Vasilii Gromov
- Deputy Head, Professor: Faculty of Computer Science / School of Data Analysis and Artificial Intelligence
- Senior Research Fellow: Faculty of Computer Science / International Laboratory for Intelligent Systems and Structural Analysis
- Vasilii Gromov has been at HSE University since 2018.
Education, Degrees and Academic Titles
Dnepropetrovsk State University
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.
Professional Interests
Awards and Accomplishments
Best Teacher — 2024, 2022
Winner of the HSE University Best Russian Research Paper Competition – 2023
Supervisor of the following Doctoral theses
- 1
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)
- 2Speciation and efficiency of genetic algorithms in solving complex optimization problems
- 3Bifurcation Analysis of Nonlinear Fokker-Planck Equations
- 4M. Sohrabi Speciation in Genetic Algorithms with Interplay Among Species
- 5Investigation of natural language structures in Spot the bot task
- 6B. Hendawi Spot the bot: statistical tests to distinguish texts written by human, and those generated by bots
Courses (2024/2025)
- Complex Systems Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 1, 2 module)Rus
- Mentor's Seminar (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Methods of Artificial Intelligence in Decision Making (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Methods of Artificial Intelligence in Decision Making (Mago-Lego; 3, 4 module)Eng
- Research Seminar "Data Analysis and Artificial Intelligence 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Research Seminar "Data Analysis and Artificial Intelligence" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Eng
- Research Seminar "Data Science in scientific" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Eng
- Research Seminar "Data analysis in complex systems" (Bachelor; 4 year, 1-3 module)Eng
- Past Courses
Courses (2023/2024)
- Complex Systems Theory (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, field of study Applied Mathematics and Information Science; 4 year, 1, 2 module)Rus
- How to Examine and Predict Time Series: Methods and Applications (Master’s programme; Faculty of Computer Science field of study Applied Mathematics and Informatics, field of study Applied Mathematics and Informatics; 2 year, 1, 2 module)Eng
- How to Examine and Predict Time Series: Methods and Applications (Mago-Lego; 1, 2 module)Eng
- Mentor's Seminar (Master’s programme; Faculty of Computer Science; 1 year, 1-4 module)Eng
- Modern Methods of Decision Making (Master’s programme; Faculty of Computer Science; 1 year, 3, 4 module)Eng
- Modern Methods of Decision Making (Mago-Lego; 3, 4 module)Eng
- Research Seminar "Data Analysis and Artificial Intelligence 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Research Seminar "Data Analysis and Artificial Intelligence" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Eng
- Research Seminar "Data Analysis in the Natural Sciences" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Research Seminar "Data Science in scientific" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Eng
Courses (2022/2023)
- Complex Systems Theory (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, field of study Applied Mathematics and Information Science; 4 year, 1, 2 module)Rus
- How to Examine and Predict Time Series: Methods and Applications (Mago-Lego; 1, 2 module)Rus
- How to Examine and Predict Time Series: Methods and Applications (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Rus
- Research Seminar "Data Analysis and Artificial Intelligence 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Research Seminar "Mathematical and Computational Engineering in Science and Business 1" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Eng
- Research Seminar "Mathematical and Computational Engineering in Science and Business 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
Courses (2021/2022)
- Complex Systems Theory (Bachelor’s programme; Faculty of Computer Science field of study Applied Mathematics and Information Science, field of study Applied Mathematics and Information Science; 4 year, 1, 2 module)Rus
- How to Examine and Predict Time Series: Methods and Applications (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Rus
- Research Seminar "Data Analysis and Artificial Intelligence 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Research Seminar "Mathematical and Computational Engineering in Science and Business 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Eng
- Research Seminar "Mathematical and Computational Engineering in Science and Business" (Bachelor’s programme; Faculty of Computer Science; 3 year, 1-4 module)Eng
- Self-Organizing Systems Theory (Bachelor’s programme; Faculty of Computer Science; 4 year, 3 module)Rus
Courses (2020/2021)
- Evolutionary Algorithms and Real-world Logistics (Bachelor’s programme; Graduate School of Business; 4 year, 1, 2 module)Rus
- How to Examine and Predict Time Series: Methods and Applications (Master’s programme; Faculty of Computer Science; 2 year, 1, 2 module)Rus
- Research Seminar "Data Analysis and Artificial Intelligence 2" (Bachelor’s programme; Faculty of Computer Science; 4 year, 1-3 module)Rus
Conferences
- 2020
Modeling and Analysis of Complex Systems and Processes MACSPro'2020 (Венеция). Presentation: Prediction after a Horizon of Predictability
- 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
International Conference on Software Testing, Machine Learning and Complex Process Analysis (TMPA-2019) (Тбилиси). Presentation: Chaotic Time Series Prediction: Run for the Horizon
- 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
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.
‘Bots Are Simply Imitators, not Artists’: How to Distinguish Artificial Intellect from a Real Author
Today, text bots like ChatGPT are doing many tasks that were originally human work. In our place, they can rewrite ‘War and Peace’ in a Shakespearean style, write a thesis on Ancient Mesopotamia, or create a Valentine’s Day card. But is there any way to identify an AI-generated text and distinguish it from works done by a human being? Can we catch out a robot? The Deputy Head of the HSE School of Data Analysis and Artificial Intelligence, Professor of the HSE Faculty of Computer Science Vasilii Gromov explained the answer in his lecture ‘Catch out a Bot, or the Large-Scale Structure of Natural Intelligence’ for Znanie intellectual society.
New Technologies for Preserving Brain Functions: ‘Not Magic, but Normal Engineering’
New methods of brain mapping will make it easier to identify the cortex areas responsible for speech functions and to perform operations on the brain, as well as reduce the likelihood of damage to important areas. In addition, this will allow for more frequent use of non-invasive methods for restoring speech and other functions lost due to injuries and illnesses.
‘Working in Academia Is My Lifelong Desire’
Majid Sohrabi is a 28 year-old student from Iran currently enrolled in a doctoral programme at the HSE University Faculty of Computer Science. Before starting his PhD, he graduated with honours from the university’s Master of Data Science programme. In addition to studying, he also works as an assistant at the School of Data Analysis and Artificial Intelligence and a research assistant at the Laboratory for Models and Methods of Computational Pragmatics.
Mathematicians and Practicing Surgeons to Fight Venous Diseases
One million people in Russia suffer from venous diseases. The ‘Intelligent data analysis for healthcare information systems’ Mirror Lab project brings together expertise in mathematics and medicine in order to better diagnose various conditions in phlebology. Project leader Vasilii Gromov talked to The HSE LooK about its achievements and prospects.
Ilya Segalovich Scholarship Winners Interviews. Part 1
The winners of the Ilya Segalovich Scholarship were announced recently. We talked to them about the award, their studies and their projects.