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Regular version of the site

Dean — Ivan Arzhantsev


First Deputy Dean — Tamara Voznesenskaya


Deputy Dean for Research and International Relations — Sergei Obiedkov


Deputy Dean for Methodical and Educational Work — Ilya Samonenko


Deputy Dean for Development, Finance and Administration — Irina Plisetskaya

Phone: +7 (495) 772-95-90 * 12332


125319, Moscow, 3 Kochnovsky Proezd (near metro station 'Aeroport'). 

Feb 22 – Feb 23
Регистрация открыта 
Mar 21 – Mar 23
Papers Submission Deadline: 15 January 2019 
Jun 12 – Jun 14
submission: Friday, 01 February 2019, notification: Friday, 15 February 2019 
Aug 26 – Aug 30
Registration and Poster Submission deadline — April 1, 2019 
Ontology-Mediated Queries: Combined Complexity and Succinctness of Rewritings via Circuit Complexity

Bienvenu M., Kikot S., Kontchakov R. et al.

Journal of the ACM. 2018. Vol. 65. No. 5. P. 28:1-28:51.

Randomized Block Cubic Newton Method
In press

Doikov Nikita, Richtarik P.

Proceedings of Machine Learning Research. 2018. No. 80. P. 1290-1298.

Particle-identification techniques and performance at LHCb in Run 2
In press

Hushchyn M., Chekalina V.

Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2018. P. 1-2.

Observational evidence in favor of scale free evolution of sunspot groups

Shapoval A., Le Mouël J., Shnirman M. et al.

Astronomy and Astrophysics. 2018. Vol. 618. P. A183-1-A183-13.


The Faculty is active in many research areas: theoretical computer science, algorithms for big data, optimisation, machine learning, computer vision, software engineering, and bioinformatics. We publish in leading computer science journals and present our results at major conferences.

Selected publications

Faculty Laboratories

Head: Professor Nikolay Vereshchagin, Member of the Academy of Europe

Established in late 2015, the Laboratory conducts research in computational complexity, information theory, algorithmic statistics, combinatorial optimization, and algorithmic game theory. Dr. Vladimir Gurvich, an internationally renowned scientist in the field of theoretical computer science, works here as a leading international researcher.

Head: Professor Sergei O. Kuznetsov, Member of the HSE Academic Council

The Laboratory is a center for researching and integrating the latest methods of artificial intelligence (with a focus on data mining and structural analysis) in order to improve software “intelligence” and adaptability. Dr. Andre Scedrov, a widely respected scientist in the field of logic and formal methods in computer science, is one of the Laboratory’s leading researchers.

Head: Andrey Ustyuzhanin, Head of joint CERN-Yandex Research & Education programs at Yandex Data Factory

Established in February 2015, LAMBDA currently focuses on using machine learning and data analysis methods to solve problems of fundamental science such as particle physics and astrophysics. The Laboratory cooperates with the European Organisation for Nuclear Research (CERN) and the Large Hadron Collider.

Head: Professor Irina A. Lomazova, member of IEEE Task Force on Process Mining

The Laboratory was established in January 2013 under the scientific leadership of world-renowned Dutch scientist Dr. Wil van der Aalst. The Laboratory conducts research in the field of process mining and process-aware information systems such as BPM systems, workflow management systems, ERP systems, and case handling systems. The main goal is to develop new methods and approaches in PAIS modelling, analysis, and design.

Head:  Dmitry Vetrov, Research Professor at HSE
The Centre conducts research in machine learning and probabilistic modelling by combining two popular approaches, neural networks and Bayesian methods. Head: Alexey Naumov, Associate Professor, Faculty of Computer Science

The International Laboratory of Stochastic Algorithms and High-Dimensional Inference was created in April 2018 and is part of the Faculty of Computer Science at HSE. Russian and international researchers work at the laboratory at the intersection of numerous mathematical disciplines, including modern statistics, optimisation, probability theory and theory of computation. Its main aim is to develop new probability and statistical approaches to current problems in the field of data analysis.

Faculty Colloquium

This platform for scientific discussions is meant to foster connections among researchers in different fields of computer science. The field of computer science is constantly developing and it is crucial to be aware of the latest developments. The Faculty Colloquium is a research seminar for the Faculty’s teachers, scholars, and doctoral, graduate and undergraduate students, as well as for anyone else who interested in computer science.

Conferences and Workshops