Find Academic Supervisors

• 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.

Shilov Valery VladimirovichView profile

Professor

• Parallel Computing
• Parallel Architectures
• History of Informatics
• +3 more

Valery Vladimirovich Shilov is a Professor at the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE University) in Moscow. He began working at HSE in 2015 and has extensive scientific and teaching experience spanning several decades across various prestigious institutions in Russia. His educational background includes a degree in Applied Mathematics from Lomonosov Moscow State University (1976), qualification as a Lawyer from the Higher Institute of Management (2001), and the academic title of Candidate of Technical Sciences (1989). His professional journey began at Central Research Institute 45 of the Ministry of Defense of the USSR (1976-1989), continued at the USSR Academy of Sciences Computing Center (1989-1997), and included professorial positions at MATI - Russian State Technological University named after K.E. Tsiolkovsky (1997-2015), where he also served as Head of the Department of Design of Computing Complexes and Deputy Dean of the Engineering and Economic Faculty for Science. Professor Shilov's research focuses on parallel computing, parallel architectures, and the history of informatics, with particular emphasis on Soviet and Russian computing history. His scholarly output demonstrates deep engagement with historical aspects of computing technology, including early mechanical calculators, Soviet-era computer development, and the evolution of computing in Eastern Europe. His publications reveal a consistent pattern of examining how computing technologies evolved within specific historical, political, and economic contexts, with special attention to Russian and Soviet contributions. His numerous scientific awards reflect significant recognition in his field, including honors from the Ministry of Education and Science of Russia, the Russian Section of IEEE Computer Society, the Polytechnic Museum, and multiple awards from HSE University. His leadership in organizing academic conferences, particularly those focused on the history of computing in Russia and former Soviet states, has been instrumental in preserving and advancing knowledge in this specialized area. Professor Shilov has supervised multiple PhD students focusing on software engineering, processor architecture, and parallel computing algorithms. His grant activities include leading an RFBR project on the history of domestic computing and informatics (1946-1960), demonstrating his commitment to documenting and analyzing the historical development of computing in Russia. He remains actively involved in academic service as a member of editorial boards for several journals and as a participant in numerous international conferences.

• programming technologies
• architecture-independent parallel programming
• evolutionary software development
• +3 more

Alexander Ivanovich Legalov is a Professor at the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE). He has been working at HSE since 2020, bringing 47 years of scientific and teaching experience to his role. Prior to joining HSE, he served as a Professor at the Siberian Federal University from 2006 to 2020. Professor Legalov earned his Candidate of Technical Sciences degree in 1983 and was awarded the academic title of Associate Professor in 1987. He achieved the Doctor of Technical Sciences degree in 2005 and was granted the academic title of Professor in 2007. His educational background includes a specialization in "Design and production of radio equipment" with the qualification of "Engineer-designer-technologist of radio equipment" from the Krasnoyarsk Polytechnic Institute in 1978. Professor Legalov's research focuses on programming technologies, particularly architecture-independent parallel programming and evolutionary software development. His work explores innovative approaches to parallel programming, including procedural-parametric programming paradigms and functional-dataflow models. He has made significant contributions to language design and transformation, particularly in extending C language capabilities and developing tools for parallel program development. His research demonstrates a consistent trajectory toward creating more flexible and efficient programming paradigms that can adapt to different architectural constraints. HSE University Honorary Diploma (May 2025) Gratitude from the Faculty of Computer Science, National Research University Higher School of Economics (August 2022) Badge of honor "For the development of students' research work" (October 2006) Professor Legalov actively supervises student research, currently guiding Kosov P.V. in dissertation research for the degree of candidate of sciences on "Language and instrumental means of evolutionary development of programs based on the procedural-parametric programming paradigm." He teaches courses on Computer Architecture and Operating Systems for second-year students in the Software Engineering bachelor's program at HSE. Professor Legalov participates in editorial boards of several scientific journals, including "Systems Management, Communications and Security" since 2017, and "Reports of the Russian Academy of Higher School Sciences" since 2010. His technical contributions include multiple registered software programs for functional-dataflow parallel programming languages.

• 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

Belevantsev Andrey AndreevichView profile

Professor

• Analysis and optimization of programs
• Static analysis
• Parallel programming

Belevantsev Andrey Andreevich is a Professor at the Faculty of Computer Science, National Research University Higher School of Economics, affiliated with 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 has been working at HSE since 2021, and also holds positions at Lomonosov Moscow State University (since 2011) and ISP RAS (since 2004). Education: 2018: Doctor of Physical and Mathematical Sciences 2003: Moscow State University named after M.V. Lomonosov, specialty 'Applied Mathematics and Computer Science', qualification 'Mathematician. Systems Programmer' Research interests focus on program analysis and optimization, static analysis techniques, and parallel programming. His work emphasizes code reliability through static analyzers, taint analysis, and vulnerability detection in software systems. Publications include studies on static analysis for code defects, taint analysis accuracy, Kotlin programming language evaluation, and vulnerability detection in the Svace analyzer. These reflect expertise in software engineering, security, and programming language design. Awards: 2025: Elected to membership in Russian Academy of Sciences Teaching involves courses on Algorithms and Algorithmic Languages for Software Engineering bachelor's students at HSE's Faculty of Computer Science since 2021.

• computer security
• compiler technologies
• parallel programming
• +2 more

Padaryan Vartan Andronikovich serves as an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE University) since 2022. He concurrently holds positions at the Basic Department "System Programming" of the Institute for System Programming named after V.P. Ivannikov of the Russian Academy of Sciences (ISP RAS), as Associate Professor at Moscow State University's Faculty of Computational Mathematics and Cybernetics since 2010, and as Head of the Laboratory of Reverse Engineering of Binary Code at ISP RAS since 1999. Since 2018, he has chaired Subcommittee 4 "Secure Software Development" of Technical Committee for Standardization 362 "Information Security". Education: 2005: Candidate of Physical and Mathematical Sciences 2000: Specialty in "Applied Mathematics" from Moscow State University, qualification "Mathematician. Systems Programmer" Dr. Padaryan's research centers on binary code analysis and security applications. His expertise spans computer security, compiler technologies, parallel programming, binary code analysis, and emulation and virtualization. His work addresses critical challenges in understanding and securing software systems when source code is unavailable, with particular focus on reverse engineering techniques, vulnerability detection, and secure software development methodologies. His research bridges theoretical computer science with practical security applications, contributing to innovative tools for binary code analysis. His publication record reveals a strong trajectory in binary code analysis, with consistent contributions to algorithm extraction, intermediate representation recovery, and security vulnerability detection. The interdisciplinary nature of his work combines programming languages, software engineering, and cybersecurity to develop practical solutions for analyzing and securing software systems. His research has evolved to address increasingly complex security challenges, particularly in network interface testing and data leakage detection in binary environments. Dr. Padaryan actively contributes to academic and professional communities through teaching and leadership roles. He teaches "Computer Architecture and Assembly Language" for Software Engineering bachelor's students at HSE University across multiple academic years. His laboratory leadership at ISP RAS has fostered significant research output, while his standardization committee role demonstrates influence in shaping secure software development practices in Russia. His laboratory work focuses on developing advanced security tools including the "LAKMUS" system for labeled data analysis and the "PROTOSPHERE" system for network traffic analysis. These tools represent practical applications of his research in real-world security scenarios, enabling security professionals to detect vulnerabilities and analyze software behavior without access to source code.

Fedor Aleksandrovich BuzaevView profile

Lecturer

• Physics-informed neural networks
• Computer Vision
• Machine Learning
• +3 more

Fedor Aleksandrovich Buzaev is a Lecturer and Junior Research Fellow at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), where he also serves as a postgraduate student in his second year of study. He began his work at HSE in 2024 and is affiliated with both the Institute of Artificial Intelligence and Digital Sciences and the Department of Big Data and Information Retrieval. His educational background includes a Master's degree in Applied Mathematics and Computer Science from HSE (2023) and a Bachelor's degree in Electric Power Engineering and Electrical Engineering from MPEI (2020). Buzaev's research focuses on the intersection of physics and machine learning, particularly in developing physics-informed neural networks for solving complex scientific problems. His work spans several key areas including climate prediction, computational physics, and the solution of partial differential equations. He has made significant contributions to optimizing neural network architectures for scientific computing applications, with a particular emphasis on solving the nonlinear Schrödinger equation and other physics-based problems. His professional experience includes working as a deep learning researcher at Zvuk.com (since December 2024), a junior researcher at the Research and Educational Laboratory of Big Data Analysis Methods (since June 2023), and previous positions at Huawei RRI, JuniStat, and EdisonLab. He teaches the "Machine Learning 1" course at HSE and has expertise in multiple programming languages and research methodologies. Buzaev is currently working on his dissertation with the approved topic "Climate prediction using physically-informed neural networks" under the supervision of Fedor Dmitrievich Ratnikov. His research demonstrates a strong commitment to advancing the application of machine learning techniques in scientific domains, particularly where physical constraints and equations guide the learning process.