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Address: 11 Pokrovsky Bulvar, Pokrovka Complex, room S939
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ORCID: 0000-0001-5891-6597
ResearcherID: M-6614-2015
Scopus AuthorID: 35228959300
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S. Kuznetsov
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Vasilii Gromov

  • Vasilii Gromov has been at HSE University since 2018.

Education, Degrees and Academic Titles

  • 2018
  • 2017

    Doctor of Sciences*
    Oles Honchar Dnipro National University

  • 2000

    Master's in Applied Mathematics
    Dnepropetrovsk State University

* Doctor of Sciences
A post-doctoral degree called Doctor of Sciences is given to reflect second advanced research qualifications or higher doctorates in ISCED 2011.

Continuing education / Professional retraining / Internships / Study abroad experience

The Centre for Modern State Development. Course of futurology seminars Russia and the World under Technological Transformation: Strategic Vision (in the framework of Presidental grant Modern popular pilot futurology course "Trends 2.0"). Graduated with honours. 2019

Stanford-online. Online course Writing in the Science. 2015. 

Student Term / Thesis Papers

  • Master degree theses:


    Speciation for evolutionary programming algorithms


    Relational tensors as a way to represent information about a chaotic time series

    Constructive neural networks to explore chaotic systems

    Predictive clustering algorithms to multi-step ahead chaotic time series prediction

    Prediction of abrupt trend breaks

    Estimated invariant measure for dynamical system given by an observed time series


    Similar time series in chaotic time series problems

    Natural languages statistical investigations with the employment of self-organized criticality methods


    Clustering techniques to predict chaotic time series

    Predictive clustering to identify in advance popular tweets


    NEAT neural models to predict chaotic time series


    Damaged mechanical systems identification using constructive neural networks


    Bachelor theses:


    Characteristics of invariant measure to predict time series

    Constructive neural networks to predict neural networks

    Multi-step ahead time series prediction

    Identification of coordinated atacks in Tweeter

    Speciation in the vehicle routing problem


    Statistical characteristics of literary texts corpus

    Dynamics of texts in finite-dimensional semantic space (for English language corpus)

    Statistical characteristics of emotion switches in English texts


    Self-organized criticality methods for natural selection in genetic algorithms

    Natural language co-occurence graphs as complex networks

    Estimated prediction quality of clusters for chaotic time series prediction


    Non-linear boundary problem and Kolmogorov superposition theorem


    Evolutionary algorithms for time series prediction








  • Bachelor
  • S. Rybin «Complex Networks: Graph of Connections and Data Graph». Faculty of Computer Science, 2019

  • Master
  • A. Gaisin «Clustering of Distinctive Sequences of Semantic Trajectories». Faculty of Computer Science, 2019

  • N. Bondartcev «Evolutionary Algorithms for the Large-scale Business Tourist Problem». Faculty of Computer Science, 2019

  • V. Ladenkov «The Generation of Typical Stock-Market Figures for a Set of Time Series». Faculty of Computer Science, 2019

  • R. Britkov «How to Identify Bots in Social Media: Motifs in Semantic Spaces». Faculty of Computer Science, 2019

  • A. Vorontsov «Financial Time Series: Multi-step Ahead Prediction». Faculty of Computer Science, 2019

Academic Supervision

for a degree of Candidate of Science

Anastasia V. Kabeshova (2015, co-supervision with Prof. Olivier Beauchet, geriatrist), University of Angers (France). Title: Prediction of fallings for aged persons: advantages of nonlinear models (Predire la chute de la personne agee: apports des modeles mathematiques non-lineaires)

Courses (2019/2020)

Courses (2018/2019)



  • 2019

    МЕЖДУНАРОДНАЯ НАУЧНАЯ КОНФЕРЕНЦИЯ «СОВРЕМЕННЫЕ ПРОБЛЕМЫ МАТЕМАТИКИ И МЕХАНИКИ», ПОСВЯЩЕННАЯ 80-ЛЕТИЮ АКАДЕМИКА В.А. САДОВНИЧЕГО 13-15 МАЯ 2019 Г. (Москва). Presentation: Предсказание потери устойчивости цилиндрической оболочки: прямые и обратные задачи теории бифуркаций для уравнений Кармана

  • 4-й Колмогоровский семинар по компьютерной лингвистике и наукам о языке (Москва). Presentation: SEMANTIC AND EMOTIONAL PATHS OF A LITERARY WORK AND ITS TRANSLATIONS

  • 2018

    14-th International Conference “Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering TCSET” (Славское). Presentation: Inverse Bifurcation Problem for von Karman-type Elliptic Equations

  • International Conference “Ukrainian Conference on Applied Mathematics” (Львов). Presentation: The extended Kantorovich method for von Karman equations

  • 2016

    5-th International conference “Nonlinear Dynamics” (Харьков). Presentation: Inverse bifurcation problem as a tool for rapid identification of progressive collapse for thin-walled systems

  • 2014

    EURO Working Group on Vehicle Routing and Logistics Optimization (VEROLOG-2014) (Осло). Presentation: A Decision Support System for the Management of Petroleum Distribution

  • 2012

    11-th International Conference “Modern Problems of Radio Engineering, Telecommunications and Computer Science TCSET'2012” (Славское). Presentation: Decision-making support system for light petroleum products traffic and transport management

  • 2008

    Международный семинар “Актуальные проблемы нелинейной механики оболочек”. Presentation: Численный анализ ветвления нелинейных краевых задач теории тонкостенных систем

Employment history

Associate professor of School of Data Analysis and Artificial Intelligence, National Research University Higher School of Economics (2108-present).

Seniour researcher of Center for Reliability and Sustainability of Structures (Dnepropetrovsk National University, 2007-2018), research officer of the same center (2000-2007).

Associate professor of Computational Mathematics and Mathematical Cybernetics Department (2006-2018); assistant professor (the same department, 2002-2006).

Visiting positions:

         Visiting professor of Universite du Maine (Faculty of Science and Technologies, May 2011).

Visiting lecturer of Universite du Maine (Engineering Higher School, November 2011). I deliver lectures on Data Mining.


I deliver (or delivered) lectures on:


For Masters in Data Mining

- Time series forecasting with applications

- Probability and statistics

- Bio-inspired algorithms and real-world logistics


For Masters in AI and System Analysis:

- Non-linear time series forecasting;

- Theory of self-organizing systems;

- Theory of statistical complexity;

- Catastrophe theory;

- Foresighting;

- Complex Networks;

- Deep learning;


For Bachelors in System Analysis:

- Statistical forecasting of economical process;

- Neural networks.

- Data Mining;

- Qualitative theory of ordinary differential equations;

- Theory of complex systems;

- Design patterns;

- Object-oriented programming.

I took part in the development of bachelor’s, master’s, and PhD programmes (both concepts and curricula) in decision-making support systems (artificial intelligence) and system analysis. 

Timetable for today

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