جست‌وجوی استاد و پژوهشگر

• sociology of law
• sociology of professions
• economic sociology
• +۸ مورد دیگر

Anton Pavlovich Kazun is an Associate Professor at the Department of Applied Economics, Faculty of Economic Sciences, National Research University Higher School of Economics (HSE University). He serves as Director of both the Institute for Enterprise and Market Analysis and the International Center for the Study of Institutions and Development. Kazun has been working at HSE since 2011, accumulating over 11 years of scientific and teaching experience. His academic credentials include a Candidate of Sociological Sciences degree (2018) from HSE University, a Master's degree in Sociology (2014), and a Bachelor's degree in Sociology (2012), all from HSE University. His research spans the sociology of law, sociology of professions, economic sociology, informal economy, and collective actions, with a particular focus on the intersection of legal institutions, economic behavior, and social structures in Russia. Kazun's scholarly output demonstrates a consistent pattern of interdisciplinary research combining legal studies, sociology, and economics. His recent work increasingly employs text mining and computational analysis of court decisions, reflecting methodological innovation in studying legal systems. Research topics range from gender bias in homicide sentencing to business adaptation strategies under economic sanctions, showcasing the breadth of his scholarly interests. Gratitude from the Higher School of Economics (September 2021) Gratitude from the Higher School of Economics (May 2021) Gratitude from the Department of Applied Economics (February 2020) Winner in the "Article Series" nomination at NAMMI-2020 First prize "New Generation" from ANCEA (2014) As a supervisor, Kazun guides doctoral students working on industrial policy, decarbonization, regional development, and energy transition. His research is supported by significant grants including from the Russian Science Foundation (RSF) for developing automated analysis of court verdicts, and he leads the "Recommendation system for selecting a lawyer" project. He manages research teams, coordinates scientific activities, organizes conferences, and develops institutional strategies for the institutes he directs.

• History and philosophy of science
• Philosophy and medicine
• Epistemology of virtues
• +۷ مورد دیگر

Anastasia Valerievna Ugleva is a Professor at the School of Philosophy and Cultural Studies within the Faculty of Humanities at the National Research University Higher School of Economics (HSE University). She also serves as a Leading Researcher at the St. Petersburg School of Humanities and Arts, where she works in the Laboratory of Critical Theory of Culture. With over 20 years of academic experience since joining HSE in 2005, she has established herself as a prominent scholar in philosophy, ethics, and the intersection of AI and medicine. Her educational background includes: PhD from University Paris IV (2011), specialty: Natural Sciences, dissertation on "L'État face to the question of universities: comparative analysis of university politics in Russia and France" Academic title of Associate Professor (2010) Candidate of Philosophical Sciences from Lomonosov Moscow State University (2004), specialty: "History of Philosophy", dissertation on "Ontology of power in modern French philosophy" Specialist degree in Philosophy from Lomonosov Moscow State University (2001), qualification: "Philosopher. Teacher of Philosophy" Professor Ugleva's research spans the history and philosophy of science, philosophy and medicine, epistemology of virtues, bioethics, history of ethics and moral concepts, and socio-humanitarian and ethical expertise. Her work particularly focuses on the ethical implications of artificial intelligence in healthcare, moral philosophy, and the philosophical foundations of education. She has made significant contributions to understanding the intersection of technology, ethics, and human values. Her recent publications reveal a strong trend toward AI ethics, particularly in medical applications. She has developed an "Ethics Index" for AI systems in medicine, exploring how to balance technological innovation with ethical considerations. Her work bridges historical philosophical traditions (particularly Enlightenment thought and Condorcet's ideas) with contemporary technological challenges, creating a unique interdisciplinary approach to ethical questions in the digital age. Professor Ugleva has received numerous accolades for her contributions: Honorary title "Honored Worker of the Education Sector of the Russian Federation" (2022) Medal "Recognition - 15 years of successful work" from HSE University (2020) Multiple Letters of appreciation from HSE University and its Faculty of Humanities Designation as "Best Teacher" for 2011-2013 Academic work bonuses and publication bonuses spanning multiple years As an advisor, Professor Ugleva has mentored numerous students, including six PhD candidates and several master's and bachelor's students whose theses have won awards in HSE's NIRS competition. Her research is supported by various grants, including individual grants from HSE's Faculty of Philosophy and collective grants from HSE's Center for Fundamental Research. She is currently involved in the HSE AI Research Center's project on ethical expertise in AI, serving as head of the working group "Ethics of AI in Education." Professor Ugleva leads research activities at the Laboratory of Critical Theory of Culture in St. Petersburg and serves as HSE Ethics Commissioner for the Alliance in the field of Artificial Intelligence. She is also a member of the Commission for the Implementation of the Code of Ethics in the Sphere of Artificial Intelligence.

• Databases
• Software Engineering
• Data Warehousing
• +۶ مورد دیگر

Breiman Alexander Davidovich is an Associate Professor at the Department of Software Engineering, Faculty of Computer Science at the National Research University Higher School of Economics (HSE) in Moscow. He began working at HSE in 2010 and has 30 years of scientific and teaching experience. Previously, he served as an Associate Professor at the Department of Personal Computers and Networks at the Moscow State University of Instrument Engineering and Informatics from 1994 to 2013. He also works as a Senior Lecturer at the Luxoft Training Center since 2013 and as Head of the IT Department at Titan Meta LLC since 1996. National Research University Higher School of Economics (2010-present): Associate Professor/Invited Lecturer Moscow State University of Instrument Engineering and Informatics (1994-2013): Associate Professor Luxoft Training Center (2013-present): Senior Lecturer Titan Meta LLC (1996-present): Head of IT Department His educational background includes a Candidate of Technical Sciences degree (equivalent to PhD) from Moscow State Academy of Instrument Engineering and Computer Science in 1998, with a dissertation on "Database software for training systems with multimedia elements," and a degree in Computer Science from Moscow Institute of Instrument Engineering in 1994, specializing in "Computers, Complexes, Systems and Networks." Professor Breiman's research focuses on databases, software engineering, data warehousing, information systems, and knowledge engineering. His work spans theoretical database design, practical implementations of database systems, and educational applications of information technology. He has published extensively on database architecture, reliability engineering, and distributed systems, with a particular emphasis on practical applications in educational and business contexts. His teaching covers database systems, distributed databases, data warehouses, and advanced database topics across multiple programming languages and platforms. His publications reveal a consistent focus on database technologies, evolving from foundational database concepts to modern distributed and big data systems. He has explored specialized areas including embedded databases, social network analysis, process mining, and stream data processing systems, demonstrating both theoretical depth and practical application. Gratitude from the Faculty of Computer Science, HSE (July 2025) Best Teacher award (2021-2024) Best Teacher award (2016-2019) Best Teacher award (2013) Best Teacher award (2011) Professor Breiman has supervised numerous student theses at both bachelor's and master's levels, covering diverse topics in database systems, software engineering, and information systems. His students have developed applications ranging from distributed content delivery systems to health monitoring systems for diabetes patients. He teaches a variety of courses including Databases, Advanced Databases, Distributed Databases and Data Warehouses, and Database Construction, in both Russian and English. His teaching spans multiple campuses of HSE including Moscow, Perm, and Nizhny Novgorod. While not explicitly mentioning specific labs or research teams in the provided information, his work with students on practical implementations suggests active engagement with applied research projects, particularly in database technologies and their real-world applications.

• antitrust legislation
• corporate law
• competition law
• +۴ مورد دیگر

Ashfa Daniel Mohamadovich is a Lecturer at the Department of Public Law within the Faculty of Law at the National Research University Higher School of Economics (HSE), starting in 2025. He also serves as an Associate Professor at the Department of Competition Law, Moscow State Law University named after O.E. Kutafin since 2018. 2022: Candidate of Law, Moscow State Law University named after O.E. Kutafin 2018: Postgraduate Study, Moscow State Law University named after O.E. Kutafin 2015: Specialty in Jurisprudence, Moscow State Law University named after O.E. Kutafin His research focuses on antitrust legislation , corporate law , competition law , and financial law , with a particular emphasis on digital markets and artificial intelligence. He teaches courses like Competition Law and Antimonopoly Regulation at HSE. The 15 most recent articles span banking law , financial compliance , antitrust regulation , and AI in legal contexts , reflecting his expertise in digital market fairness and financial stability.

• Probability Theory
• Mathematical Statistics
• Combinatorial Optimization
• +۲ مورد دیگر

Dr. Zhukova Galina Nikolaevna is an Associate Professor at the Department of Software Engineering , Faculty of Computer Science , National Research University Higher School of Economics (HSE), where she has worked since 2017. Her academic career spans 21 years, including prior roles at Moscow State University of Printing Arts and Moscow Polytechnic University. PhD in Physical and Mathematical Sciences (2004, Moscow State University of Printing Arts) Specialist in Applied Mathematics (1999, Moscow State University) Advanced training in software engineering pedagogy (2018–2025) Research Focus : Dr. Zhukova specializes in Probability Theory , Mathematical Statistics , and Combinatorial Optimization . Her work analyzes algorithm complexity distributions, develops hybrid exact methods for the Traveling Salesman Problem (TSP), and investigates symbolic sequence reconstruction under noise. She contributes to probabilistic modeling of computational efficiency and quantile-based complexity metrics . Publication Trends : Her 15 most recent articles focus on TSP complexity prediction , noise-resistant sequence reconstruction , and hybrid algorithm design for asymmetric problems. These combine probabilistic modeling , statistical analysis , and computational efficiency studies , with applications in optimization and data processing. Gratitude from HSE Software Engineering Department (2023) Gratitude from HSE Faculty of Computer Science (2019) Selected for HSE Personnel Reserve (High Professional Potential Group) Recognized under 'New Teachers' category (2018) Teaching Contributions : Dr. Zhukova delivers courses on Operations Research , Mathematical Analysis , and Algebra in Python . She designs practical Python-based curricula for software engineering students and teaches minors in Applied Linear Algebra for the Faculty of Economic Sciences.

• Information Systems in Economics and Management
• Risk Management
• Business Process Optimization and KPI Development
• +۱ مورد دیگر

Pesotskaya Elena Yuryevna is an Associate Professor at the Faculty of Computer Science, Department of Software Engineering, National Research University Higher School of Economics (HSE), where she has worked since 2009. With 26 years of scientific and teaching experience, she holds a Candidate of Economic Sciences degree (2008) and a specialization in Applied Informatics in Economics (2002). Education: Candidate of Economic Sciences (2008), Moscow Institute of Economics and Statistics (2002) Her research focuses on Information Systems in Economics , Risk Management , Business Process Optimization , and IT Strategy Development . Her recent work explores AI-driven cybersecurity, blockchain applications, and pandemic-induced shifts in IT workforce requirements. She has authored 15 notable publications across 2007–2025, including conference chapters and journal articles. Her research trends span Software Engineering Education , Blockchain in Charity , and Agility-Driven Learning . Scientific Awards: Letter of thanks from HSE Rector (2024) Medal 'Recognition - 10 years of successful work' (2022) Gratitude from Higher School of Economics (2013) Academic Work Allowance (2012–2014) Best Teacher Award (2011–2012) Advising & Grants: Supervises final qualification works at HSE and has participated in multiple research grants and projects, particularly in AI and blockchain domains. Conferences: Regularly presents at international conferences like FICC, FTC, and CAISE, including topics on cybersecurity, digital government, and educational platforms.

• Software Engineering
• Formal Methods in Software Development
• Verification and Validation of Operating Systems
• +۲ مورد دیگر

Viktor Vyacheslavovich Kulyamin is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), affiliated with the Basic Department 'System Programming' of the Institute for System Programming (ISP RAS). With 25 years of scientific and teaching experience , he has been actively contributing to HSE since 2015. Education: 1995: Specialist in Mathematics (Applied Mathematics) from Lomonosov Moscow State University 2000: Candidate of Physical and Mathematical Sciences 2009: Academic Title of Associate Professor His research interests span software engineering , formal methods , verification and validation of operating systems, and security policy modeling . His recent publications focus on dynamic software analysis , runtime verification , multi-level security models , and formal testing techniques , reflecting a deep engagement with automated testing and system validation frameworks. Teaching : He has consistently taught Quality Assurance and Testing in the Software Engineering program at HSE since 2020, covering topics such as test construction , model-based testing , and system conformance . Professional Affiliation : Since 1998 , he has worked at the Institute for System Programming of the Russian Academy of Sciences , becoming a leading research fellow by 2014. He also held positions at Moscow State University's Department of System Programming (Senior Lecturer: 2008, Associate Professor: 2009).

• Competition Policy
• Industrial Market Theory
• Economic Analysis of Law
• +۳ مورد دیگر

Avdasheva Svetlana Borisovna is a distinguished Professor and Head of the Department of Applied Economics at the Faculty of Economic Sciences, National Research University Higher School of Economics (HSE). She also serves as Deputy Director of the Institute for Enterprise and Market Analysis. With 34 years of scientific and teaching experience, she has been a tenured Professor since 2007 and earned the title of Distinguished Professor in 2019. She is a Member of the Academic Council of HSE and has been working at the university since 1993, contributing significantly to the development of economic education and research in Russia. Professor Avdasheva's research focuses on competition policy, industrial market theory, and economic analysis of law, with a growing emphasis on digital platforms and their regulatory challenges. Her work bridges theoretical economic frameworks with practical policy applications, particularly examining how legal standards influence antitrust enforcement in transitional economies. She has extensively studied the Russian competition policy framework in comparative perspective, analyzing its evolution and effectiveness across various sectors including digital markets, agriculture, and energy. Her recent publications reveal a clear trend toward analyzing digital platform markets and their regulatory challenges, with increasing focus on AI applications in antitrust enforcement, the economic implications of deglobalization, and the interplay between competition policy and industrial policy. Her research spans both theoretical economic modeling and empirical analysis of competition authorities' practices across BRICS countries and beyond. Professor Avdasheva has received numerous prestigious awards including the Honorary Sign I Degree of Higher School of Economics, the Medal 'Recognition - 25 Years of Successful Work' of HSE, and the Medal of the Order 'For Merits to the Fatherland' II Degree. She has consistently been recognized as one of HSE's Best Teachers (2013, 2015-2016, 2018, 2022) and has received multiple publication bonuses for her scholarly contributions. As an academic advisor, Professor Avdasheva has supervised 14 PhD students to completion and currently mentors two doctoral candidates. Her teaching portfolio includes advanced courses on industrial market analysis, competition policy, and digital platform economics at both undergraduate and graduate levels. She has contributed to numerous research projects examining competition policy implementation, market structure analysis, and regulatory frameworks across various economic sectors.

• Algorithm Analysis
• Complex Networks
• Supercomputer Modeling
• +۳ مورد دیگر

Klavdiya Bochenina is a Researcher and engineer at ITMO University's National Center for Cognitive Research, where she has worked since 2013. She previously served as an assistant and senior lecturer at Vladimir State University from 2008 to 2013. Education: 2008 – BSc in Applied Mathematics and Computer Science from Vladimir State University; 2014 – PhD in Engineering. Advanced Training: Participated in the 4th International Young Scientists Conference and Summer School in Computer Modeling and Simulation (YSC 2015) in Athens, Greece. Teaching: Instructs courses in Algorithm Analysis and Development, and Machine Learning Technologies. Her research interests focus on algorithm design, computational modeling of complex systems, and high-performance computing. She actively applies parallel and distributed computing techniques to analyze critical phenomena in complex networks , while integrating machine learning methodologies into her work. Her professional activities bridge theoretical research and practical implementation in computational sciences. Contact details: kbochenina@itmo.ru | Homepage

• High-performance planning models
• Mathematical modeling (linear/integer programming)
• Information & Communication Systems
• +۷ مورد دیگر

Tatiana Zudilova is an Associate Professor at the Faculty of Infocommunication Technologies and Deputy Director of the IT Education Center at ITMO University. With over 30 years of experience, she leads Russia's first International Authorized Training Center for Information Technologies, collaborating with global IT giants like Microsoft, Oracle, Cisco, and IBM.

• automata theory
• formal languages
• information technology in education
• +۳ مورد دیگر

Ilya Yuryevich Samonenko serves as Associate Professor at the Department of Big Data and Information Retrieval within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE University). He holds dual administrative roles as Deputy Dean for Academic and Methodological Work for the Faculty of Computer Science and Director of the Center for organizing student training for top specialists in the field of artificial intelligence. Samonenko joined HSE University in 2018 and brings 11 years of scientific and teaching experience to his position. His educational background includes a Candidate of Sociological Sciences degree from Moscow State Technological University 'Stankin' (2009) and a Mathematics specialty from Lomonosov Moscow State University (2006), where he also completed additional qualifications as a Specialist in theoretical computer science (2005), Higher education teacher (2011), and Management in Education (2017) from Moscow State Pedagogical University. Samonenko's research spans automata theory , formal languages , information technology in education , and social graph analysis . His scholarly work demonstrates a clear trajectory from theoretical computer science toward applications in educational contexts and organizational structures. He has published extensively on automata theory, face recognition, and the application of social graph analysis to organizational efficiency. His 14 publications over two decades reveal a research evolution from pure theoretical computer science toward more applied work in educational technology and organizational analysis. His recent work focuses on social graph structure in organizations, academic performance analysis using educational data, and the application of formal language theory to practical problems. Letter of gratitude from the Vice-Rector of HSE University (October 2024) HSE University Honorary Diploma (October 2022) Letter of gratitude from the Director of the HSE Lyceum (August 2022) Honorary Diploma from the Higher School of Economics (June 2020) Participant of the Administrative Personnel Reserve program (2019–2020) Best Academic Supervisor in the category 'Student Engagement in Intercampus and Interfaculty Interaction' - 2024 Best Academic Supervisor in the International Student Admissions category – 2024 As Deputy Dean, Samonenko coordinates educational programs, participates in accreditation processes, develops regulatory documents for the educational process, and oversees faculty initiatives. He coordinates interaction between the faculty and both the HSE Lyceum and the general education system. Notably, he was featured in university news as one of the first couples to have a wedding at the Durasov House on Pokrovsky Boulevard, part of the HSE University campus. Samonenko teaches core computer science courses including Algorithms and Data Structures, Python Programming Language, and Programming and Data Analysis in Python across multiple departments at HSE University. His teaching spans the Faculty of Computer Science, Faculty of Economic Sciences, and Faculty of Social Sciences.

• optimal transport
• probability theory
• mathematical statistics
• +۲ مورد دیگر

Aleksey Vladimirovich Kroshnin is a Senior Research Fellow at the Faculty of Computer Science, National Research University Higher School of Economics (HSE), working within the Institute of Artificial Intelligence and Digital Sciences and the Laboratory of Theoretical Foundations of Artificial Intelligence Models. He joined HSE in 2018 and maintains a dual affiliation as Junior/Senior Researcher at the Dobrushin Mathematical Laboratory, IITP RAS since 2016. His educational background includes a PhD from University of Lyon (2022), a Master's degree in Applied Mathematics and Physics from Moscow Institute of Physics and Mathematics (2018), and a Bachelor's degree in the same field (2016). Dr. Kroshnin's research focuses on optimal transport theory , probability and mathematical statistics , functional analysis , and convex optimization . His work bridges theoretical mathematics with practical applications in machine learning and data science, particularly in the area of Wasserstein geometry and barycenter computation. His publication record from 2018-2024 demonstrates consistent contributions to top-tier journals in mathematics, statistics, and machine learning. The research shows a clear trajectory toward increasingly complex applications of optimal transport in machine learning, with significant contributions to computational methods for Wasserstein barycenters and statistical inference in metric spaces. While specific awards aren't listed in the provided information, his publications in prestigious journals like Annals of Statistics, SIAM Journal on Mathematical Analysis, and Journal of Convex Analysis indicate recognition within the mathematical community. Dr. Kroshnin collaborates extensively with researchers at HSE and internationally, particularly with Gasnikov Alexander and other members of the optimization and machine learning community in Russia. His work combines deep theoretical insights with practical computational approaches to challenging problems in data science.

• Data Analysis
• Artificial Intelligence
• Financial Technology
• +۳ مورد دیگر

Maxim Vyacheslavovich Minets serves as Visiting Lecturer and Project Manager at HSE University's Faculty of Computer Science, primarily affiliated with Sberbank's Core Department of Financial Technologies and Data Analysis. He concurrently holds leadership roles in AI laboratories under the Institute of Artificial Intelligence and Digital Sciences. His academic background includes: Master's degree in Applied Mathematics and Computer Science (expected 2025), HSE University Bachelor's degree in Software Engineering (2023), HSE University Minets specializes in data analysis development with strong emphasis on financial technology applications, artificial intelligence integration, and big data methodologies. His practical work focuses on recommender systems and mathematical finance, demonstrated through the HSE Sber RecSys Hack 2024 which engaged 98 student teams from 50 Russian universities in developing advanced recommendation algorithms. Award recognition includes: Faculty of Computer Science Letter of Gratitude (July 2025) He actively manages the Project-based Learning Laboratory 'Artificial Intelligence in Mathematical Finance' and supports the Research and Educational Laboratory of Big Data Analysis Methods, facilitating industry-academia collaboration between HSE and Sberbank through teacher recruitment, student project supervision, and departmental event organization.

• convex optimization
• mathematical modeling of traffic flows
• Markov processes
• +۳ مورد دیگر

Alexander Vladimirovich Gasnikov is a Leading Researcher at the National Research University Higher School of Economics (HSE), specifically within the Faculty of Computer Science, the Institute of Artificial Intelligence and Digital Sciences, and the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis. He has been working at HSE since 2015 and has accumulated 17 years of scientific and teaching experience. Gasnikov received his academic credentials from the Moscow Institute of Physics and Technology (State University). He earned his Bachelor's degree in Applied Mathematics and Physics in 2004, followed by a Master's degree in the same specialty in 2006. He completed postgraduate studies at MIPT from 2006-2007, earned his Candidate of Physical and Mathematical Sciences degree in 2007, was awarded the academic title of Associate Professor in 2011, and ultimately received his Doctor of Physical and Mathematical Sciences degree in 2016 with a dissertation on 'Efficient Numerical Methods for Finding Equilibria in Large Transport Networks.' Gasnikov's research focuses on convex optimization, mathematical modeling of traffic flows, and Markov processes. His work bridges theoretical mathematics with practical applications in optimization algorithms and transportation science. He has made significant contributions to developing efficient numerical methods for optimization problems, particularly in the context of large-scale networks and stochastic settings. His research has evolved from traditional optimization methods to more advanced techniques involving stochasticity, decentralization, and applications to machine learning problems. His publications demonstrate expertise in both theoretical analysis (establishing convergence rates, lower bounds) and practical algorithm development across multiple prestigious venues including Journal of Optimization Theory and Applications, SIAM Journal on Optimization, and top machine learning conferences like NeurIPS. Gasnikov has received recognition including a bonus for publication in international peer-reviewed journals (2019-2021) and has served as a member of the editorial board of the 'Siberian Journal of Computational Mathematics' since 2017. As a supervisor, Gasnikov has guided multiple doctoral candidates, including Alexander Ogaltsov, Titov A. A. (2023), and Tyurin A. I. (2020) for Candidate of Sciences degrees, and Dvurechensky P. E. (2020) for a Doctor of Science degree. His research has been supported by grants from the President of Russia (MD-1320.2018.1) and the Russian Foundation for Basic Research (18-31-20005 mol_a_ved). Gasnikov's work contributes significantly to the theoretical foundations of optimization algorithms that power modern artificial intelligence systems. His leadership in the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis positions him at the forefront of research connecting mathematical optimization with practical applications in machine learning and data science.

• Reinforcement Learning
• Stochastic Optimization

Daniil Nikolaevich Tyapkin is a Junior Research Fellow and Postgraduate Student at the National Research University Higher School of Economics (HSE), affiliated with the Faculty of Computer Science. He works within the Institute of Artificial Intelligence and Digital Sciences and the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis under the supervision of Alexey Alexandrovich Naumov. Education: 2021: Bachelor's degree in Applied Mathematics and Computer Science from HSE Currently in 2nd year of postgraduate studies with dissertation topic: "Randomized trial for reinforcement learning" Research Interests: His work focuses on reinforcement learning and stochastic optimization, including exploration strategies, generative flow networks, and theoretical analysis of learning algorithms. He develops efficient methods for complex decision-making problems with applications in AI and data science. Publications: His research appears in top venues (ICLR, NeurIPS, ICML, AISTATS) covering reinforcement learning, optimization, and probabilistic modeling. Recent works explore GFlowNets, entropy regularization, and high-probability bounds for learning algorithms. Awards & Honors: Letter of gratitude from HSE Faculty of Computer Science (2022) Publication bonus for List A journal articles (2023-2024) HSE Personnel Reserve - New Researchers category (2022-2023) Teaching & Advising: Teaches courses in Mathematical Statistics and Matrix Computations. No formal student advising mentioned. Laboratory Affiliation: Member of the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis, focusing on algorithmic development for machine learning challenges.