Алексей Шпильман

Исследовательские группы

Биография

Окончил факультет Биоинженерии и Биоинформатики МГУ им. Ломоносова.

Кандидат технических наук.

Лауреат премии Ильи Сегаловича в номинации «Научные руководители».

Автор более 20 научных публикаций по тематике ИИ.

Занял призовые места более чем в 10 крупных международных соревнованиях по машинному обучению.

Профессиональная активность

Руководитель Лаборатории Искусственнного Интеллекта, JetBrains Research, Санкт-Петербург.

Заведующий центром анализа данных и машинного обучения НИУ ВШЭ, Санкт-Петербург.

Автор и академический руководитель магистерской программы "Машинное обучение и анализ данных", НИУ ВШЭ, Санкт-Петербург.

Публикации

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

Март 2022

Farid Bagirov, Dmitry Ivanov, Aleksei Shpilman

Arxiv preprint

Алексей Шпильман

Исследовательские группы

Биография

Профессиональная активность

Публикации

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

Maximum Entropy Model-based Reinforcement Learning

Self-Imitation Learning from Demonstrations

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

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

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

Deep Multi-Agent Reinforcement Learning with Relevance Graphs

Framework for Deep Reinforcement Learning with GPU-CPU Multiprocessing

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

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

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

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

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

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

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

Stochastic Computer Model of the Cell Microtubule Dynamics

Stochastic Modeling of Microtubule Systems

Computational Stochastic Modeling of Cellular Microtubule Network

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