni Dzjivelikyan (2022, “Algorithms for modeling goal-oriented behavior using hierarchical temporal memory”)
    • Daniil Kirilenko (2022, “Visual question answering for the task of navigating robotic platforms”)
    • Artem Latyshev (2022, “Modeling intrinsic motivation in hierarchical temporal memory”)
    • Artem Zholus (2022, “Generalization of tasks for robotic control with trainable models of the world”)

National Research University Higher School of Economics, Faculty of Computer Science, Moscow, Russia

Peoples’ Friendship University of Russia, Department of Computer Science, Moscow, Russia

  • Lectures on Intelligent Dynamic Systems, Theoretical Computer Science, and Intelligent Data Analysis