• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
Contacts

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

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

Email: computerscience@hse.ru

 

Administrations

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

Events
Aug 26 – Aug 30
Registration and Poster Submission deadline — May 1, 2019 
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.

International Experts in the Faculty of Computer Science

An important step in integrating the university into the global educational, scientific and research space is the expansion of international recruiting. Since its very first year, the Faculty of Computer Science at the Higher School of Economics has had a foreign professor working on staff. In 2015, four internationally recruited experts teach and conduct research in the faculty.

 

Geoffrey Decrouez has worked in the faculty since 2014. He currently teaches the courses Modern Methods of Decision Making and Probability Theory and Mathematical Statistics in the Data Science Master's programme. Geoffrey is a graduate of the Master's programme at the Grenoble National Polytechnic Institute (INPG); he received his PhD at the University of Melbourne (Australia).

Bruno Bauwens, an expert in Kolmogorov complexity, received his PhD from Ghent University in Belgium, after which he held post-doctoral fellowships at Porto University (Portugal), as well as at the University of Montpellier and University of Lorraine (both in France). He has worked at the HSE Faculty of Computer Science since September 2015. 

‘I experience Moscow in a very similar way as Belgium. We also have a culture of faithful pessimism. Of course, I’m impressed by the mathematical history and general level of mathematical skills of PhD students here in Moscow. I’m also impressed by the pedagogical talents of teachers at HSE. When I’m spying in the auditoria, I see there is often a lot of interaction between the teacher and the students, even when teaching abstract and complicated topics. In the Russian language lessons, there is loads of fun and laughing…’

Attila Kertesz-Farkas received his PhD at the University of Szeged (Hungary), after which he worked at the University of Maryland (USA) and later held post-doctoral fellowships at the University of Trieste (Italy) and the University of Washington (Seattle, USA). He has been at the HSE Faculty of Computer Science since September 2015.

‘Before coming here I was a postdoc at the University of Washington in Seattle and I spent lots of time on what I really want to do in my professional career. I had several opportunities in the U.S., but unfortunately none of them seemed the right one. Then I found this opportunity at HSE in Moscow, which gives me everything I was looking for in a good job: freedom in research, a `nice city and culture to live in, and close to my home (in Hungary). I cannot imagine a better job offer than I have here at HSE. My wife is also very happy about this opportunity, as she is Muscovite.

‘I am developing novel Machine Learning and Data Mining algorithms for real-life applications. Within this I have different projects; for instance, I am currently working on a new deep learning method for matching biomolecular data. Lately, I have become interested in analyzing human motion data captured via mobile phone sensors.’