Denis A. Fomenkov is a Lecturer at the Department of Marketing, Faculty of Management, HSE University, Nizhny Novgorod. He has been affiliated with HSE since 2009 and holds a Candidate of Sciences (PhD) in Economics and National Economy Management (2009) and a degree from HSE University (2006). His research focuses on Marketing innovation Contributions of universities to national innovation systems Brand management for radical innovations Digital product development Startup market performance
Denis Romanovich Rakitin serves as a Research Fellow and Senior Lecturer at the Faculty of Computer Science, National Research University Higher School of Economics (HSE University), where he has been employed since 2020. He is affiliated with both the Institute of Artificial Intelligence and Digital Sciences and the Center for Deep Learning and Bayesian Methods, contributing to HSE's growing prominence in AI research. Rakitin completed his Master's degree in Applied Mathematics and Computer Science at HSE in 2022 and is currently in his third year of postgraduate studies. His dissertation focuses on computational methods for solving the Schrödinger bridge problem under the supervision of Professor Dmitry Petrovich Vetrov. His academic journey reflects a strong foundation in mathematical and computational disciplines applied to cutting-edge AI research problems. His research interests center around Bayesian methods, machine learning, and probability theory, with significant contributions to generative models, differentiable rendering, and probabilistic approaches to AI challenges. His teaching portfolio includes advanced courses such as "Generative Models Based on Diffusion" and "Probability Theory," for which he was recognized as "Best Teacher of 2023." Rakitin's publication record demonstrates expertise in cutting-edge areas of machine learning, with research presented at top-tier conferences including NeurIPS, ICML, and AISTATS. His work spans computer vision, graphics, and combinatorial optimization, reflecting the interdisciplinary nature of modern AI research. Letter of gratitude from the Faculty of Computer Science at HSE (July 2023) Academic Work Allowance (2024-2025) Bonus for publication in a journal from List A (2025-2026, 2023-2024) Best Teacher of 2023 High Professional Potential Group (HSE Personnel Reserve) Category 'New Researchers' (2022-2023) Yandex Scholarship Award (2025) As a member of the Center for Deep Learning and Bayesian Methods, Rakitin actively participates in academic events such as the workshop "The Mathematics of Machine Learning," where researchers explore mathematical aspects underlying modern machine learning approaches. His recent recognition with the Yandex Scholarship highlights his significant contributions to research in computer science and positions him as a rising figure in Russia's AI research community.
Alexander Mikhailovich Shabalin is a Visiting Lecturer and Research Intern at the National Research University Higher School of Economics (HSE), specifically within the Faculty of Computer Science, Institute of Artificial Intelligence and Digital Sciences, Center for Deep Learning and Bayesian Methods, and Department of Big Data and Information Retrieval. He began working at HSE in 2020 and is currently in his second year of postgraduate studies. Shabalin holds a Master's degree (2023) and Bachelor's degree (2021) in Applied Mathematics and Computer Science from HSE. His approved dissertation topic is "Application of diffusion models to text data" under the supervision of Dmitry Petrovich Vetrov. His primary research interests focus on Natural Language Processing and self-supervised learning, with particular emphasis on diffusion models for text data. His work bridges theoretical machine learning concepts with practical applications in text analysis and generation. The research trajectory evident in his publications shows a progression from foundational machine learning concepts toward more specialized applications of diffusion models in language processing. Among his notable achievements are contributions to three significant Massive Open Online Courses (MOOCs) including "Modern Data Analysis: Machine Learning," "Fundamentals of Deep Learning," and "Advanced Deep Learning Methods," demonstrating his commitment to education and knowledge dissemination in artificial intelligence. As an educator, Shabalin teaches "Deep Learning for Text Data" across multiple programs including Applied Mathematics and Computer Science and Economics. His teaching experience spans various faculties and demonstrates versatility in delivering technical content to diverse student populations. His professional background includes research at the Center for Deep Learning and Bayesian Methods since 2021, along with previous development experience at Yandex.Cloud and Yandex ML-landing where he worked on infrastructure development and reinforcement learning applications for music recommendations.
Egor Felixovich Chimbulatov serves as a Research Intern at the Center for Deep Learning and Bayesian Methods and as a Teacher in the Department of Big Data and Information Retrieval at the National Research University Higher School of Economics (HSE), Faculty of Computer Science. He began his work at HSE in 2024 and is affiliated with the Institute of Artificial Intelligence and Digital Sciences. Chimbulatov completed his Bachelor's degree in Applied Mathematics and Computer Science from Lomonosov Moscow State University in 2023. His professional interests focus on diffusion models and their application in text generation, representing cutting-edge research in artificial intelligence. His research output includes work on understanding diffusion model properties in language model encodings, demonstrating expertise at the intersection of generative AI and natural language processing. While early in his career, his publication record shows promising contributions to the field of machine learning. Chimbulatov has been recognized for his potential, being selected for the High Professional Potential Group in the HSE Personnel Reserve under the 'New Researchers' category for 2025. High Professional Potential Group (HSE Personnel Reserve) Category: New Researchers (2025) As an educator, Chimbulatov teaches advanced courses including Bayesian Methods in Machine Learning and Deep Learning for Text Data to fourth-year undergraduate students in both Applied Mathematics and Computer Science and Economics programs. His teaching responsibilities indicate strong technical expertise in machine learning methodologies and their practical applications. He works under the supervision of Alanov A. at the Center for Deep Learning and Bayesian Methods, which hosted its fifth 'Laboratory' meeting in December 2024 where students had the opportunity to explore the center's research activities. Chimbulatov maintains professional profiles through ORCID (0009-0003-8638-7102), ResearcherID (LQJ-8752-2024), and Google Scholar, demonstrating his commitment to academic transparency and scholarly communication.
Sergey Alexandrovskiy is Associate Professor at the National Research University Higher School of Economics (HSE University) and has served since 2020 as Director of the HSE Business School in Nizhny Novgorod. He has been a continuous member of HSE’s academic staff since 2007, previously heading the Master’s Programme in Marketing (2015–2020) and holding ranks from Senior Lecturer to Associate Professor. Education 2011 – Candidate of Sciences (PhD equivalent) in Economics and National Economy Management, Nizhny Novgorod State University of Architecture and Engineering 2006 – Specialist degree, HSE University Research Interests His research agenda centres on data-driven management , marketing analytics , and strategic alliances within innovation ecosystems. He investigates how firms leverage data for marketing decisions, how entrepreneurial ecosystems evolve in transforming economies, and how imitation strategies shape startup performance. Scientific Awards Best Teacher Award – 2018–2021, 2016 HSE Young Faculty Support Programme – “Future Professoriate” (2012) HSE Young Faculty Support Programme – “New Lecturers” (2009–2010) Grants & Advising He has led or co-led competitive research grants from HSE, including a 2014 faculty grant on “Research of imitation practices in Russian companies” and a 2013 HSE research group grant on “Contemporary marketing practices in Russia”. He supervises numerous master’s theses and term papers in management and marketing analytics. Labs & Teams While no dedicated lab is named, his ongoing leadership of the Business School and master’s programmes implies active engagement with research teams in marketing analytics and data-driven management at the Nizhny Novgorod campus.
Professor Igor Rubenovich Agamirzyan is a distinguished academic and administrator at the National Research University Higher School of Economics (HSE), holding professorial positions across multiple departments. He serves as Professor at the Faculty of Computer Science/Department of Software Engineering, Professor at the Moscow Institute of Electronics and Mathematics named after A.N. Tikhonov/Department of Electronic Engineering, and Professor at the School of Innovation and Entrepreneurship. Additionally, he is the Scientific Director of the educational program "Internet of Things and Cyber-Physical Systems." With 28 years of scientific and teaching experience, Professor Agamirzyan has been contributing to HSE since 2016, following a distinguished career in both academia and the technology industry. Professor Agamirzyan's educational background includes: 1986: Candidate of Physical and Mathematical Sciences 1979: Graduated from Leningrad State University named after A.A. Zhdanov with specialty in "Applied Mathematics," qualification as "Mathematician. Teacher" His professional development continues with recent advanced training: 2025: "Modernization of educational programs in software engineering in the context of scientific and technological development of Russia," HSE University 2024: "Problems of training modern specialists in software engineering," Faculty of Computer Science, HSE 2021: "Features of the organization of the educational process at HSE," National Research University Higher School of Economics Professor Agamirzyan's research spans multiple domains at the intersection of technology, innovation, and entrepreneurship. His work focuses on cyber-physical systems, Internet of Things (IoT), digital transformation, and the management of innovation. He has made significant contributions to understanding how technological advancements shape urban environments, business models, and educational approaches. His research often bridges theoretical frameworks with practical applications, emphasizing the importance of integrating technological capabilities with market needs and policy frameworks. His recent publications demonstrate a clear progression from foundational work in programming and software engineering to contemporary research on digital transformation, innovation ecosystems, and cyber-physical systems. The trajectory of his scholarly output reflects the evolution of information technology from standalone systems to interconnected networks and intelligent environments. His work increasingly addresses the societal implications of technological change, particularly in urban contexts and educational settings. Professor Agamirzyan has received numerous prestigious awards and recognitions: HSE University Honorary Diploma (March 2024) Gratitude from the Ministry of Education and Science of Russia (August 2023) Letter of thanks from the Vice-Rector of HSE (January 2023) HSE University Honorary Diploma (March 2022) Gratitude from the Director of the Roscongress Foundation (June 2019) Honorary Diploma of HSE (March 2017) Certificate of Honor of the Ministry of Economic Development of the Russian Federation (March 2012) Gratitude from the Government of the Russian Federation (2011) Gratitude from the President of the Republic of Tatarstan (December 2014) Throughout his career, Professor Agamirzyan has played significant leadership roles in academic administration and innovation management. As Vice-President of HSE from July 2016 to June 2023, he was responsible for developing the university's innovation ecosystem strategy, building relationships with technology businesses, and creating feedback mechanisms with employers to adjust graduate requirements. Prior to this, he served as General Director and Chairman of the Board of JSC "Russian Venture Company" from April 2009 to June 2016. His extensive industry experience, including leadership roles at Microsoft and EMC, informs his approach to academic-industry collaboration and innovation management education. Professor Agamirzyan has been instrumental in developing HSE's innovation infrastructure, including project-based learning initiatives and startup support programs. He has contributed to the establishment of the School of Innovation and Entrepreneurship, which evolved from the Department of Innovation Management founded in 2009. His leadership has helped position HSE as a leader among entrepreneurial universities in Russia, with the university ranking first in the Expert Analytical Center's entrepreneurial university rankings.
Vladimir Vladimirovich Karacharovsky is an Associate Professor at the Department of Applied Economics, Faculty of Economic Sciences, National Research University Higher School of Economics (HSE). He also serves as Deputy Dean for work with applicants, graduates and employers, and as Head of the Laboratory for Comparative Analysis of the Development of Post-Socialist Societies at the same faculty. With 25 years of scientific and teaching experience, Karacharovsky began his career at HSE in 2000, initially as a teacher (later senior teacher) until 2005 when he became an Associate Professor. His educational background includes a Candidate of Economic Sciences degree (2005) from the Institute of Systems Analysis of the Russian Academy of Sciences, a Master's degree in Sociology (2001) from HSE, and a specialty in Solid State Physics (1997) from Moscow State Engineering Physics Institute. Professor Karacharovsky's research focuses on socioeconomics, economic sociology, the relationship between economic theory and social values, social and technological changes, social contract theory, and justice theory. His work bridges economics and sociology, examining how social structures and values influence economic behavior and vice versa. He has developed innovative approaches to measuring social phenomena, including the 'shadow price of social change' concept that has become influential in Russian social sciences. His recent publications demonstrate a consistent focus on understanding Russian society through the lens of social values, preferences, and institutional changes. Karacharovsky has developed methodologies for measuring societal security shocks and analyzing intergenerational preferences, contributing significantly to the understanding of Russian social dynamics. HSE University Honorary Diploma (September 2024) Gratitude from the Vice-Rector of HSE (September 2022) Medal 'Recognition - 20 years of successful work' of HSE (August 2021) Letter of thanks from the Rector of HSE (March 2021) Multiple other awards and recognitions throughout his career As Deputy Dean, Karacharovsky oversees work with applicants, graduates, and employers, managing the faculty's outreach and ensuring strong connections between academic programs and the professional world. He has supervised numerous student qualification works, guiding students through research on topics ranging from human capital to market competition. His current research is supported by grants from the Russian Science Foundation, including a 2024-2025 project on societal security shocks. Professor Karacharovsky leads the Laboratory for Comparative Analysis of the Development of Post-Socialist Societies, which conducts comparative research on social and economic transformations in post-socialist countries. The laboratory has produced significant research on labor markets, innovation, social values, and institutional change in the post-Soviet space.
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.
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.
Nina Yuryevna Chelysheva serves as a Research Intern at the Center for Deep Learning and Bayesian Methods within the Institute of Artificial Intelligence and Digital Sciences, Faculty of Computer Science at the National Research University Higher School of Economics (HSE). Concurrently, she holds a Visiting Lecturer position in the Department of Big Data and Information Retrieval at the same faculty. Since June 2024, she has also been conducting research at AIRI (Artificial Intelligence Research Institute) on semantic image editing using text-to-image diffusion models. Her educational background includes: Bachelor of Science in Applied Mathematics and Computer Science, National Research University Higher School of Economics (2025) Chelysheva's research focuses on Deep Learning and Bayesian Methods , particularly in semantic image editing through text-to-image diffusion models . Her work bridges theoretical advancements in generative AI with practical applications in computer vision. Additional expertise spans Information Retrieval and Big Data analytics through her departmental affiliation. No scientific awards or fellowships are documented in available sources. Current advisory roles and grant funding details are not specified in public records. She actively contributes to the Center for Deep Learning and Bayesian Methods at HSE and collaborates with AIRI , driving innovation in diffusion model applications for image manipulation and analysis.
Fyodor Konstantinovich Pakhurov serves as a Research Intern at the Institute of Artificial Intelligence and Digital Sciences and as a Visiting Lecturer in the Department of Big Data and Information Retrieval within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE). He joined HSE in 2025 and works under the supervision of Lukyanchenko P.P. His research focuses on cutting-edge areas of artificial intelligence with particular emphasis on Natural Language Processing and Large Language Models. His work bridges theoretical computer science with practical financial applications through involvement in the Project-based Learning Laboratory "Artificial Intelligence in Mathematical Finance". Pakhurov actively participates in academic events and project seminars, contributing to the university's research ecosystem. His professional profile reflects strong engagement with both academic instruction and practical industry applications of AI technologies. He maintains professional activity with Ecom.Tech as a Machine Learning Model Specialist since 2024, demonstrating dual commitment to academic and industry work. His involvement in HSE's fifth Fintech School and project seminars on diffusion models highlights his active role in current research discussions.
