Biography
Graduated from School of Bioinformatics and Bioengineering of Lomonosov Moscow State University in 2010.
Professional Activity
Educational Program Director, Reseach and Education Center "JetBrains", Saint-Petersburg.
Director, Center for Data Analysis and Machine Learning, National Research University Higher School of Economics, Saint-Petersburg.
Head of Applied Machine Learning and Deep Learning Laboratory, JetBrains Research, Saint-Petersburg.
Head of Agent Systems and Reinforcement Learning Laboratory, JetBrains Research, Saint-Petersburg.
Academic Advising
Academic Supervisor of Bachelors, Masters, and Ph.D. projects at HSE, ITMO, SPbSU.
Projects
-
We apply anomaly detection algorithms on all publicly avaliable Kotlin code to identify anomalous code fragments that can be of interest for the Kotlin compiler team.Project supervisor: Timofey Bryksin
Publications
- The NeurIPS '18 Competition, November 2019
- The 20th International Conference on Artificial Intelligence in Education (AIED), June 2019
- Adaptive and Learning Agents at AAMAS, May 2019
- NeurIPS Deep Reinforcement Learning Workshop, December 2018
- Open Access Software, December 2018
- ICMLA, December 2018
- ICARCV, November 2018
- ICARCV, November 2018
- 2nd International Workshop on Refactoring (IWoR), September 2018
- Workshop on Adaptive and Learning Agents (ALA) at ICML-AAMAS, July 2018
- AAAI Workshop on Natural Language Processing for Software Engineering, February 2018
- ICMLA, December 2017
-
Investigation on Dependence of Stress Granules Formation on Microtubule Network Parameters and Stress Agent Concentration Through Numerical ModelV ICMBB, 2014
-
Dependence of stress granule formation on microtubules supports the idea of stress granule specific “glue” arising in stress conditions54th Annual Meeting of the American Society for Cell Biology, 2014
-
Using Quazi-3D Approach for Microtubule Self-Organization ModelV ICMBB, 2014
-
Role of Microtubules in Formation of Stress GranulesAIPRC, 2013
-
Molecules that Organize Cell Microtubule Systems and Why are They Doing ItIII SCBM, 2012
-
Microtubules govern stress granule mobility and dynamics, Biochimia Biophysica ActaBiochimia Biophysica Acta, 2010
-
Simple Computer Model Shows Posibility of Non-Motor Microtubule Binded Gradient Transport49th Annual Meeting of the American Society for Cell Biology, 2009
-
Imitational Modeling of Cytoskeleton: Dynamics, Differentiation, Active Transport and Membrane Interactions48th Annual Meeting of the American Society for Cell Biology, 2008
-
In silico vs in vitro: Mimitation v1.0 program allows to predic morphological and dynamic changes of tubulin cytoskeleton caused by microtubule stabilizationBiological Motility: Achievements and Perspectives, 2008
-
Disturbance of the Radial System of Interphase Microtubules in the Presence of Excess Serum in Cell Culture MediumBiophysics, 2008
-
Stochastic Modeling of Microtubule SystemsI ICMBB, 2006
-
Stochastic Computer Model of the Cell Microtubule DynamicsBiophysics, 2006
-
Computational Stochastic Modeling of Cellular Microtubule Network46th Annual Meeting of the American Society for Cell Biology, 2006
-
Machine Learning and Information Management Lab Advisor
-
Machine Learning Methods in Software Engineering Advisor
-
Machine Learning Applications and Deep Learning Head of Laboratory
-
Agent Systems and Reinforcement Learning Head of Laboratory