جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Data Analysis
• +۱۲ مورد دیگر

Dmitry Vladimirovich Alexandrov serves as Professor at the Faculty of Computer Science, Department of Software Engineering at the National Research University Higher School of Economics (HSE) and heads the Research and Educational Laboratory of Cloud and Mobile Technologies. With 24 years of scientific and teaching experience, he joined HSE in 2014 and has established himself as a leading expert in multiple computer science domains. His academic credentials include Doctor of Technical Sciences (2010) and the academic title of Professor (2012). His educational foundation was built at Vladimir State University, where he graduated in 1997 with specialty in "Computers, complex systems and networks" and earned his Candidate of Technical Sciences degree in 2000. Dr. Alexandrov's research spans artificial intelligence, machine learning, mobile application development (particularly iOS), software engineering, and database technologies. His work bridges theoretical research with practical applications in cloud computing, mobile technologies, and intelligent systems development. His recent publications reveal a strong focus on practical AI applications in software engineering, including code generation using large language models, service mesh optimization, face recognition algorithms, and database technologies. This research demonstrates interdisciplinary collaboration across computer science subfields with real-world applications. HSE University Honorary Diploma (February 2025) Gratitude from the Faculty of Computer Science, National Research University Higher School of Economics (July 2023) Dr. Alexandrov actively supervises students at all academic levels, from bachelor's theses to doctoral research. He has secured significant research funding including the Grant of the President of the Russian Federation for state support of scientific research by young Russian scientists-doctors of sciences. As laboratory head, he directs research on cloud and mobile technologies, oversees scientific seminars, and leads collaborative projects with industry partners. His laboratory recently developed and registered with Rospatent software for visualization and markup of digital medical images in DICOM format, developed in partnership with the N.V. Sklifosovsky Research Institute of Emergency Medicine.

• Cybersecurity
• Infocommunications
• Cloud Technologies
• +۵ مورد دیگر

Alexey Nikolaevich Nazarov is a Professor at the Department of Software Engineering, Faculty of Computer Science, National Research University Higher School of Economics (HSE), where he has worked since 2015. His academic and teaching experience spans 14 years, with a focus on cybersecurity, cloud technologies, and information confrontation in social media. Doctor of Technical Sciences (2000) Engineer-Mathematician, Moscow Geological Prospecting Institute (1980) UN and ITU-certified expert His research interests center on cybersecurity , information warfare , and mathematical modeling , particularly in IoT and social media contexts. Articles highlight trends in neural network intrusion detection , ferroelectric memory devices , and cloud resource optimization . He has supervised 5 postgraduate and 2 doctoral students, organized scientific seminars, and contributed to cloud technology curricula. His expertise includes international standards (ITU, VAK), Skolkovo grant #87 (2012), and leadership in cybersecurity research.

• Global Optimization
• Augmented Reality
• Computational Biology
• +۳ مورد دیگر

Ignatov Andrey Dmitrievich is a lecturer at the Faculty of Computer Science , Department of Software Engineering at National Research University Higher School of Economics (HSE), since 2019. He holds a postgraduate degree in Informatics and Computer Engineering (2023) and Master's in Applied Mathematics and Computer Science from Lomonosov Moscow State University (2019). Lecturer in Software Engineering and Applied Mathematics programs Conducts research in combinatorial optimization and protein structure modeling Recipient of multiple teaching awards including Best Teacher (2023, 2025) His research focuses on global optimization , parallel computing , and computational biology with applications to cloud scheduling and protein modeling. Publications demonstrate expertise in heuristic algorithms , branch-and-bound optimization , and BOINC-based distributed computing . Recent teaching includes courses on Algorithms and Data Structures, Protein Structure Modeling, and Optimization Methods. 2023-2024, 2024-2025: Allowance for young teachers 2023: Gratitude from Faculty of Computer Science 2024: Category 'New Lecturers' 2025: Co-inventor of legal assistance software patent

• mathematical economics
• optimal control
• mathematical modeling
• +۳ مورد دیگر

Nikolay Petrovich Pilnik serves as Deputy Dean for Project Work and Interaction with Partners at the Faculty of Economic Sciences of the National Research University Higher School of Economics (HSE) in Moscow. He also holds positions as Deputy Head of the Department of Applied Economics and Senior Research Fellow at the Scientific and Educational Laboratory of Macrostuctural Modeling of the Russian Economy. With over 16 years of scientific and teaching experience, Pilnik has been working at HSE since 2009 and is a member of the Academic Council of the university. Candidate of Economic Sciences (2012) Master's degree in Economics from HSE (2008) Bachelor's degree in Economics from HSE (2006) Pilnik's research focuses on mathematical economics, optimal control, mathematical modeling of economic mechanisms, simulation modeling, and macroeconomics. His work demonstrates a strong emphasis on dynamic general equilibrium models, banking system analysis, and macroeconomic forecasting. He has developed specialized models for analyzing Russian economic systems, particularly in the banking sector, and has contributed significantly to understanding the relationship between monetary policy and banking indicators. His recent publications (2019-2025) reveal a consistent research trajectory in mathematical economics and macrostructural modeling. The articles predominantly focus on general equilibrium modeling, banking system dynamics, optimal control applications in economics, and spatial market analysis. A significant portion of his work examines the Russian banking system's response to monetary policy changes, particularly regarding the Bank of Russia's key rate. Honorary Diploma of the Faculty of Economic Sciences (January 2024) Medal "Recognition - 15 years of successful work" (December 2022) Multiple Academic Work Allowances (2011-2018) Consistently recognized as "Best Teacher" (2012-2023) Pilnik has supervised several graduate students working on topics related to macroprudential policy, budget rules, spatial market equilibrium, and banking sector dynamics. He has participated in numerous research grants, including projects funded by RFBR, RGNF, and RSF, focusing on mathematical modeling of economic systems, financial balance monitoring, and general equilibrium modeling. Pilnik is also actively involved in the Laboratory of Macrostuctural Modeling of the Russian Economy, where he contributes to ongoing research and forecasting projects related to the Russian economy.

• Distributed computing
• Composite application planning
• Social media analysis
• +۱ مورد دیگر

Nikolay Butakov is an Associate Professor at the Faculty of Digital Transformation and a Senior Researcher at the Research Center ‘Strong AI in Industry’ at ITMO University. He earned a PhD in engineering and has been actively involved in research, teaching, and student supervision since 2013. Education: Graduated from Ulyanovsk State University (2012) in Mathematical Software and Administration of Information Systems; PhD in Mathematical and Software Support of Computers, Complexes, and Computer Networks (2015) at ITMO University Research Focus: High-performance computing, distributed systems, cognitive modeling, and social media analysis Labs: National Center for Cognitive Research, Research Center ‘Strong AI in Industry’

• Mathematical modeling of physical and chemical processes
• High-temperature gas dynamics
• Optoelectronics materials and structures
• +۳ مورد دیگر

Sergei Khoruzhnikov is an Associate Professor at ITMO University, serving as Head of Department for Information and Communication Infrastructure, Director of the University Telecom Center, and Dean of the Faculty of Infocommunication Technologies. He also leads the International Laboratory 'Networked Technologies in Distributed Computer Systems' and has been instrumental in nationwide educational technology initiatives. PhD in Thermal Physics from M.Kalinin Leningrad Polytechnic Institute His research focuses on mathematical modeling of high-temperature gas processes for optoelectronic materials and large-scale network infrastructure development. He pioneered Russia's RUNNet computerization program and satellite-based remote access systems for rural schools, managing networks serving over 10,000 institutions. Notable achievements include the 1999 Russian Government Prize in Education for RUNNet's development. His publications span computational modeling of chemical reactors and thin-film fabrication processes, reflecting interdisciplinary expertise in physics, engineering, and telecommunications.

• Modelling of complex systems
• High-performance computing
• Distributed computing
• +۴ مورد دیگر

Sergey Kovalchuk is Associate Professor at the Faculty of Digital Transformation and Senior Researcher at the National Center for Cognitive Research, ITMO University, Russia. He also teaches at the Institute of Design & Urban Studies and heads the Master’s programmes in Computational Biomedicine and Digital Healthcare. Education: 2006 – BSc/Spec., Software of Computing and Automated Systems, Orenburg State University 2008 – PhD in Engineering, ITMO University Research interests revolve around mathematical and computational modelling of complex systems, high-performance and distributed computing infrastructures, and intelligent knowledge-oriented technologies applied to e-Science and digital healthcare domains. He leads the Digital Healthcare research team, supervises Bachelor’s, Master’s and PhD students, and serves on ITMO’s Academic Council and the Academic Council of the School of Translational Information Technologies. Since 2016 he acts as visiting editor for annual special issues of the Journal of Computational Science devoted to the ICCS conference.

• Big Data Processing
• Computational Science
• Distributed Computing
• +۳ مورد دیگر

Denis Nasonov is an Associate Professor at ITMO University's Faculty of Digital Transformation and Senior Research Associate at the National Center for Cognitive Research. He leads the Research Laboratory "Cognitive Technologies in Industry" and contributes to TROIKA: Technology and Research On Information-Driven Knowledge Alliance since 2013. Graduated from ITMO University with a major in Applied Mathematics and Computer Science (2010) Specializes in Big Data processing, workflow scheduling algorithms, and urgent computing infrastructure Active in computational science research with focus on distributed environments and metaheuristic optimization His research spans computational science, distributed computing, and environmental modeling, focusing on hybrid scheduling algorithms for early warning systems and urgent computing applications. Email: dnasonov@itmo.ru

• Computer Science
• Software Engineering
• Artificial Intelligence
• +۳ مورد دیگر

Dmitry Zhdanov is an Associate Professor and Senior Researcher at the Faculty of Software Engineering and Computer Systems at ITMO University. His work focuses on foundational and applied aspects of computer science, with an emphasis on software engineering methodologies and advanced data systems development. University: ITMO University Faculty: Software Engineering and Computer Systems Email: ddzhdanov@itmo.ru

• stochastic approximation
• reinforcement learning
• sampling
• +۴ مورد دیگر

Sergey Vladimirovich Samsonov is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), where he also serves as Head of the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis within the Institute of Artificial Intelligence and Digital Sciences. He is affiliated with the Department of Big Data and Information Retrieval and the Joint Department of the A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences. Samsonov began his tenure at HSE in 2018 and has accumulated 7 years of scientific and teaching experience. His educational background includes a PhD from HSE (2024) and a Bachelor's degree in Applied Mathematics and Computer Science from Lomonosov Moscow State University (2017). Samsonov's research focuses on stochastic approximation, reinforcement learning, sampling techniques, Markov chain Monte Carlo (MCMC) methods, and multivariate statistics . His work bridges theoretical mathematics with practical machine learning applications, particularly in developing algorithms with strong theoretical guarantees. He has made significant contributions to understanding convergence properties of stochastic algorithms and developing variance reduction techniques. Analysis of his recent publications reveals a consistent focus on the mathematical foundations of machine learning, particularly in stochastic approximation methods, reinforcement learning theory, and generative modeling. His work often combines rigorous theoretical analysis with practical applications, demonstrating expertise in both pure mathematics and applied machine learning. The publication venues (including top conferences like NeurIPS, ICLR, and AISTATS) reflect the high impact and quality of his research in the machine learning community. Young Scientist Badge (December 2024) Letter of gratitude from the First Vice-Rector of HSE (March 2023) Letter of gratitude from the Faculty of Computer Science at HSE (September 2021) Rector's personal allowance (2022-2023) Numerous bonuses for high-impact publications (2021-2027) Best Teacher award (2024-2025, 2022, 2020) Segalovich Scientific Prize (2022) National Prize 'Leaders in AI - 2024' Samsonov teaches advanced courses including Markov Chains, Sampling and Generative Modeling, and Matrix Computations. His laboratory work focuses on developing stochastic algorithms for machine learning applications. He has been involved in HSE's collaboration with Sber, which has resulted in 19 successfully implemented AI projects since 2021. His research has gained significant recognition, with multiple papers accepted at top-tier conferences including 12 papers presented at NeurIPS in recent years.

• nonparametric statistics
• Statistics of random processes
• numerical methods of stochastics
• +۵ مورد دیگر

Denis Vitalievich Belomestny is a Leading Researcher at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE) in Moscow. He is affiliated with the Institute of Artificial Intelligence and Digital Sciences and the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis. Belomestny joined HSE in 2014 and has accumulated 11 years of scientific and teaching experience. His academic background includes a Candidate of Physical and Mathematical Sciences degree from Lomonosov Moscow State University (2002) and a specialty in Applied Mathematics from the same university (1998). Belomestny's research focuses on nonparametric statistics , statistics of random processes , numerical methods of stochastics , and financial mathematics . His work demonstrates a strong interdisciplinary approach bridging theoretical mathematics with practical applications in machine learning and artificial intelligence. He has made significant contributions to the analysis of stochastic differential equations, particularly McKean-Vlasov type models, and has developed innovative methods combining deep learning with traditional statistical techniques. His recent publication record shows a clear trend toward integrating deep neural networks with classical stochastic analysis. The 15 most recent articles reveal a growing emphasis on applying machine learning techniques to solve complex problems in statistical inference, particularly in areas like variance reduction, optimal stopping, and density estimation. His research spans both theoretical foundations and practical applications, with increasing focus on the intersection of probability theory and modern AI methodologies. Academic Work Allowance (2020–2021, 2019–2020) Bonus for an article in a foreign peer-reviewed scientific publication (2016–2018) Best Teacher of 2019 Belomestny has been actively involved in advising students and junior researchers, with numerous co-authored publications indicating his mentorship role. He is a key member of the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis, which received a significant grant from the Russian Science Foundation in 2018 (project No. 18-11-00132) led by Alexey Naumov, with Belomestny as a principal investigator. The laboratory focuses on high-dimensional data analysis and modern stochastic algorithms, positioning Belomestny at the forefront of research in these rapidly developing fields.

• Reinforcement Learning
• Probability Theory
• Stochastic Algorithms
• +۳ مورد دیگر

Ilya Valerievich Levin serves as a Junior Research Fellow at the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis and as a Teacher in the Department of Big Data and Information Retrieval, both within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE). He began his tenure at HSE in 2020 and has accumulated 3 years of scientific and teaching experience. His primary affiliations include the Institute of Artificial Intelligence and Digital Sciences where he works under the supervision of A. A. Naumov. ORCID: 0000-0002-9708-8189 Researcher ID: GZL-7944-2022 Location: Pokrovsky Boulevard, 11, office T926 Office Hours: 12:00-18:00 Levin's research expertise centers on reinforcement learning methodologies, stochastic approximation algorithms, and multidimensional data analysis. His work bridges theoretical foundations with practical applications in machine learning systems, particularly focusing on federated learning environments and evaluation frameworks for reinforcement learning algorithms. His research demonstrates strong mathematical foundations with applications across distributed computing systems. His publication record shows a clear trajectory in advancing reinforcement learning techniques, with recent work presented at NeurIPS 2024 addressing heterogeneity challenges in federated learning systems. His research combines theoretical rigor with practical implementation concerns, reflecting the interdisciplinary nature of modern artificial intelligence research. Letter of gratitude from the Faculty of Computer Science (July 2024) Bonus for publication in List A journal (2025-2026) HSE Personnel Reserve - New Researchers category (2022) Levin has been actively involved in teaching Probability Theory, Mathematical Statistics, and Mathematical Foundations of Reinforcement Learning across multiple academic programs including bachelor's and master's degrees. His teaching spans both Russian and English language instruction formats, including specialized programs like Mago-Lego. He has consistently taught core mathematical courses for computer science students since the 2022/2023 academic year, demonstrating commitment to foundational education in the field.

• Machine Learning
• Natural Language Processing
• Deep Learning
• +۲ مورد دیگر

Elizaveta Vsevolodovna Zhemchuzhina serves as a Researcher and project manager at the National Research University Higher School of Economics (HSE University), affiliated with the Faculty of Computer Science and the Institute of Artificial Intelligence and Digital Sciences. She works within the Laboratory of Theoretical Foundations of Artificial Intelligence Models where she manages applied research projects under supervisor Puchkin N. A. She earned her Bachelor's degree in Applied Mathematics and Computer Science from HSE University in 2023 and has been engaged in research activities since 2021. Her professional trajectory shows progression from research projects at LEA, HSE St. Petersburg (2021-2023) to managing applied projects at HSE University since 2024. Dr. Zhemchuzhina's research focuses on machine learning and data analysis with specialization in natural language processing using deep neural networks. She maintains strong interest in commercialization of scientific results, bridging theoretical AI advancements with practical applications. Her work on the project "Complexity and learnability of artificial intelligence models" reflects her commitment to both theoretical foundations and real-world implementation of AI systems. Her publication record includes research presented at the prestigious AAAI Conference on Artificial Intelligence (2023), demonstrating her contributions to computational linguistics and semantic modeling within the AI field. Professional Role: Project manager for applied research at Institute of AI and Digital Sciences Collaboration: Organizes industry partnerships and integrates HSE students into laboratory work Location: Office T926 at Pokrovsky Boulevard, Building 11 (10:00-18:00)

• Probability Theory
• Random Processes
• Large Deviations
• +۲ مورد دیگر

Evgeny Igorevich Prokopenko is a Senior Research Fellow at the Faculty of Computer Science, National Research University Higher School of Economics (HSE), specifically within the Institute of Artificial Intelligence and Digital Sciences and the Laboratory of Theoretical Foundations of Artificial Intelligence Models. He joined HSE in 2024 and concurrently serves as a Senior Researcher at the Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences since January 2019. His educational background includes: 2018: Candidate of Physical and Mathematical Sciences 2014: Master's degree in Mathematics from Novosibirsk National Research State University Prokopenko specializes in probability theory and random processes, with particular focus on large deviations. His research bridges theoretical mathematics with applications in artificial intelligence and complex systems. His work demonstrates a strong foundation in mathematical theory while addressing contemporary challenges in data science and stochastic modeling. His scientific contributions primarily focus on limit theorems, branching processes, and large deviation principles. His publications reveal a consistent research trajectory in probability theory with applications to various domains including polymer physics and random environments. The temporal pattern of his publications shows ongoing productivity with recent work published in top probability journals. His notable achievements include: Multiple publications in high-impact journals including Probability Theory and Its Applications, Extremes, Statistics and Probability Letters, and Problems of Information Transmission Collaborations with prominent researchers in probability theory across international institutions Prokopenko maintains active research affiliations with both HSE University in Moscow and the Sobolev Institute of Mathematics in Novosibirsk, reflecting a strong connection between Russia's leading mathematical centers. His current position at HSE's Faculty of Computer Science suggests an integration of his theoretical expertise with modern computational approaches.