Andrey Dmitriev
- Professor:Graduate School of Business / Department of Business Informatics
- Leading Research Fellow:Faculty of Computer Science / Big Data and Information Retrieval School / Laboratory of Complex Systems Modeling and Control
- Andrey Dmitriev has been at HSE University since 2013.
Education and Degrees
- 2009
Doctor of Sciences* in Biophysics
Lomonosov Moscow State University - 2003
Candidate of Sciences* (PhD) in Biophysics
- 2000
Candidate of Sciences* (PhD) in Physical Chemistry
- 1998
Degree
Lipetsk State Teacher Training Institute
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.
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
- Analysis for Business Systems
an online non-credit course authorized by University of Minnesota and offered through Coursera, 04/28/2019
- Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure
an online non-credit course authorized by University of Illinois at Urbana-Champaign and offered through Coursera, 06/29/2018
- Practical Machine Learning
an online non-credit course authorized by Johns Hopkins University and offered through Coursera, 09/25/2018
- Введение в машинное обучение
онлайн-курс, одобренный ВУЗом Higher School of Economics и предлагаемый на Coursera, 14.06.2017
Student Term / Thesis Papers
- Bachelor
A. Pershin, Video Games Development and Selling During the Coronavirus Crisis. Graduate School of Business, 2021
Y. Sanochkin, Machine Learning Concepts in the E-Commerce Sphere. Graduate School of Business, 2021
M. Volpe, Identification of Micropost Streams on Twitter Related to Protest Movements. Graduate School of Business, 2020
G. Soghoyan, Implementation of Nonlinear Stochastic Dynamic Systems Theory for the Analysis of Brain Signals in Cases of BCI Algorithms Development. Graduate School of Business, 2019
V. Zaspenko, Recurrence Quantification Analysis Technique for Detecting an Extremal Events. Graduate School of Business, 2019
M. Merkushina, Study of Stock Prices Dynamics through Twitter Time Series Analysis. Graduate School of Business, 2019
V. Godunova, The Application of Current Complexity Theory to the Study of the Evolution of Social Networks. Graduate School of Business, 2018
A. Somov, Twitter as a Nonlinear Dynamical System. Graduate School of Business, 2018
O. Yaropolov, Credit Risk Prediction with Merton Model Based on Nonlinear SDE. Graduate School of Business, 2018
M. Ostroukhov, Optimization of Pathology Diagnosis Business Process by Applying Chaos Theory and Fractal Analysis to EEG-signal Processing. Graduate School of Business, 2018
B. Mysiv, Qualitative Characteristics of the Low-dimensional Chaos from Financial Time Series. Graduate School of Business, 2017
A. Apostolov, Determination of the Bifurcation Point of Dynamical System for Empirical Financial Series with Noise. Graduate School of Business, 2017
V. Dmitriev, Investigation into the Regular and Chaotic States of Twitter as a Dissipative System. Graduate School of Business, 2017
D. Shumilin, Nonlinear Differential and System Dynamics of the Interacting Companies. Graduate School of Business, 2017
E. Sitnikov, Optimization of the Selection of CRM Systems for Customers. Graduate School of Business, 2017
R. Khosnetdinov, Correlating Financial Time Series with Micro-blogging Activity. Graduate School of Business, 2017
M. Udalov, Financial Time Series Forecasting with Neural Networks. Graduate School of Business, 2017
- Master
A. Archa, Recurrence Quantification Analysis for Detecting Financial Volatility. Graduate School of Business, 2019
D. Shumilin, Recurrence Quantification Analysis Technique for Detecting an Extremal Events on Social Networks. Graduate School of Business, 2019
P. Kirgintseva, Processing of Large Financial Series During the Management of Immediate and Short-Term Liquidity by the Example of the Bank’s Foreign Currency Position. Graduate School of Business, 2016
A. Akireikin, Deterministic Variable in Big Chaotic Financial Series. Graduate School of Business, 2016
V. Silchev, Discovery of Dramatic Changes in Characteristics of Financial Data Streams. Graduate School of Business, 2016
A. Filipyev, Implementation of Machine Learning Methods into Cloud Systems. Graduate School of Business, 2016
D. Shostko, Big Data Orchestration from Logical to Physical Level. Graduate School of Business, 2016
A. Barskov, Assessing an impact of continuous monitoring on the effectiveness of FMCG Company’s control environment. Faculty of Business Informatics, 2014
Courses (2021/2022)
- Analysis and Forecasting of Heterogeneous Time Series (Bachelor’s programme; Graduate School of Business; 4 year, 3 module)Rus
- Mathematical modeling of complex systems (Bachelor’s programme; Graduate School of Business; 4 year, 1 module)Rus
- Quantitative Methods for Management Decisions (Bachelor’s programme; Graduate School of Business; 3 year, 4 module)Rus
- Statistics and Data Analisys (Master’s programme; Graduate School of Business; 1 year, 2 module)Rus
- Past Courses
Courses (2020/2021)
- Neural Networks and Deep Learning (Bachelor’s programme; Graduate School of Business; 4 year, 2 module)Eng
- Probabilistic and Statistical Management Models (Bachelor’s programme; Graduate School of Business; 2 year, 2, 3 module)Rus
Courses (2019/2020)
- Analysis and Forecasting of Heterogeneous Time Series (Bachelor’s programme; Graduate School of Business; 3 year, 3, 4 module)Rus
- Modeling of Processes and Systems (Bachelor’s programme; Graduate School of Business; 4 year, 1, 2 module)Rus
Courses (2018/2019)
Conferences
- 2021
14th Chaotic Modeling and Simulation International Conference (CHAOS 2021) (Афины). Presentation: Detection of Early Warning Signals for Self-Organized Criticality in Cellular Automata
- 202010th International Conference on Applied Physics and Mathematics (Токио). Presentation: A new spectrum of complexity exponents
- Modeling and Analysis of Complex Systems and Processes (MACSPro’2020) (Венеция). Presentation: Twitter Critical Phases Identification Based on Time Series of Microposts Analysis
- 20199th International Conference on Applied Physics and Mathematics (Бангкок). Presentation: Nonlinear random dynamical model for the stock market
- 9th International Conference on Applied Physics and Mathematics (Бангкок). Presentation: Optimization of pathology diagnosis by applying chaos theory and fractal analysis to EEG-signal processing
- 8th International Conference on Complex Networks and their Applications (Лиссабон). Presentation: Three-Parameter Kinetics of Self-organized Criticality on Twitter
- 2018
7th International Conference on Complex Networks and Their Applications (Кембридж). Presentation: Theoretical Study of Self-organized Phase Transitions in Microblogging Social Networks
- 2017International work-conference on time series (ITISE 2017) (Гранада). Presentation: Nonlinear Dynamical Analysis of Twitter Time Series
- 2nd International Conference on: Applied Physics, System Science and Computers (Дубровник). Presentation: A Simple Econophysics Model of the Stock Market as a Nonequilibrium Open System
6th International Conference on Complex Networks and Their Applications (Лион). Presentation: A Nonlinear Dynamical Approach to the Interpretation of Microblogging Network Complexity
- 5th International Conference on Information Technology and Quantitative Management (Нью-Дели). Presentation: The Application of Stochastic Bifurcation Theory to the Early Detection of Economic Bubbles
- 5th International Conference on Information Technology and Quantitative Management (Нью-Дели). Presentation: Modeling of Microblogging Social Networks: Dynamical System vs. Random Dynamical System
- 2016Global Conference on Applied Physics and Mathematics (Рим). Presentation: Using singularity points in financial time series for identification of economic downfall
- 18th IEEE Conference on Business Informatics (Париж). Presentation: Network Evolution Modeling under Conditions of Change in the Data Exchange Rate
- 4th International Conference on Complex Dynamical Systems in Life Sciences: Modeling and Analysis (4thICCDS’2016) (Агадир). Presentation: Investigation into the regular and chaotic states of Twitter
- 20152nd International Conference on Advances in Management, Economics and Social Science (Рим). Presentation: The Nonlinear Differential Dynamics of Interdependent Branches of Industry
- 12th International Scientific Conference "European Financial Systems" (Брно). Presentation: Application of the Nonlinear Oscillations Theory to the Study of Non-equilibrium Financial Market
- Third International Conference on Information Technology and Quantitative Management (Рио де Жанейро). Presentation: Double Layer Interval Graph Model: The Universal Tool for Data Driven Market Analysis and Forecasting
- 2014Performance Management: Designing the Hich-Performing Organization (Aarhus). Presentation: Dynamic system crisis’s detecting using big data flow
- Большие Данные в национальной экономике (Москва). Presentation: Предсказательная аналитика на основе потоков Больших Данных
- Global Interdisciplinary Dusiness-Economics Advancement Conference (GIBA) (Clearwater Beach, Florida, USA). Presentation: Crisis Forecasting in Ask and Bid Prices Formation Systems in Case of Precious Metals
20211
20202
- Chapter Dmitriev V., Dmitriev A., Maltseva S. V., Balybin S. Three-Parameter Kinetics of Self-organized Criticality on Twitter, in: Studies in Computational Intelligence (Complex Networks and Their Applications VIII) Vol. 881: Complex Networks and Their Applications VIII. Part 2. Springer, 2020. doi Ch. 881. P. 556-565. doi
- Chapter Dmitriev A., Dmitriev V., Balybin S. Twitter Critical Phases Identification Based on Time Series of Microposts Analysis, in: Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2020 (MACSPro 2020) / Ed. by Alexander Shapoval, V. Popov, I. Makarov. Vol. 2795. CEUR Workshop Proceedings, 2020. Ch. 2795. P. 140-145.
20195
- Chapter Dmitriev A., Silchev V., Dmitriev V. A Simple Econophysics Model of the Stock Market as a Nonequilibrium Open System, in: Lecture Notes in Electrical Engineering Vol. 489: Applied Physics, System Science and Computers II. Springer, 2019. doi P. 237-243. doi
- Chapter Dmitriev A., Kornilov V. Nonlinear random dynamical model for the stock market, in: Journal of Physics: Conference Series Vol. 1298. Issue 1. United Kingdom: Institute of Physics Publishing (IOP), 2019. P. 012009-1-012009-5. doi
- Chapter Kornilov V., Остроухов М. Н., Dmitriev A. Optimization of pathology diagnosis by applying chaos theory and fractal analysis to EEG-signal processing, in: Journal of Physics: Conference Series Vol. 1298. Issue 1. United Kingdom: Institute of Physics Publishing (IOP), 2019. Ch. 1298. P. 012015-1-012015-6. doi
- Article Dmitriev A., Dmitriev V., Balybin S. Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results // Complexity. 2019. Vol. 2019. No. Article ID 8750643. P. 1-16. doi
- Chapter Dmitriev A., Maltseva S. V., Tsukanova O. A., Dmitriev V. Theoretical Study of Self-organized Phase Transitions in Microblogging Social Networks, in: Studies in Computational Intelligence Vol. 813: Complex Networks and Their Applications VII. Part 2. Springer, 2019. doi P. 236-245. doi
20183
- Chapter Dmitriev A., Dmitriev V., Tsukanova O. A., Maltseva S. V. A Nonlinear Dynamical Approach to the Interpretation of Microblogging Network Complexity, in: Studies in Computational Intelligence Vol. 689: Complex Networks & Their Applications VI. Springer, 2018. doi P. 390-400. doi
- Article Dmitriev A., Kornilov V., Maltseva S. V. Complexity of a microblogging social network in the framework of modern nonlinear science // Complexity. 2018. Vol. 2018. No. Article ID 4732491. P. 1-11. doi
- Article Dmitriev V., Dmitriev A. Investigation into the Regular and Chaotic States of Twitter // Discontinuity, Nonlinearity, and Complexity. 2018. Vol. 7. No. 4. P. 403-411. doi
20174
- Article Твердислов В. А., Dmitriev A., Sidorova A. Active Media as a Physical Model of Spatiotemporal Self-Organization in the Stock Market // Bulletin of the Russian Academy of Sciences: Physics. 2017. Vol. 81. No. 1. P. 114-120. doi
- Chapter Dmitriev A., Tsukanova O. A., Maltseva S. V. Modeling of Microblogging Social Networks: Dynamical System vs. Random Dynamical System, in: Procedia Computer Science Vol. 122: 5th International Conference on Information Technology and Quantitative Management. Elsevier, 2017. doi P. 812-819. doi
- Chapter Dmitriev A., Silchev V., Dmitriev V., Maltseva S. V. Nonlinear Dynamical Analysis of Twitter Time Series, in: Proceedings of International Work-Conference on Time Series (ITISE 2017) Vol. 2. Granada : Godel Impresiones Digitales S.L., 2017. Ch. 2. P. 1219-1230.
- Chapter Dmitriev A., Dmitriev V., Сагайдак О. И., Tsukanova O. A. The Application of Stochastic Bifurcation Theory to the Early Detection of Economic Bubbles, in: Procedia Computer Science Vol. 122: 5th International Conference on Information Technology and Quantitative Management. Elsevier, 2017. doi P. 354-361. doi
20163
- Article Markov N., Dmitriev V., Maltseva S. V., Dmitriev A. Application of the Nonlinear Oscillations Theory to the Study of Non-equilibrium Financial Market // Financial Assets and Investing. 2016. Vol. 7. No. 3. P. 5-19. doi
- Chapter Dmitriev A., Tsukanova O. A., Maltseva S. V. Investigation into the Regular and Chaotic States of Microblogging Networks as Applied to Social Media Monitoring, in: IEEE 13th International Conference on e-Business Engineering. IEEE, 2016. P. 293-298. doi
- Chapter Tsukanova O. A., Dmitriev A., Maltseva S. V. Network Evolution Modeling under Conditions of Change in the Data Exchange Rate, in: IEEE 18th Conference on Business Informatics Vol. 2: Short and Workshop Papers. IEEE, 2016. P. 68-71. doi
20155
- Chapter Markov N., Dmitriev V., Maltseva S. V., Dmitriev A. Application of the Nonlinear Oscillations Theory to the Study of Non-equilibrium Financial Market, in: European Financial Systems 2015. Proceedings of the 12th International Scientific Conference. Brno : Masarykova univerzita, 2015. P. 375-381.
- Article Markov N., Dmitriev A., Maltseva S. V. Double Layer Interval Graph Model: The Universal Tool for Data Driven Market Analysis and Forecasting // Procedia Computer Science. 2015. Vol. 55. P. 1165-1173. doi
- Chapter Markov N., Dmitriev A., Maltseva S. V. Double layer interval graph model: The universal tool for data driven market analysis and forecasting, in: Procedia Computer Science. 3rd International Conference on Information Technology and Quantitative Management, ITQM 2015 Vol. Volume 55. Amsterdam : Elsevier, 2015. P. 1165-1173.
- Article Dmitriev V., Dmitriev A., Maltseva S. V. The Nonlinear Differential Dynamics of Interdependent Branches of Industry // International Journal of Business and Management Study. 2015. Vol. 2. No. 2. P. 113-117.
- Chapter Dmitriev V., Maltseva S. V., Dmitriev A. The Nonlinear Differential Dynamics of Interdependent Branches of Industry, in: Proceedings of 2nd International Conference on Advances in Management, Economics and Social Science. NY : Institute of Research engineers and Doctors, 2015. P. 34-38. doi
20143
- Chapter Dmitriev A., Maltseva S. V., Markov N. Crisis Forecasting in Ask and Bid Prices Formation Systems in Case of Precious Metals, in: Global Interdisciplinary Business-Economics Advancement Conference. Conference Proceeding. Sarasota : University of South Florida Sarasota-Manatee, 2014. P. 11-18.
- Chapter Dmitriev A., Maltseva S. V., Markov N. Crisis Forecasting in Ask and Bid Prices Formation Systems in Case of Precious Metals, in: Global Interdisciplinary Business-Economics Advancement Conference. Conference Proceeding. Sarasota : University of South Florida Sarasota-Manatee, 2014. Ch. 1. P. 11-18.
- Chapter Maltseva S. V., Dmitriev A. Dynamic system crisis’s detecting using big data flow, in: Performance Management: Designing the High-Performing Organization. Conference Proceding. Aarhus : Aarhus University, 2014. P. 192-201.
20063
- Article Dmitriev A., Tverdislov V. A., Isaev P. P. Effect of isomerization of amino acid residues on the structure of aquaporin // Journal of Structural Chemistry. 2006. Vol. 47. No. 3. P. 567-569.
- Article Dmitriev A., Tverdislov V. A. Energy distribution and ion selectivity of the bacterial potassium channel // Biofizika. 2006. Vol. 51. No. 4. P. 624-628.
- Article Dmitriev A., Tverdislov V. A. Separation of long-and short-range interactions in calculations of energy distribution of ions in membrane channels // Journal of Structural Chemistry. 2006. Vol. 47. No. 2. P. 241-246.
20052
- Article Dmitriev A., Tverdislov V. A. About using the approximate fields to calculate the electrostatic potential distribution of membrane channels // Journal of Structural Chemistry. 2005. Vol. 46. No. 5. P. 624-628.
- Chapter Dmitriev A., Baryshnikov V., Markov I., Tverdislov V. Band and point statistical estimation of channelforming polypeptides potential, in: Progress in Chemomitrics Research. Band and Point Statistic Estimation of Channelforming polypeptides potential. NY : Nova Science Publishers, 2005. P. 30-45.
20041
20022
- Article Dmitriev A., Isaev P. P., Isaeva G. A. Energy Levels and Wave Functions of an Ion in Gramicidin Channels // Biofizika. 2002. Vol. 47. No. 5. P. 864-868.
- Article Isaeva G. A., Dmitriev A., Isaev P. P. Interaction of Local Anesthetics with Model Ion Channels // Biofizika. 2002. Vol. 47. No. 3. P. 506-511.
20012
- Article Isaeva G. A., Dmitriev A., Isaev P. P. Effect of the Basis on the Accuracy of Dipole Moment Estimation for Acetanilide // Journal of Structural Chemistry. 2001. Vol. 42. No. 6. P. 1222-1225.
- Article Isaeva G. A., Dmitriev A., Isaev P. P. QSAR Relationships for the Anesthetic Activity of Acetanilides Analyzed by Regression and Quantum-Chemical Methods // Pharmaceutical Chemistry Journal. 2001. Vol. 35. No. 6. P. 54-66.