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Table of contents

General Information

Full Name Aleksandr Panov
Place of work Moscow, Russia
Languages Russian, English

Education

  • 2015
    PhD
    Institute for System Analysis of RAS, Moscow, Russia
    • Specialized in modeling of goal-oriented behavior of intelligent agents and their coalitions
    • Thesis title is Investigation of methods, development of models and algorithms for formation of elements of sign-based worldview of the actor
  • 2011
    Master’s degree
    Moscow Institute of Physics and Technology, Department of Applied Mathematics and Management, Dolgoprudny, Russia
    • Majors are technologies of active databases, computer graphics, game theory and decision making, effective algorithms, decomposition in optimization
    • Specialized in logical methods (AQ, JSM) of data mining and multi-agent systems
    • Thesis title is Investigation and modeling of group behavior for multifunctional agents
  • 2009
    Bachelor of Physics
    Novosibirsk State University, Department of Physics, Novosibirsk, Russia
    • Majors are operational systems, digital integrated circuits, introduction to CAD, microprocessors, information networks and systems, object-oriented analysis and design
    • Specialized in semantic integration of databases.
    • Thesis title is Semantic integration of biological databases

Teaching Experience

  • 2019 - Present
    Head of AI Master Program
    Moscow Institute of Physics and Technology, Phystech School of Applied Mathematics and Informatics, Dolgoprudny, Russia
    • Seminars on Basis of Operation Systems and Basis of Object-Oriented Programming
    • Lectures on Introduction in AI and Reinforcement Learning
  • 2015 - 2019
    Associate Professor
    National Research University Higher School of Economics, Faculty of Computer Science, Moscow, Russia
    • Seminar on Intelligent Data Mining
  • 2011 - 2016
    Assistant Lecturer
    Peoples’ Friendship University of Russia, Department of Computer Science, Moscow, Russia
    • Lectures on Intelligent Dynamic Systems, Theoretical Computer Science and Intelligent Data Analysis

Research Experience

  • 2021 - Present
    Principal Research Fellow
    Artificial Intelligence Research Institute, Neural-symbolic team, Moscow, Russia
    • Leading non-profit organization in the field of Artificial Intelligence – http://airi.net
    • Reinforcement learning in multi-agent systems
      • Switching algorithms of planning-based and learning-based multi-agent path finding methods
      • Monte-Carlo approach in multi-agent systems
    • Neural-symbolic integration
      • Disentangled representations and object-oriented world models
      • Vector symbolic architectures in VQA and robot navigation setting
  • 2010 - Present
    Principal Research Fellow, Head of Laboratory
    Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow, Russia
    • Leading academic institute in Computer Science and High-performance computing – http://frccsc.ru
    • Cognitive modeling
      • Psychologically inspired models of human behavior based on theory of sign-based world model
      • Biologically inspired models of sign components - image, significance and personal meaning
      • Algorithms of behavior planning and goal setting procedures
    • Machine learning and multi-agent systems
      • The composite logical method to extract cause-effect relationships
      • Algorithms of planning and role distribution in coalition of cognitive agents
    • Cognitive Robotics
      • Multi-layer control system for coalition of cognitive robots
  • 2018 - Present
    Director, Head of Laboratory
    Moscow Institute of Physics and Technology, Center for Cognitive Modeling, Dolgoprudny, Russia
    • Leading University in Russia in Physics and Computer Science – http://cogmodel.mipt.ru
    • Applied research in self-driving cars and mobile robotics
      • New framework for behavior planning of self-driven cars based on Apollo-auto
      • Original methods of neural-based object segmentation, detection, tracking for mobile robots
    • Reinforcement learning
      • Hierarchical reinforcement learning and learning from demonstrations
      • Learning-based methods for visual navigation in indoor scenes
    • Neuromorphic computing
      • Architecture of the hierarchical intrinsically motivated agent (HIMA)
      • Improved variants of hierarchical temporal memory
  • 2015 - 2018
    Research Fellow
    National Research University Higher School of Economics, Laboratory of Process-Aware Information Systems (PAIS Lab), Moscow, Russia
    • Leading University in Russia in Economics and Computer Science - http://hse.ru
    • {"title"=>"Investigation of learning mechanisms based on sign representations in the problem of collective behavior planning"}

Honors and Awards

  • 2023
    • I led the SkillFusion team, which secured the first place in the CVPR Habitat competition
  • 2019
    • I led the CDS team, which took first place in the NeurIPS MineRL competition
  • 2017
    • Russian Academy of Sciences Medal for Young Scientists

Academic Interests

  • Computer Cognitive Modeling
    • Semiotics
    • Sign-based World Model
  • Embodied AI
    • Cognitive Robotics
    • Behaviour planning
    • Language models for planning
  • Multi-agent systems
    • Multi-agent planning
    • Multi-agent reinforcement learning
  • Reinforcement Learning
    • Model-based learning and planning
    • Transformer-based world models
    • Structured world models

Other Interests

  • Hobbies: snowboarding, ski-touring, badminton, football