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SPIN-RSCI: 4339-7570
ORCID: 0000-0001-6863-9028
ResearcherID: H-4870-2015
Scopus AuthorID: 8382687000
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V. V. Podolskii
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Dmitry Vetrov

  • Dmitry Vetrov has been at HSE since 2014.

Education and Degrees

  • 2007

    Candidate of Sciences* (PhD) in Discrete Mathematics and Mathematical Cybernetics
    Lomonosov Moscow State University
    Thesis Title: The relation of accuracy and stability of the classification algorithms

  • 2003

    Lomonosov Moscow State University

* 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 (2017/2018)

Courses (2016/2017)

Courses (2015/2016)

Courses (2014/2015)


Timetable for today

Full timetable

Machines Can See: International Summit on Computer Vision

On June 9, a summit was held on computer vision and deep learning ‘Machines can see’, organized by Sistema VC, Visionlabs, and the Strelka Institute. Dmitry Vetrov and Anton Konushin, staff members of HSE Faculty of Computer Science, were among the organizers of and speakers at the conference.

'Machine Learning Algorithm Able to Find Data Patterns a Human Could Not'

In December 2016, five new international laboratories opened up at the Higher School of Economics, one of which was the International Laboratory of Deep Learning and Bayesian Methods. This lab focuses on combined neural Bayesian models that bring together two of the most successful paradigms in modern-day machine learning – the neural network paradigm and the Bayesian paradigm.

Variational dropout sparsifies DNNs paper has been accepted to ICML'17

The paper authored by laboratory's research assistants Dmitry Molchanov and Arsenii Ashukha and head Dmitry Vetrov has been accepted to the International Conference on Machine Learning'2017. In this research a state-of-the-art result in deep neural networks sparsification was achieved using Bayesian framework applied to deep learning.

Collaboration with Samsung Opens New Perspectives for the Laboratory and the Faculty

Dmitry Vetrov, head of the laboratory, held a meeting with Mr. Shi-Hwa Lee, a Vice-President of Samsung, a company the laboratory collaborates with. Interim research results, internship possibilities and collaboration perspectives were discussed.

New International Laboratories Opening up at HSE

On December 23, 2016, the HSE Academic Council approved the creation of four new laboratories: the International Laboratory for the Study of Russian and European Intellectual Dialogue, the International Laboratory for Population and Health Studies, the International Laboratory of Deep Learning and Bayesian Methods, and the International Laboratory for Supercomputer Atomistic Modelling and Multi-scale Analysis.

‘Our Programme Aims to Make a Research Breakthrough at the Intersection of Mathematics and Computer Science’

In 2017, the HSE Faculty of Computer Science and Skoltech are opening admissions to the Master’s programme inStatistical Learning Theory, which will become the successor to theMathematical Methods of Optimization and Stochastics programme.Vladimir Spokoiny, the programme’s academic supervisor and professor of mathematics at Humboldt University in Berlin, told us about the research part of the new programme and the opportunities it offers to both Master’s students and undergraduate students alike.

Big Data: Prospects for Russian-French Cooperation in Science and Technology

Participants of the ‘Big Data Applications’ research workshop, which took place in the beginning of December, discussed big data and prospects for Russian-French cooperation in this area. The workshop, held at HSE, brought together about 50 participants from leading research centres, universities, governmental bodies and IT companies in both Russia and France.

Tensorizing Deep Neural Networks

The article ‘Tensorizing Neural Networks’, prepared by the Bayesian Methods Research Group under the supervision of Associate Professor of HSE’s Computer Science Faculty Dmitry Vetrov, has been accepted by the NIPS conference – the largest global forum on cognitive research, artificial intelligence, and machine learning, rated A* by the international CORE ranking. This year it is being held December 7-12 in Montreal. Here Dmitry Vetrov talks about the research he presented and about why delivering reports at conferences is better than getting published in the academic press.

Two Papers by Dmitry Vetrov Accepted at NIPS Conference

The Twenty-ninth Annual Conference on Neural Information Processing Systems (NIPS) is a single-track machine learning and computational neuroscience conference that includes invited talks, demonstrations and oral and poster presentations of refereed papers. All of the key breakthroughs in machine learning over the last 15 years were first presented at this conference. The conference is assigned to the highest category (A*) in the CORE Conference Ranking.

Reports by Ekateina Lobacheva and Dmitry Vetrov Accepted at ICCV 2015

The reports be Ekateina Lobacheva, doctoral student, and Dmitry Vetrov, Associate Professor of the Department Dmitry Vetrov, Associate Professor at the Big Data and Information Retrieval School were accepted the organisers of the International Conference on Computer Vision, which got the highest rank A* according to the international rating of IT conferences.