Vadim

Vadim is a Doctor of Sciences in Physics and Mathematics, a professor at the Moscow Institute of Physics and Technology.

Fields of research

AI, Machine Learning and Data Analysis, Deep Learning
Functional and Geometric Learning, Physics-Informed learning
Behavioural Analysis and Brain-Computer Wearable Interfaces

Activities

Makes long-term planning of applied and theoretical research. Leads and runs research projects in the field of AI: states problems, connects researchers and programmers, delivers projects to implementation and publications

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Duties

2004–2022 Doctor of physico-mathematical sciences, Principal investigator at the Computing Center of the Russian Academy of Sciences
2010–2022 Professor, chief of department at the Moscow Institute of Physics and Technology
2019–2022 Chief scientist of the Laboratory of Machine Intelligence at MIPT
2006 Consultant on human behaviour analysis projects at Forecsys Ltd
2015-2022 Chair of the MS thesis committee at the Skolkovo Institute of Science and Technology
2015-2022 Chair of the BS thesis committees at the University Higher School of Economics
2011–2019 Editor in chief of the Journal of Machine Learning and Data Analysis

Teaching courses

Automation Research in Machine Learning – My First Scientific Paper: each year this course delivers over 30 supervised student projects and publications
Signal and Functional Data Analysis – Mathematical Methods of Forecasting
Machine learning and Data analysis}: in 2015 with colleagues obtained a grant from Coursera.org to create a MOOC specialization, eight consequent courses
2018–2022 Plans and runs five courses with his PhD alumni:
- Bayesian Model Selection,
- Generative Deep Learning Models,
- Bayesian Multi-modeling,
- Communications in Machine Learning Research,
- Fundamental Theorems of Machine Learning

Supervision of research activities

Alumni under scientific supervision: 32 BS, 28 MS, 16 PhD students. Now in his team 9 BS, 13 MS, 7 PhD students

PhD thesis, supervised and defended

now the students are working for Amazon, Yahoo, Meta, WorldQuant:

2014 Algebraic graph transformations for non-linear model generation
2015 Concordance of the partial ordered expert estimations
2017 Multi-model selection for classification problem
2017 Hierarchical topic modelling for short-text collections
2019 Multi-way feature selection for ECoG-based Brain-Computer Interface
2020 Bayesian model selection for deep learning neural network structures
2021 Dimensionality reduction for ECoG Brain-Computer Interface time series
2022 Expert learning and Bayesian multi-modelling

Scheduled

2023 Spatial-time series multiple alignment and clustering
2024 Continuous space-time differential models for Brain-Computer Interface

Organisational duties

Responsible for French Institute for Research in Computer Science and Automation INRIA-MIPT collaboration
Examiner of the PhD thesis committee at the Grenoble-Alpes University
Member of PhD thesis committee at the Russian Academy of Sciences, Computing Centre
Chair of the MS/PhD thesis committee at the Skolkovo Institute of Science and Technology
Chair of the BS thesis committees at the National Research University Higher School of Economics
Editor in chief of the Journal of Machine Learning and Data Analysis
Executive chair of the International Conference on Intelligent Data Processing]
Program committee member of the International Federation of Operational Research Societies

Visiting professor

2013 University of Siegen (Germany), delivers a course Data Analysis in Business Analytics
2014 Middle East Technical University (Turkey), delivers a course on Model Selection in Machine learning
2014 RWTH Aachen University (Germany), delivers a course on Preference Learning and Model Selection
2015 University of Grenoble, Computer Science Laboratory (France), participates in research projects, devoted to industrial time series forecasting
2019 National Institute of Automation and Informatics (France), plans and organizes scientific research projects in machine learning for bio-informatics

Education

Obtained D.Sc.(2014) and Ph.D.(2002) in Physics and Mathematics with theses on Mathematical Modelling and Machine Learning from Russian Academy of Sciences, Computing Center

Distinctions

Yandex Segalovich prize award in 2020 for his significant impact in the scientific community development in the CIS-countries. Series of grants from Foundation for Basic Research

Impact projects

The physical activity behaviour analysis': resulted in a set of algorithms for deployment in the wearable devices. Proceeded as a three joint start-up companies, which are successfully developing.
Multiway feature selection for ECoG-based Brain-Computer Interface resulted as a feature selection algorithms and a forecasting model to decode the human upper limb movement using the electrocorticogram
Rail-road time series forecasting for the county rail-roads resulted a set of the hierarchical time series forecasting algorithms to deploy to the freight planning
Creation the system of decision making for The Foundation for Basic Research
The theory of model generation and selection. The project resulted as a joint MS program. Laboratory of Machine Intelligence, MIPT and University Grenoble-Alpes
The theory of expert assessment concordance for decision making. The project was made for WWF and IUCN to rank protected areas, national parks and wilderness areas

Patents

Particle Detector} // European Patent Office, patent 06808733.7-1240 PCT/GB2006060369
Time series generation for railway freight models // Software program register, patent 2016617271
Model of railway freight volumes forecasting // Software program register, patent 2016617272

Skills

Scientific and applied research planing and executing, Experiment planning, Electronic devices developing: programmable microchips and printed circuit boards , Programming VHDL, Matlab, Mathematica, C++, Python, Editorial duties and publishing

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