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English
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+7(495) 772-9590
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Address: Moscow, Kochnovsky, 3, 520
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SPIN-RSCI: 2982-7110
ORCID: 0000-0001-7865-2357
ResearcherID: K-7189-2013
Scopus AuthorID: 55803484600
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Supervisor
I. Arzhantsev
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Andrey Ustyuzhanin

  • Andrey Ustyuzhanin has been at HSE since 2015.

Education and Degrees

  • 2007

    Candidate of Sciences* (PhD)

  • 2000

    Master
    Moscow Institute of Physics and Technology

  • 1998

    Bachelor
    Moscow Institute of Physics and Technology

* Candidate of Sciences
According to the International Standard Classification of Education (ISCED) 2011, Candidate of Sciences belongs to ISCED level 8 - "doctoral or equivalent", together with PhD, DPhil, D.Lit, D.Sc, LL.D, Doctorate or similar. Candidate of Sciences allows its holders to reach the level of the Associate Professor.

Student Term / Thesis Papers

Full list of of student term / thesis papers

Courses (2018/2019)

Courses (2017/2018)

Publications53


Conferences

2015
21th International Conference on Computing in High Energy and Nuclear Physics (CHEP-2015) (Окинава). Presentation: Agile Research - Strengthening Reproducibility in Collaborative Data Analysis Projects

Timetable for today

Full timetable

HSE Becomes LHCb Associate Member at CERN

The Higher School of Economics has joined the LHCb collaboration at the Large Hadron Collider, which is operated by the European Organization for Nuclear Research. The group from HSE will consist of researchers from the Laboratory of Methods for Big Data Analysis (LAMBDA). This will give HSE researchers full access to data from the collaboration and allow the university to participate in various projects.

HSE and University of London: Joint BA Programme in Applied Data Analysis

In 2018, the Higher School of Economics will launch an English-taught double degree programme in partnership with the University of London in Applied Data Analysis. Graduates will be awarded an undergraduate degree from HSE in Applied Mathematics and Information Science and a Bachelor of Science in Data Science and Business Analytics from the University of London. International applicants are invited to apply online starting November 15, 2017.

Third Machine Learning Summer School Held in UK

On July 17-23 the Third Machine Learning summer school organized by Yandex School of Data Analysis, Laboratory of Methods for Big Data Analysis at the National Research University Higher School of Economics and Imperial College London was held in Reading, UK. 60 students, doctoral students and researchers from 18 countries and 47 universities took part in the event.

HSE and Yandex Hold Second Summer School in Machine Learning in High Energy Physics

On June 20-27, the HSE Faculty of Computer Science teamed up with the Yandex School of Data Analysis to carry out the Second International Summer School in Machine Learning in High Energy Physics. This year’s Summer School took place in Lund, Sweden, and saw the participation of 60 students and researchers from Austria, Great Britain, Germany, Italy, Russia, the U.S., Sweden, Switzerland, and more. Of these students, five came from the Higher School of Economics.

How Programmers Help Unravel the Secrets of Physics

The Summer School on Machine Learning in High Energy Physics, which was co-organised by the HSE Faculty of Computer Science and Russian internet company Yandex, has ended. Below, the Head of HSE's Laboratory of Methods for Big Data Analysis, Andrey Ustyuzhanin, talks about the various ways in which physicists and programmers cooperate. He also discusses how researchers from HSE and Yandex have been participating in CERN experiments and how ordinary smartphone users can help unravel the secrets of the universe.

HSE, Yandex and CERN Researchers Work Together on Machine Learning in High Energy Physics

On August 30, 2015, the Summer School on Machine Learning in High Energy Physics wrapped up this year’s session. The school, which was held at the St. Petersburg Academic University, was organized by HSE in cooperation with the Yandex School of Data Analysis (SDA) and the Yandex Data Factory (YDF). This school is continuing cooperation between Yandex and CERN, which involves YDF and SDA researchers working together with experimental physicists on solving current problems in the field of physics. Many tasks require using machine learning approaches, which allow for greater accuracy and efficiency in these studies.