Difference between revisions of "Vadim"

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* [https://orcid.org/0000-0002-2194-8859 ORCID]
 
* [https://orcid.org/0000-0002-2194-8859 ORCID]
 
* [http://strijov.com/papers_en.html List of papers]
 
* [http://strijov.com/papers_en.html List of papers]
 +
* [https://www.linkedin.com/in/v1s/ linkedin.com/in/v1s]
 +
* [mailto://vadim.vct@gmail.com vadim.vct@gmail.com]
  
−
[[Vadim: CV]]
+
==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
 +
 
 +
%\includegraphics[width=5cm]{str200.jpg}
 +
%\end{tabular}
 +
 
 +
==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
 +
* [http://jmlda.org/ Editor in chief] of the Journal of Machine Learning and Data Analysis
 +
* [http://mmro.ru/en/ Executive chair] of the International Conference on Intelligent Data Processing]
 +
* Program committee member of the International Federation of Operational Research Societies
 +
<!--
 +
% Guest editor of the Machine Learning Journal, Springer
 +
%Editorial board member in journals Factory Laboratory and Material Diagnostics
 +
%Reviewer in Elsevier journals
 +
%Visiting professor: Siegen University, Middle East Technical University, Université Grenoble Alpes, Laboratoire d'Informatique de Grenoble-->
 +
 
 +
==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. <!--Forecsys (15 researchers)-->
 +
* ''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 <!-- Computing Centre of Russian Academy of Sciences (7 researchers)-->
 +
<!-- joint team from Forecsys  MIPT (5 researchers)-->
 +
* ''Creation the system of decision making'' for The Foundation for Basic Research <!-- 10 researches form MIPT-->
 +
* ''The theory of model generation and selection''. The project resulted as a  joint MS program. Laboratory of Machine Intelligence, MIPT and University Grenoble­-Alpes<!--%, MSIAM (6 researchers)-->
 +
* ''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
 +
 
 +
==Selected publications==
 +
 
 +
<!--
 +
==Achievements of impact==
 +
* Plans 600 projects in ML, the most part were successfully implemented
 +
* Competence to create a number of small research groups, which reach a given goal during limited amount of time
 +
* Used to plan a project “from goal to start, given resources”, not “as it goes”
 +
-->

Revision as of 20:40, 28 September 2022

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

%\includegraphics[width=5cm]{str200.jpg} %\end{tabular}

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

Selected publications

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