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• Analysis and transformation of programs
• Software Security
• Parallel and distributed computing technologies

Harutyun Ishkhanovich Avetisyan is a Professor and Head of the Basic Department "System Programming" at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE). He began his tenure at HSE in 2017 and brings 30 years of scientific and teaching experience to his role. Additionally, he serves as the Director of the Institute for System Programming of the Russian Academy of Sciences (ISP RAS), a position he has held since 2015. Avetisyan holds numerous prestigious academic distinctions, including being elected as an Academician of the Russian Academy of Sciences in 2019 and as a Corresponding Member in 2016. He earned his Doctor of Physical and Mathematical Sciences degree in 2012 and was awarded the academic title of Associate Professor in 2009. His educational background includes a specialty in "Applied Mathematics" from Yerevan State University (1993). His research focuses on three main areas: analysis and transformation of programs, software security, and parallel and distributed computing technologies. These interests are reflected in his extensive publication record and leadership in major research initiatives. His work bridges theoretical computer science with practical applications in cloud computing, secure data storage, and high-performance computing systems. Avetisyan's scholarly contributions demonstrate a consistent focus on system programming challenges, particularly in the areas of code analysis, optimization, and security. His recent publications indicate a growing interest in cloud computing paradigms, smart city infrastructure, and energy-efficient computing solutions. His research has significant implications for both academic theory and industrial applications in software development. Among his notable recognitions, Avetisyan was awarded the medal of the Order "For Merit to the Fatherland" 2nd degree in 2021 for his significant contributions to science and dedicated service. He also serves on the editorial boards of several prestigious journals including "Programming" (since 2015) and "Proceedings of the Institute for System Programming of the RAS" (since 2010). Throughout his career, Avetisyan has led and participated in numerous research grants funded by the Ministry of Education and the Russian Foundation for Basic Research. His professional trajectory shows steady progression from postgraduate studies (1997-2000) to research fellow (2000-2002), deputy director of ISP RAS (2002-2015), and ultimately director of the institute (2015-present). At HSE, Avetisyan teaches courses in parallel programming and mentor seminars for master's students in Software Engineering. His teaching philosophy emphasizes the integration of cutting-edge research with practical software development skills, preparing students for careers at the forefront of computer science.

Khritankov Anton SergeevichView profile

Associate Professor

• Machine Learning
• Software Engineering
• MLOps
• +3 more

Khritankov Anton Sergeevich is an Associate Professor at the Faculty of Computer Science , National Research University Higher School of Economics (HSE) , where he started working in 2021. He holds a Candidate of Physical and Mathematical Sciences (2010) and a Master's degree (2007) and Bachelor's degree (2005) in Applied Mathematics and Physics from the Moscow Institute of Physics and Mathematics (State University) . Research Interests include machine learning , software engineering , MLOps , metamorphic testing , and feedback loops in ML systems . His work focuses on automating and ensuring reproducibility in data science, with a particular emphasis on blockchain verification and hidden feedback mechanisms that cause concept drift in AI systems. Publication Trends reveal a strong focus on MLOps platforms (2025), metamorphic testing for AI/ML systems (2024–2022), blockchain verification (2022–2021), and feedback loop modeling (2021–2020). His recent work addresses challenges in distributed computing and state registration of software developed with the AI Center project teams at HSE. Scientific Awards include a Bonus for publication in a List A journal (2024–2025) . Additional Contributions involve developing the SmartMLOps platform (2024–2025), co-authoring state-registered software frameworks (2024), and organizing roundtable discussions on reproducibility in data science (2021). He has taught Advanced Software Design to Master's students in Software Engineering since 2021.

• medical informatics
• image analysis and processing
• medical information systems
• +6 more

Oleg Stanislavovich P'yanykh is a Professor in the Department of Data Analysis and Artificial Intelligence at the Faculty of Computer Science, National Research University Higher School of Economics (HSE) in Moscow. He has been working at HSE since 2012 with 13 years of scientific and teaching experience. P'yanykh maintains active roles as a Guest Editor for both the American Journal of Roentgenology (since 2011) and Pattern Recognition (since 2010), and serves as a permanent member of the International DICOM Committee working group. His educational background includes a PhD in Computer Science from Louisiana State University (1998), an MS with honors in Applied Mathematics and Physics from Moscow State University (1994), and a Diplôme d'Etudes et de Recherches in Philosophy from French University College, Moscow State University and Sorbonne University (1994). P'yanykh's research spans medical informatics, image analysis and processing, medical information systems and standards (particularly DICOM and PACS), computer-aided diagnostics, teleradiology, machine learning, and control theory. His work bridges computer science with practical medical applications, focusing on improving medical imaging systems and data analysis. His publication record shows consistent contributions from 1997 through 2024, with recent work emphasizing scheduling algorithms, machine learning interpretability, human knowledge modeling, and medical image quality assessment. His research demonstrates a clear trajectory from foundational signal processing work to increasingly applied medical informatics solutions. Bonus for publication in an international peer-reviewed scientific journal (2019-2021) Bonus for publication in an international peer-reviewed scientific journal (2017-2018) Bonus for an article in a foreign peer-reviewed journal (2013-2015) P'yanykh has supervised student research including Viktor Sergeevich Lopatin's bachelor's thesis on 3D medical image processing and Ksenia Dmitrievna Loginova's master's thesis on medical image quality assessment. He has taught courses including Big Data and Machine Learning in Healthcare across multiple academic years (2020-2026) and Medical Informatics (2020-2022), reflecting his focus on applying computational methods to healthcare challenges.

Denis Vladimirovich KapulinView profile

Associate Professor

• Space Instrumentation
• Satellite Navigation Systems
• Radio-Electronic Equipment Design
• +4 more

Denis Vladimirovich Kapulin is an Associate Professor at the School of Space and Information Technologies, Siberian Federal University, holding the academic title of доцент (Associate Professor) with a Candidate of Technical Sciences degree in technical sciences. His work spans multiple departments related to radio-electronic systems and space instrumentation, with an office located at Kirensky street, 26B, building № 17 (F), room 2-20a. He serves as Acting Director of a research unit focused on space instrumentation and navigation systems. Dr. Kapulin's research interests center around space instrumentation, satellite navigation systems, radio-electronic equipment design, and production optimization. His work bridges theoretical research with practical applications, particularly in developing miniature band-pass microwave filters, angular satellite navigation equipment, and automated production planning systems. He has made significant contributions to both aerospace engineering and manufacturing optimization fields, with numerous patents reflecting his practical approach to solving engineering challenges. His publication trends show consistent research output with 15+ publications annually, demonstrating expertise across multiple domains including satellite navigation, production planning, and radio-electronic equipment design. Recent work focuses on digital transformation in manufacturing, augmented reality applications for predictive maintenance, and optimization of small-batch production systems. Scientific Awards and Recognition: Laureate of the award for young talents of the head of Krasnoyarsk city for achievements in scientific and educational activities Laureate of the award from JSC AKC "International Financial Club" for contributions to space instrumentation science Expert in the scientific and technical field of FSBSI NII RINKTSE Member of the expert council of the Krasnoyarsk regional innovation and technology business incubator Dr. Kapulin has secured multiple significant research grants from the Russian Ministry of Education and Science, including projects on high-tech production of miniature band-pass filters (2017-2019), development of highly selective microwave filters (2017-2019), creation of angular satellite navigation equipment (2016-2017), and architecture development for System-on-Chip navigation receivers (2015-2017). His collaborative research involves extensive work with colleagues like Oleg Drozd and Polina Russkikh across multiple laboratories focused on radio-electronic systems and space technologies. The research team he participates in maintains strong connections with industry partners in the aerospace and radio-electronic sectors, facilitating technology transfer from academic research to practical applications. Current projects focus on digital transformation of manufacturing processes, advanced satellite navigation systems, and optimization of production planning for small-batch manufacturing environments.

• 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.

• Global Optimization
• Augmented Reality
• Computational Biology
• +3 more

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

• Real-Time Operating Systems
• Scheduling Algorithms
• System Programming
• +5 more

Sergey Vadimovich Zelenov serves as an Associate Professor at the Faculty of Computer Science, National Research University Higher School of Economics (HSE), working within the Basic Department "System Programming" of the Institute for System Programming named after V.P. Ivannikov of the Russian Academy of Sciences (ISP RAS). He joined HSE in 2017 and brings 26 years of scientific and teaching experience to his position. Dr. Zelenov earned his Candidate of Physical and Mathematical Sciences degree in 2001 and completed his specialist education at Lomonosov Moscow State University in 1998, specializing in Mathematics and Applied Mathematics with the qualification of Mathematician. His research focuses on Real-Time Operating Systems, scheduling algorithms for periodic tasks, software and hardware reliability assessment, and system security analysis. His work demonstrates particular expertise in developing scheduling criteria for conflict-free execution of periodic tasks in real-time environments and applying stochastic methods to analyze complex hardware-software systems. He has made significant contributions to AADL (Architecture Analysis & Design Language) modeling and visualization techniques. Dr. Zelenov's publication record shows consistent scholarly output with multiple publications in reputable journals and conference proceedings between 2017-2019, primarily in the field of real-time systems and system programming. His work frequently appears in the Proceedings of the Institute for System Programming of the Russian Academy of Sciences and international venues like IEEE conferences. Gratitude from the Faculty of Computer Science, HSE (September 2020) As an educator, Dr. Zelenov teaches Applied Systems Analysis for Master's students in Software Engineering at HSE, a course he has consistently delivered across multiple academic years from 2020/2021 through 2025/2026. His professional affiliation with the Institute for System Programming of the Russian Academy of Sciences (ISP RAS) dates back to 1997, indicating a long-standing commitment to system programming research. His scholarly identity is established through multiple identifiers including ORCID (0000-0003-0446-0541), ResearcherID (H-2069-2014), and Scopus AuthorID (10039123900), reflecting his integration into the international academic community.

• Big Data Processing
• Computational Science
• Distributed Computing
• +3 more

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

• nonparametric statistics
• Statistics of random processes
• numerical methods of stochastics
• +5 more

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.