Find Academic Supervisors

• measure theory
• Gaussian measures
• measures on infinite-dimensional spaces
• +4 more

Egor Dmitrievich Kosov is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), where he has been working since 2016. He also serves as a Senior Research Fellow at the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis within HSE's Institute of Artificial Intelligence and Digital Sciences. Additionally, he holds positions as Senior Researcher at the Steklov Mathematical Institute's Department of Function Theory and Junior Researcher at the Laboratory of Multidimensional Approximation and Applications. Dr. Kosov earned his Candidate of Physical and Mathematical Sciences degree from Lomonosov Moscow State University in 2018, where he also completed postgraduate studies specializing in Mathematics and Mechanics with a qualification as Researcher. His research focuses on measure theory , particularly Gaussian measures , measures on infinite-dimensional spaces , logarithmically concave measures , and measurable polynomials . Kosov's work bridges theoretical mathematics with applications in stochastic analysis, exploring the regularity properties of distributions and developing discretization techniques for functional norms. His research has significant implications for understanding complex probabilistic structures in high-dimensional spaces. Analysis of Kosov's recent publications reveals a strong focus on polynomial mappings of random variables, particularly Gaussian and log-concave distributions. A significant portion of his research addresses discretization problems—developing methods to approximate continuous mathematical structures through discrete sampling. His publications demonstrate growing recognition in the mathematical community, with appearances in prestigious journals across multiple subfields of mathematical analysis. Letter of gratitude from the First Vice-Rector of HSE (March 2023) Letter of Gratitude from the Faculty of Computer Science at HSE (September 2019) Bonus for publication in List A journals (2023-2024) Multiple bonuses for international peer-reviewed publications (2019-2023) Best Teacher award (2018) Moscow Mathematical Society award (2021) At HSE, Kosov teaches Mathematical Analysis, Probability Theory, and Functional Analysis to undergraduate students in the Applied Mathematics and Computer Science program across both the Faculty of Computer Science and the Faculty of Economic Sciences. His teaching spans multiple academic years (2020-2023), demonstrating his commitment to education alongside research. Dr. Kosov is actively involved in research teams including the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis at HSE and the Laboratory of Multidimensional Approximation and Applications. His work connects with the broader mathematical community through collaborations with researchers such as V.I. Bogachev, V.N. Temlyakov, and others, contributing to Russia's strong tradition in mathematical analysis and probability theory.

• Databases
• Software Engineering
• Data Warehousing
• +6 more

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.

• Probability Theory
• Mathematical Statistics
• Combinatorial Optimization
• +2 more

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
• +1 more

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
• +2 more

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).

Danilov Alexey AndreevichView profile

Research Fellow

• Software Engineering
• Decision Support Systems
• Distributed Software Systems
• +2 more

Dr. Danilov Alexey Andreevich is a graduate student and Junior Research Fellow at the Faculty of Computer Science, Department of Software Engineering, National Research University Higher School of Economics (HSE University). He joined HSE in 2025 and is affiliated with the Research and Educational Laboratory of Cloud and Mobile Technologies. Education: Master's (2023) and Bachelor's (2021) in Software Engineering from HSE University His research focuses on software engineering, particularly decision support systems for distributed software systems architecture. He actively contributes to academic development through postgraduate study and teaching activities, including courses on industrial server application deployment and software engineering fundamentals. He is part of the Research and Educational Laboratory of Cloud and Mobile Technologies, where he explores modern software design paradigms and systematization of knowledge in distributed computing environments.

• Algorithm Analysis
• Complex Networks
• Supercomputer Modeling
• +3 more

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
• +7 more

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.

• optimal transport
• probability theory
• mathematical statistics
• +2 more

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.

• convex optimization
• mathematical modeling of traffic flows
• Markov processes
• +3 more

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.

• federated learning
• Gradient-free algorithms
• machine learning
• +1 more

Alexander Vladimirovich Lobanov serves as a Research Fellow at the Faculty of Computer Science, National Research University Higher School of Economics (HSE University) in Moscow. Affiliated with the Institute of Artificial Intelligence and Digital Sciences and the Laboratory of Theoretical Foundations of Artificial Intelligence Models since 2024, he operates under supervisor Puchkin N. A. from Pokrovsky Boulevard Building 11, Office T926. His research centers on federated learning architectures and gradient-free optimization algorithms, with deep specialization in convex optimization frameworks for machine learning systems. Lobanov develops novel black-box optimization techniques using kernel approximation methods to solve complex stochastic problems where gradient information is unavailable or computationally prohibitive. His 2024 publication in the Journal of Optimization Theory and Applications exemplifies his focus on zero-order accelerated stochastic methods, addressing critical challenges in derivative-free optimization. This work advances theoretical foundations for artificial intelligence systems requiring efficient computation in high-dimensional spaces. As an active member of the Laboratory of Theoretical Foundations of Artificial Intelligence Models, Lobanov collaborates on theoretical AI research with flexible scheduling. His professional identifiers include ORCID 0000-0003-1620-9581, ResearcherID IFR-8600-2023, and Scopus AuthorID 57219489070.

Agamirzyan Igor RubenovichView profile

Professor

• informatics
• programming languages
• operating systems
• +4 more

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.

• financial econometrics
• functional analysis
• probability theory
• +4 more

Borzykh Dmitry Alexandrovich is an Associate Professor at the National Research University Higher School of Economics , affiliated with the Department of Applied Economics under the Faculty of Economic Sciences . He also serves as a Research Fellow at the International Laboratory of Stochastic Analysis and its Applications . With 18 years of scientific and teaching experience since joining HSE in 2006, he teaches advanced courses in probability theory, mathematical statistics, and econometrics at both undergraduate and graduate levels. Education: Candidate of Physical and Mathematical Sciences (2022, HSE), Master's in Economics (2006, HSE), Bachelor's in Economics (2004, HSE) Key research areas: financial econometrics , stochastic analysis , structural breaks in time series , and stochastic volatility models His recent publications focus on stochastic processes , structural break detection , and quantile function applications across financial and economic modeling. He has received multiple institutional awards, including Best Teacher (2014, 2016–2025) and formal gratitudes from HSE departments (2019, 2022). He provides consultations via email and holds office hours at Pokrovsky Boulevard campus (room S517).

• Spatial Econometrics
• Bayesian Methods
• Microeconometrics
• +5 more

Olga Anatolyevna Demidova is a Professor at the National Research University Higher School of Economics (HSE), working within the Faculty of Economic Sciences and the Department of Applied Economics. She also serves as Head of the Scientific and Educational Laboratory of Spatial-Econometric Modeling of Socio-Economic Processes in Russia. With over 35 years of scientific and teaching experience, including 27 years at HSE since 1998, Professor Demidova has established herself as a leading expert in spatial econometrics and regional economic analysis in Russia. 2022: Doctor of Economics from National Research University Higher School of Economics 2012: Academic title of Associate Professor 1999: Master's degree in Economics from State University - Higher School of Economics 1995: Candidate of Physical and Mathematical Sciences from A.A. Dorodnitsyn Computing Center of the Russian Academy of Sciences 1989: Specialist in Mathematics from Lomonosov Moscow State University, Faculty of Mechanics and Mathematics Professor Demidova's primary research interests include spatial econometrics, Bayesian approaches, microeconometrics, nonparametric estimation methods, and comparative economic research. Her work focuses on analyzing regional economic processes in Russia, with particular attention to spatial dependencies, regional disparities, and the effects of economic policies across different Russian regions. She has developed specialized methodologies for spatial-econometric modeling that have been widely applied in Russian economic research. Professor Demidova's recent publications (2021-2025) demonstrate a consistent focus on spatial-economic analysis of Russian regions. Her research examines monetary policy transmission mechanisms, regional government spending effects, income inequality impacts, and electoral patterns through the lens of spatial econometrics. A notable trend is her increasing focus on crisis effects, particularly analyzing the impact of the COVID-19 pandemic on household consumption across Russian regions. Her work consistently applies advanced spatial modeling techniques to understand regional economic dynamics in Russia's heterogeneous economic landscape. 2022: Honorary title "Honored Worker of the Sphere of Education of the Russian Federation" 2018: "Recognition - 20 Years of Successful Work" Medal from HSE 2016: Honorary Certificate from Higher School of Economics 2013 & 2012: Gratitude from Higher School of Economics 2022-2025: Bonus for defending doctoral dissertation 2023-2025: Bonuses for publications in journals from List B Professor Demidova has supervised numerous graduate students, including nine doctoral candidates (as of 2025), with several having successfully defended their dissertations. Her current PhD students are working on topics related to electoral preferences, business performance, unemployment, mortgage rates, and regional inequality. She has led multiple research grants, including a 2020-2021 RFBR grant project "Modeling the mutual influence of Russian regions and assessing the effectiveness of government programs using spatial-econometric methods." Her research has been supported by various HSE individual research projects since 2010, focusing on spatial effects in regional economic analysis. As Head of the Scientific and Educational Laboratory of Spatial-Econometric Modeling of Socio-Economic Processes in Russia, Professor Demidova leads a research team that develops and applies spatial-econometric methodologies to analyze regional economic processes in Russia. The laboratory conducts research on regional convergence, electoral behavior, monetary policy transmission, and the effects of government spending across Russian regions. In 2024, the laboratory initiated a "Mirror Laboratory" project with the Ufa University of Science and Technology to enhance spatial-econometric models considering hierarchical data structures and heterogeneous process dynamics.