Aleksei Shpilman

Research Groups

Biography

Masters degree in Bioengineering and Bioinformatics from Lomonosov Moscow State University.

Ph.D. in Technical Sciences from Saint-Petersburg State University.

Laureate of Ilya Segalovich science prize in AI research.

Author of more than 20 AI papers.

Winner of more than 10 international machine learning competitions.

Professional Activity

Head of AI Labs, JetBrains Research, Saint-Petersburg.

Director, Center for Data Analysis and Machine Learning, HSE University, Saint-Petersburg.

Author and academic director of Machine Learning and Data Analysis Master Program, HSE University, Saint-Petersburg.

Publications

Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data

March 2022

Farid Bagirov, Dmitry Ivanov, Aleksei Shpilman

Arxiv preprint

Maximum Entropy Model-based Reinforcement Learning

December 2021

Oleg Svidchenko, Aleksei Shpilman

NeurIPS'2021 Deep Reinforcement Learning Workshop

Simple End-to-end Deep Learning Model for CDR-H3 Loop Structure Prediction

December 2021

Natalia Zenkova, Ekaterina Sedykh, Tatiana Shugaeva, Vladislav Strashko, Timofei Ermak, Aleksei Shpilman

NeurIPS 2021 Machine Learning for Structural Biology Workshop

Self-Imitation Learning from Demonstrations

December 2021

Georgiy Pshikhachev, Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman

NeurIPS'2021 Deep Reinforcement Learning Workshop

Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation

November 2021

Vsevolod Konyakhin, Nina Lukashina, Aleksei Shpilman

Conference on Neural Information Processing Systems (NeurIPS 2021) Traffic4cast Competition

Solving black-box optimization challenge via learning search space partition for local bayesian optimization

August 2021

Mikita Sazanovich, Anastasiya Nikolskaya, Yury Belousov, Aleksei Shpilman

NeurIPS 2020 Competition and Demonstration Track

Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World

March 2021

Florian Laurent, Manuel Schneider, Christian Scheller, Jeremy Watson, Jiaoyang Li, Zhe Chen, Yi Zheng, Shao-Hung Chan, Konstantin Makhnev, Oleg Svidchenko, Vladimir Egorov, Dmitry Ivanov, Aleksei Shpilman, Evgenija Spirovska, Oliver Tanevski, Aleksandar Nikov, Ramon Grunder, David Galevski, Jakov Mitrovski, Guillaume Sartoretti, Zhiyao Luo, Mehul Damani, Nilabha Bhattacharya, Shivam Agarwal, Adrian Egli, Erik Nygren, Sharada Mohanty

NeurIPS 2020 Competition and Demonstration Track

Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments

February 2021

Dmitry Ivanov, Vladimir Egorov, Aleksei Shpilman

International Conference on Autonomous Agents and MultiAgent Systems (AAMAS'2021)

Automatic generation of reviews of scientific papers

December 2020

Anna Nikiforovskaya, Nikolai Kapralov, Anna Vlasova, Oleg Shpynov, Aleksei Shpilman

ICMLA2020

Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation

December 2020

Nina Lukashina, Alisa Alenicheva, Elizaveta Vlasova, Artem Kondiukov, Aigul Khakimova, Emil Magerramov, Nikita Churikov, Aleksei Shpilman

Machine Learning for Molecules Workshop at NeurIPS'2020

Imitation Learning Approach for AI Driving Olympics Trained on Real-world and Simulation Data Simultaneously

July 2020

Mikita Sazanovich, Konstantin Chaika, Kirill Krinkin, Aleksei Shpilman

Workshop on AI for Autonomous Driving (AIAD), the 37th International Conference on Machine Learning (ICML2020)

Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler

June 2020

Timofey Bryksin, Victor Petukhov, Ilya Alexin, Stanislav Prikhodko, Alexey Shpilman, Vladimir Kovalenko and Nikita Povarov

17th International Conference on Mining Software Repositories (MSR'20)

Artificial Intelligence for Prosthetics-challenge solutions

November 2019

Łukasz Kidziński, Carmichael Ong, Sharada Prasanna Mohanty, Jennifer Hicks, Sean F Carroll, Bo Zhou, Hongsheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaśkowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy Watson, Marcel Salathé, Sergey Levine, Scott Delp

The NeurIPS '18 Competition

End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box

October 2019

Vladislav Belyaev, Aleksandra Malysheva, Aleksei Shpilman

XVI International Symposium "Problems of Redundancy in Information and Control Systems" (REDUNDANCY)

MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning

October 2019

Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman

XVI International Symposium "Problems of Redundancy in Information and Control Systems" (REDUNDANCY)

Automatic Classification of Error Types in Solutions to Programming Assignments at Online Learning Platform

June 2019

Artyom Lobanov, Timofey Bryksin, and Alexey Shpilman

The 20th International Conference on Artificial Intelligence in Education (AIED'19)

Framework for Deep Reinforcement Learning with GPU-CPU Multiprocessing

December 2018

Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman

Open Access Software

Deep Multi-Agent Reinforcement Learning with Relevance Graphs

December 2018

Aleksandra Malysheva, Tegg Taekyong Sung, Chae-Bong Sohn, Daniel Kudenko, Aleksei Shpilman

NeurIPS Deep Reinforcement Learning Workshop

A comparative evaluation of machine learning methods for robot navigation through human crowds

December 2018

A. Gaydashenko, D. Kudenko, A. Shpilman

ICMLA

Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data

November 2018

A. Malysheva, D. Kudenko, A. Shpilman

ICARCV

Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation

November 2018

I. Sosin, D. Kudenko, A. Shpilman

ICARCV

Automatic Recommendation of Move Method Refactorings Using Clustering Ensembles

September 2018

Timofey Bryksin, Evgenii Novozhilov, and Aleksei Shpilman

2nd International Workshop on Refactoring (IWoR'18)

Learning to Run with Reward Shaping from Video Data

July 2018

A. Malysheva, A. Shpilman, D. Kudenko

Workshop on Adaptive and Learning Agents (ALA) at ICML-AAMAS

Automated Refactoring of Object-Oriented Code Using Clustering Ensembles

June 2018

Timofey Bryskin, Alexey Shpilman, and Daniel Kudenko

AAAI Workshop on Natural Language Processing for Software Engineering (NLP4SE'18)

Deep Learning of Cell Classification using Microscope Images of Intracellular Microtubule Networks

December 2017

A. Shpilman, D. Boikiy, M. Plyakova, D. Kudenko, A. Burakov, E. Nadezhdina

ICMLA

Dependence of stress granule formation on microtubules supports the idea of stress granule specific “glue” arising in stress conditions

2014

Shpilman A., Shudinova E., Ivanov P., Nadezhdina E.

54th Annual Meeting of the American Society for Cell Biology

Using Quazi-3D Approach for Microtubule Self-Organization Model

2014

Primako E.M., Shpilman A.A.

V ICMBB

Investigation on Dependence of Stress Granules Formation on Microtubule Network Parameters and Stress Agent Concentration Through Numerical Model

2014

Shpilman A.A., Chudinova E.V., Lubitelev A., Ivanov P.A. Nadezhdina E.S.

V ICMBB

Role of Microtubules in Formation of Stress Granules

2013

Chudinova E.M., Shpilman A.A., Lubitelev A.V., Ivanov P.A., Nadezhdina E.S.

AIPRC

Molecules that Organize Cell Microtubule Systems and Why are They Doing It

2012

Brodsky I.B., Burakov A.V., Zhapparova O.N., Ivanov P.A., Fokin A.I., Chudinova E.M., Shanina A.N., Shpilman A.A., Nadezhdina E.S.

III SCBM

Microtubules govern stress granule mobility and dynamics, Biochimia Biophysica Acta

2010

Nadezhdina E.S., Lomakin A.J., Shpilman A.A., Chudinova E.M., Ivanov P.A.

Biochimia Biophysica Acta

Simple Computer Model Shows Posibility of Non-Motor Microtubule Binded Gradient Transport

2009

Shpilman A.

49th Annual Meeting of the American Society for Cell Biology

In silico vs in vitro: Mimitation v1.0 program allows to predic morphological and dynamic changes of tubulin cytoskeleton caused by microtubule stabilization

2008

Shpilman A.A, Nadezhdina E.S.

Biological Motility: Achievements and Perspectives

Imitational Modeling of Cytoskeleton: Dynamics, Differentiation, Active Transport and Membrane Interactions

2008

Shpilman A., Nadezhdina E.S.

48th Annual Meeting of the American Society for Cell Biology

Disturbance of the Radial System of Interphase Microtubules in the Presence of Excess Serum in Cell Culture Medium

2008

E.V. Usova, A.V.Burakov, A.A. Shpilman, E.S. Nadezhdina

Biophysics

Computational Stochastic Modeling of Cellular Microtubule Network

2006

Shpilman A.A., Nadezhdina E.S.

46th Annual Meeting of the American Society for Cell Biology

Stochastic Computer Model of the Cell Microtubule Dynamics

2006

А.А. Shpil’man and E.S. Nadezhdina

Biophysics

Stochastic Modeling of Microtubule Systems

2006

Shpilman A.A.

I ICMBB

Aleksei Shpilman

Research Groups

Biography

Professional Activity

Publications

Improving State-of-the-Art in One-Class Classification by Leveraging Unlabeled Data

Maximum Entropy Model-based Reinforcement Learning

Simple End-to-end Deep Learning Model for CDR-H3 Loop Structure Prediction

Self-Imitation Learning from Demonstrations

Solving Traffic4Cast Competition with U-Net and Temporal Domain Adaptation

Solving black-box optimization challenge via learning search space partition for local bayesian optimization

Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World

Balancing Rational and Other-Regarding Preferences in Cooperative-Competitive Environments

Automatic generation of reviews of scientific papers

Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation

Imitation Learning Approach for AI Driving Olympics Trained on Real-world and Simulation Data Simultaneously

Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler

Artificial Intelligence for Prosthetics-challenge solutions

End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box

MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning

Automatic Classification of Error Types in Solutions to Programming Assignments at Online Learning Platform

Framework for Deep Reinforcement Learning with GPU-CPU Multiprocessing

Deep Multi-Agent Reinforcement Learning with Relevance Graphs

A comparative evaluation of machine learning methods for robot navigation through human crowds

Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data

Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation

Automatic Recommendation of Move Method Refactorings Using Clustering Ensembles

Learning to Run with Reward Shaping from Video Data

Automated Refactoring of Object-Oriented Code Using Clustering Ensembles

Deep Learning of Cell Classification using Microscope Images of Intracellular Microtubule Networks

Dependence of stress granule formation on microtubules supports the idea of stress granule specific “glue” arising in stress conditions

Using Quazi-3D Approach for Microtubule Self-Organization Model

Investigation on Dependence of Stress Granules Formation on Microtubule Network Parameters and Stress Agent Concentration Through Numerical Model

Role of Microtubules in Formation of Stress Granules

Molecules that Organize Cell Microtubule Systems and Why are They Doing It

Microtubules govern stress granule mobility and dynamics, Biochimia Biophysica Acta

Simple Computer Model Shows Posibility of Non-Motor Microtubule Binded Gradient Transport

In silico vs in vitro: Mimitation v1.0 program allows to predic morphological and dynamic changes of tubulin cytoskeleton caused by microtubule stabilization

Imitational Modeling of Cytoskeleton: Dynamics, Differentiation, Active Transport and Membrane Interactions

Disturbance of the Radial System of Interphase Microtubules in the Presence of Excess Serum in Cell Culture Medium

Computational Stochastic Modeling of Cellular Microtubule Network

Stochastic Computer Model of the Cell Microtubule Dynamics

Stochastic Modeling of Microtubule Systems

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