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Regular version of the site
Contacts

109028, Moscow,
11, Pokrovsky boulevard

Phone: +7 (495) 531-00-00 *27254

Email: computerscience@hse.ru

 

Administrations
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
Article
Infinite transitivity, finite generation, and Demazure roots

Arzhantsev I., Kuyumzhiyan K., Zaidenberg M.

Advances in Mathematics. 2019. Vol. 351. P. 1-32.

Article
Bias in False Discovery Rate Estimation in Mass-Spectrometry-Based Peptide Identification

Sulimov P., Voronkova A., Danilova Y. et al.

Journal of Proteome Research. 2019. Vol. 18. No. 5. P. 2354-2358.

Article
Compression of recurrent neural networks for efficient language modeling

Grachev A., Ignatov D. I., Savchenko A.

Applied Soft Computing Journal. 2019. Vol. 79. P. 354-362.

Book chapter
Numerical Pattern Mining Through Compression

Makhalova T., Kuznetsov S., Napoli A.

In bk.: 2019 Data Compression Conference Proceedings. IEEE, 2019.

Research

The Faculty is active in many research areas: theoretical computer science, algorithms for big data, optimization, 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: Dmitry Vetrov, Research Professor at HSE

The Centre conducts research in machine learning and probabilistic modeling by combining two popular approaches, neural networks, and Bayesian methods. The Centre includes Samsung-HSE Laboratory led by Dmitry Vetrov and Laboratory of Data Analysis in Financial Technologies led by Evgeny Sokolov.

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: 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, optimization, 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.

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: 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 modeling, analysis, and design.

Head: Alexander Shapoval, Professor, Faculty of Computer Science

The laboratory was created to solve interdisciplinary problems in the field of applied mathematics that lie at the intersection of mathematics, data science, physics, economics, finance, and sociology.

Head: Maria Poptsova, Associate Professor, Faculty of Computer Science

The laboratory of bioinformatics was created in 2018 to develop the field of bioinformatics at the Faculty of Computer Science. Due to the revolution in high-throughput technologies bioinformatics became Big Data Science in Genomics. The main direction of educational and scientific activities of the laboratory are fundamental research in the area of DNA secondary structures and their role in genome functioning, chromatin organization, and DNA-protein interactions.

Head: Dmitry Ignatov, Associate Professor, Faculty of Computer Science

The Laboratory’s area of expertise is analysis of unstructured data. The Laboratory studies recommending systems and services, develops methods for multimodal clustering and classification that allow profiling user interests based on various modalities. The Laboratory works in natural language processing, in particular, on neural-network methods for analyzing texts written in Russian.
 

Head: Vsevolod Chernyshev, Associate Professor, Faculty of Computer Science
The research interests of the Laboratory are at the crossover of several areas: applied geometry, topology and combinatorics, data analysis, and brain sciences. The laboratory aims to create a community of researchers with complementary knowledge and skills and working in the field of topological analysis of brain activity data. This area is quite attractive in itself: modern scanning methods make it possible to answer questions that, in the last century, were considered purely philosophical. Due to modern technologies, it becomes possible both to uncover the principles of operation of individual neurons and to study global characteristics such as correlation graphs of neural clusters.

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