جست‌وجوی استاد و پژوهشگر

• Mathematical Physics
• Fluid Dynamics
• Wave Theory
• +۴ مورد دیگر

Anatoly A. Abrashkin serves as Professor at HSE University's Nizhny Novgorod campus within the Faculty of Informatics, Mathematics, and Computer Science, Department of Mathematics. He has been affiliated with HSE University since 2005 and holds the position of Professor since 2014. His educational background includes a Degree in Radio Physics and Electronics (1981) from Lobachevskiy Gorky State University, Doctor of Sciences in Physical and Mathematical Sciences (2000), and Associate Professor qualification (2001). Abrashkin's research spans mathematical physics with emphasis on fluid dynamics, wave theory, and hydrodynamics. His work develops exact analytical solutions for complex wave phenomena including Gerstner waves, edge waves, and geophysical fluid flows. He investigates nonlinear wave dynamics in various contexts from deep water to equatorial currents, often employing Lagrangian descriptions and Cauchy invariants. Analysis of his recent publications reveals consistent focus on exact solutions in hydrodynamics, particularly generalizations of classical wave models. His work bridges theoretical mathematics with geophysical applications, showing strong emphasis on vorticity effects, nonlinear wave propagation, and connections between different wave solution frameworks. Best Teacher Award (2016-2017) Winner of HSE University Best Russian Research Paper Competition (2024) Abrashkin teaches Mathematical Physics, Philosophy of Science, and Probability Theory courses across Mathematics and Software Engineering programs. His conference presentations at venues like EGU-2016 and Russian mechanics congresses demonstrate active engagement with the fluid dynamics research community. While specific student names aren't listed, he supervises term and thesis papers as indicated in his profile.

• Diagnostic Features
• Testing Electronic Means
• Charging of Polymers
• +۳ مورد دیگر

Andrey E. Abrameshin is a Professor and Deputy Director at the HSE Tikhonov Moscow Institute of Electronics and Mathematics , affiliated with the School of Electronic Engineering . He has been at HSE University since 2012, contributing to research in spacecraft charging, polymer conductivity, and aerospace material reliability. His academic background includes a Candidate of Sciences (PhD) in Sociological Sciences (1997) and a Degree from Moscow Institute of Electronic Engineering (1986). Education: Candidate of Sciences (PhD) in Sociological Sciences (1997) Degree from Moscow Institute of Electronic Engineering (1986) Research Interests His work focuses on radiation-induced conductivity in polymers, spacecraft internal charging , low-energy electron effects , and dielectric material reliability . He explores charge transport mechanisms, ESD mitigation, and macro-modeling for spacecraft systems. Recent Publications Trends His 2013–2022 articles emphasize polymer conductivity under radiation , spacecraft material simulation , and macro-modeling of electrical systems . Key subtopics include dielectric composites , electron trapping , charge distribution , and radiation-resistant electronics for aerospace applications. Labs & Projects Abrameshin leads research at the Laboratory of Space Vehicles and Systems' Functional Safety , collaborating on satellite development (e.g., CubeSX-HSE) and spacecraft electronics reliability. He contributed to Russia's spacecraft charging studies and participated in international conferences like Spacecraft Charging Technology Conference.

• programming technologies
• architecture-independent parallel programming
• evolutionary software development
• +۳ مورد دیگر

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.

Makarov Sergey Lvovichمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence
• Mobile Development
• +۶ مورد دیگر

Sergey Lvovich Makarov serves as an Associate Professor in the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE), where he has been employed since 2012. With 21 years of scientific and teaching experience, he holds formal academic credentials including a Candidate of Technical Sciences degree (awarded in 2009) from the Moscow State Institute of Electronics and Mathematics, specializing in Automated Design Systems. His research interests span software engineering, artificial intelligence, mobile development, Internet of Things technologies, automatic text processing, and an unusual interdisciplinary focus on fashion informatics where he applies computational methods to analyze symbolic systems in costume design. This dual expertise is reflected in his publications that bridge technical computer science with applications in fashion industry analysis. Makarov's scholarly output demonstrates a consistent trajectory from foundational work in intelligent information processing systems toward increasingly sophisticated applications in mobile development, IoT ecosystems, and fashion data analysis. His recent publications (2018-2023) focus heavily on practical hardware-software integration through Arduino and Raspberry Pi platforms, while maintaining his distinctive research thread analyzing symbolic systems in fashion design through computational methods. Gratitude from HSE University (May 2024) Gratitude from the Department of Software Engineering, HSE (November 2023) Medal 'Recognition - 10 years of successful work' (December 2022) Gratitude from the Faculty of Computer Science, HSE (September 2019) Academic Work Allowance (2014-2018) As an educator, Makarov supervises student research including Potapenko Vladimir Andreevich's 2013 qualification work on CRM system development. He has received multiple Academic Work Allowances recognizing his teaching excellence. His research includes significant grant-funded projects, notably serving as responsible executor for the R&D project 'Intelligent system for searching the Internet for information analogues of text documents' (2010-2011) and participating in research on decision support systems (2012). His scholarly contributions include numerous publications, research grants, and participation in conferences focusing on AI applications and intelligent systems. Makarov maintains active involvement in curriculum development, particularly in mobile application development and IoT technologies, as evidenced by his current teaching assignments for the 2025/2026 academic year which include specialized courses in Android development using both Kotlin and Java, Manufacturing Data Collection and Analytics, and IoT Ecosystems.

• Higher Education System
• Education Statistics
• Quantitative Data Analysis
• +۴ مورد دیگر

Melikyan Alisa Valerievna is an Associate Professor at the Faculty of Computer Science, Department of Software Engineering at the National Research University Higher School of Economics (HSE). She has been working at HSE since 2008 with 16 years of scientific and teaching experience. Currently, she serves as Academic Director of the educational program "Product approach and data analytics in HR management". PhD in Educational Sciences (2019) from HSE Postgraduate studies in Sociology of Management (2009) Dual Master's degrees in Management Strategy from Université Paris-Est Créteil and Management from HSE (2007) Bachelor's degree in Management from HSE (2005) Dr. Melikyan specializes in higher education research with focus areas including the higher education system, education statistics, quantitative data analysis, international education markets, university-business cooperation, data science, and data analytics. Her research combines statistical methods with educational policy analysis, particularly examining how Russian universities operate in international markets and collaborate with business entities. She has developed expertise in applying data science techniques to educational research questions. Her recent publications demonstrate a consistent focus on analyzing Russian higher education through statistical methods, with particular attention to university internationalization, export activities, and collaboration with business. The research shows progression from broader system analysis to more specific examinations of university-business cooperation, IT specialist training, and data-driven approaches to understanding higher education dynamics. Her scientific achievements have been recognized through various awards: Gratitude of the first pro-rector of HSE (January 2024) Medal "Recognition - 15 years of successful work" HSE (December 2022) Gratitude of the Faculty of Computer Science HSE (September 2020) Rector's personal allowance (2017-2018) Academic work allowance (2013-2017) Named "Best teacher" for 2025 and 2019-2022 Dr. Melikyan has led research projects on improving procurement legislation (2022-2024), methodology for assessing regional education systems (2013-2014), database harmonization for Russian publications (2012-2013), and bibliometric analysis of Russia's position in global science (2011). She has been actively involved in developing and teaching courses related to data analysis, programming, and quantitative methods for social sciences.

• Petri nets
• Multi-agent systems
• Distributed systems
• +۴ مورد دیگر

Roman Aleksandrovich Nesterov is an Associate Professor at the Department of Software Engineering, Faculty of Computer Science, National Research University Higher School of Economics (HSE). He has been with HSE since 2015 and heads the Research and Educational Laboratory of Process-Oriented Information Systems (POIS). His educational background includes a PhD (2022) and Master's degree (2017) from HSE, both in Computer Science and Software Engineering. His research focuses on: Formal methods for distributed system modeling Petri nets and concurrency theory Process mining and event log analysis Multi-agent systems and business process modeling Compositional approaches to system verification His publications demonstrate consistent focus on process discovery algorithms, model verification techniques, and applications of Petri nets in distributed systems. Recent works emphasize hierarchical modeling and architecture-aware solutions for multi-agent environments. Awards and Honors: Golden HSE Prize 2019 (Silver Chick nomination) Multiple 'Best Teacher' awards (2020-2025) Research publication bonuses HSE Faculty of Computer Science Gratitude (2023) He leads the POIS laboratory where he conducts research on automated synthesis of multi-agent system models. His teaching includes undergraduate algorithms courses and graduate-level formal methods in software engineering.

Khritankov Anton Sergeevichمشاهده پروفایل

دانشیار

• Machine Learning
• Software Engineering
• MLOps
• +۳ مورد دیگر

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.

• Control Systems
• Robotics
• Artificial Intelligence
• +۳ مورد دیگر

Vladimir Prokhorovich is a Professor at the Faculty of Control Systems and Robotics, ITMO University. He serves as an academic expert and holds a Doctor of Sciences (DSc) degree. Research Focus: Control Systems, Robotics, Artificial Intelligence, Mechanical Engineering, Electrical Engineering, and Computer Science Contact: +7 (812) 640-66-92

Alexey Konstantinovich Shaitanمشاهده پروفایل

استاد

• epigenetics
• nucleosomes
• structural bioinformatics
• +۳ مورد دیگر

Alexey Konstantinovich Shaitan is a Professor at the Department of Big Data and Information Retrieval and a Leading Researcher at the International Bioinformatics Laboratory within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE). He also serves as a Leading Researcher at the Department of Bioengineering, Faculty of Biology, Lomonosov Moscow State University since 2012. With 17 years of scientific and teaching experience, Shaitan holds the prestigious titles of Professor of the Russian Academy of Sciences and Corresponding Member of the Russian Academy of Sciences (both awarded in 2022). Education: 2022: Professor of the Russian Academy of Sciences 2022: Corresponding Member of the Russian Academy of Sciences 2021: Doctor of Physical and Mathematical Sciences from Lomonosov Moscow State University 2010: Candidate of Physical and Mathematical Sciences 2007: Specialty in "Physics of Condensed Matter," qualification "Physicist" from Lomonosov Moscow State University Shaitan's research focuses on epigenetics, nucleosomes, and structural bioinformatics , bridging computational approaches with molecular biology to understand chromatin structure and function. His work spans from fundamental studies of nucleosome dynamics to applied research in drug discovery and disease mechanisms. He has made significant contributions to molecular dynamics simulations of nucleosomes and the application of AI in computational biology. Analysis of his recent publications reveals a strong trajectory in nucleosome structure and dynamics, epigenetic mechanisms, and computational methods development. His work demonstrates increasing integration of artificial intelligence with traditional bioinformatics approaches, particularly evident in his 2025 publications on AI in drug development. The interdisciplinary nature of his research connects physics, biology, and computer science to address complex biological questions. Scientific Recognition: Corresponding Member of the Russian Academy of Sciences (2022) Professor of the Russian Academy of Sciences (2022) Rector's personal allowance (2021-2022) Bonus for publication in a journal from List A (2025-2026) Shaitan actively contributes to academic education through teaching courses such as "Molecular Modeling" for both undergraduate and master's students at HSE. His international collaborations are evidenced by his previous visiting fellowship at the National Center for Biotechnology Information, National Institutes of Health, USA (2013-2017) and research position at Ulm University, Germany (2009-2011). He regularly participates in major conferences including the Ascona B-DNA Consortium meetings and the Moscow Conference on Computational Molecular Biology. As a key member of the International Bioinformatics Laboratory at HSE and the Department of Bioengineering at Moscow State University, Shaitan leads research at the intersection of computer science, biology, and physics. His laboratory work focuses on advanced computational techniques for understanding chromatin structure, DNA-protein interactions, and their implications for disease mechanisms and therapeutic development.

Korshunov Maxim Mikhailovichمشاهده پروفایل

دانشیار

• Superconductivity
• Quantum Physics
• Condensed Matter Physics
• +۷ مورد دیگر

Maxim Mikhailovich Korshunov is an Associate Professor and Head of the Department of Theoretical Physics and Wave Phenomena at the Institute of Engineering Physics and Radioelectronics, Siberian Federal University. He also serves as Chief Researcher at the Laboratory of Physics of Magnetic Phenomena, L.V. Kirensky Institute of Physics, FRC KSC SB RAS. With 23 years of experience in his specialty, he has established himself as a leading researcher in condensed matter physics and superconductivity. His educational background includes a PhD in Condensed Matter Physics (2004) and a D.Sc. in Condensed Matter Physics (2015) from the Kirensky Institute of Physics. In 2022, he was elected as a Corresponding Member of the Russian Academy of Sciences and in 2018 was awarded the academic title of Associate Professor in Theoretical Physics. Korshunov's research focuses on quantum macrophysics, specifically the description of quantum systems and manifestations of quantum properties at macroscopic scales. His work encompasses superconductivity, photophysical processes, nanosystems, quantum transport, and the structure and properties of complex systems and metalloorganic compounds. He has developed theoretical models for layered transition metal compounds, particularly examining the relationship between magnetism and unconventional superconductivity. Analysis of his recent publications reveals a strong focus on iron-based superconductors, cuprates, and quantum materials. His work frequently addresses spin-orbit coupling, electronic structure, superconducting order parameters, and the effects of doping and pressure on quantum materials. A significant portion of his research investigates the interplay between magnetism and superconductivity, particularly in iron pnictides and chalcogenides. Medal of the ORDER "FOR SERVICE TO THE FATHERLAND" 2nd degree (2024) Letter of thanks from the Russian Academy of Sciences (2023) Medal "For Impeccable Work and Distinction" of the Ministry of Education and Science (2022) Top Peer Reviewer 2019 Award, Publons — Clarivate Analytics (2019) Publons Peer Review Awards 2018 (2018) State Prize of Krasnoyarsk Krai in professional education (2012) Prize of the Siberian Branch of the Russian Academy of Sciences named after Academician L.V. Kirensky (2012) Korshunov has led multiple research grants, including projects funded by the Russian Foundation for Basic Research (RFBR) on "Spin fluctuations as a source of superconducting pairing in iron selenides" and "Effects of electronic correlations and multi-orbital physics in iron compounds and cuprates." His research has been supported by the Dynasty Foundation and the Russian Science Foundation. He has also contributed to educational development through numerous methodological materials for courses in statistical physics, quantum theory of solids, and field theory methods. As Head of the Department of Theoretical Physics and Wave Phenomena, Korshunov leads a research team investigating quantum phenomena in condensed matter systems. His laboratory focuses on theoretical modeling of superconducting and magnetic materials, with particular emphasis on iron-based superconductors and cuprates. The team employs advanced computational methods including cluster perturbation theory and ab initio calculations to understand the electronic structure and quantum properties of these materials.

Makarov Vladimir Aleksandrovichمشاهده پروفایل

استاد

• Metallogeny
• Exploration of Mineral Deposits
• Gold Mining
• +۵ مورد دیگر

Makarov Vladimir Aleksandrovich serves as Professor, Head of the Department of Geology of Deposits and Exploration Methods, and Director of the Institute of Mining, Geology and Geotechnology at Siberian Federal University (SFU). With 38 years of professional experience since 1980, he leads academic and research initiatives in mineral exploration while maintaining active teaching responsibilities in forecasting mineral deposits and metallogeny. His educational background includes: Mining Engineer-Geologist (1980) from Krasnoyarsk Institute of Non-Ferrous Metals Candidate of Geological and Mineralogical Sciences (1985) Doctor of Geological and Mineralogical Sciences (2004) Makarov's research centers on predictive metallogenic studies of non-ferrous and precious metals, geological revaluation of man-made mineral wastes, and ore flow management during mining operations. His work integrates field geology with technological solutions for gold recovery optimization and industrial waste reprocessing, particularly focusing on Siberian gold deposits and metallurgical byproducts in the Yenisei Ridge region. Analysis of his 9 most recent publications (2012-2017) reveals consistent focus on gold deposit exploration through geochemical and lithological analysis, waste stream valorization (slag dumps, tailings), and dynamic quality control systems. Key trends include computer-aided deposit prediction, germanium extraction from lignites, and environmental assessment of mining byproducts, demonstrating applied research bridging academic theory with industrial mineral processing challenges. As Chairman of Dissertation Council D 212.099.23 (VAK Order 1124/nk, 2015), he supervises 4 graduate students and leads research teams executing state contracts for entities including Norilsk Nickel and Polius Gold. His secured funding includes an RFBR grant (2016-2017) for germanium production from lignites, alongside regional programs for the Eastern Sayan Mining Complex and VSMB. Through the Department of Geology of Deposits and Exploration Methods, Makarov directs research groups conducting geological-technological mapping, ore quality assessment, and resource base revision across Krasnoyarsk Krai, Khakassia Republic, and the Yenisei Ridge, maintaining strong industry partnerships for mineral exploration projects.

Valery Vladimirovich Zavoruevمشاهده پروفایل

استاد

• Atmospheric Pollution Monitoring
• Environmental Science
• Air Quality Assessment
• +۹ مورد دیگر

Valery Vladimirovich Zavoruev is a Professor at the Department of Ecology and Nature Management within the School of Ecology and Geography at Siberian Federal University (SibFU) in Krasnoyarsk, Russia. He holds a Doctor of Biological Sciences degree with his dissertation focusing on plankton distribution in aquatic ecosystems. His academic career spans several decades with consistent contributions to environmental science and atmospheric monitoring. Doctor of Biological Sciences (2004) Krasnoyarsk State University (Education) Office: pr. Svobodny, 79, building 4, room 44-13 Phone: +7 (391) 206-21-34 Professor Zavoruev's research interests primarily focus on atmospheric pollution monitoring, ecological design, and nature management. His work extensively examines PM2.5 concentrations, benzo(a)pyrene pollution, and the impact of Siberian forest fires on urban air quality. He has developed computational systems for environmental monitoring and conducted significant research on the Yenisei River's influence on Krasnoyarsk's winter atmospheric conditions. His studies often involve spatial analysis of pollution patterns and the development of monitoring technologies. Recent publication trends show Professor Zavoruev has been particularly active in air quality research (2022-2024), with numerous publications on suspended particulates, seasonal pollution patterns, and the development of monitoring systems. His work demonstrates a consistent focus on practical environmental monitoring solutions with immediate applicability to urban pollution challenges in Siberia. The research spans atmospheric science, environmental engineering, and computational environmental analysis. His scientific contributions include: Development of atmospheric monitoring systems Analysis of PM2.5 distribution patterns Studies on river-atmosphere interactions Research on pollution sources from heating systems Wildfire smoke impact assessments Long-term pollution trend analysis Professor Zavoruev regularly collaborates with researchers including Zavorueva E.N., Sokolova O.V., Yakubailik O.E., and Tokarev A.V. on environmental monitoring projects. He teaches courses in Ecology, Environmental management, Ecological design and expertise, Comprehensive assessment of the natural and production potential of the territory, and Modern problems of ecology and nature management, contributing significantly to the education of future environmental scientists.

Borodushkin Andrey Borisovichمشاهده پروفایل

دانشیار

• Computer Modeling of Mineral Deposits
• Geological Survey
• Mineral Exploration
• +۲ مورد دیگر

Borodushkin Andrey Borisovich is an Associate Professor at the Department of Geology of Deposits and Exploration Methods within the Institute of Mining, Geology and Geotechnology at Siberian Federal University. He has over 42 years of experience in geological survey and mineral exploration. Education : Higher education in Mining Engineering-Geology, specializing in "Geological survey, prospecting and exploration of deposits", from Krasnoyarsk Institute of Non-Ferrous Metals named after M.I. Kalinin (1976). Research Focus : Specializes in computer modeling of deposits and the application of GGIS (Geospatial Information Systems) for geological and economic assessment of mineral resources. His work bridges computational methods with practical exploration techniques. Contact : Email ababb@mail.ru | Phone: +7 (905) 975-51-04 | Office: Vuzovsky lane, 3, room 130.

Labushev Mikhail Mikhailovichمشاهده پروفایل

دانشیار

• Mathematical Modeling in Geology
• Information Theory Applications
• Periodic System of Chemical Compounds
• +۲ مورد دیگر

Labushev Mikhail Mikhailovich serves as an Associate Professor and Head of the correspondence department at the Department of Geology of Deposits and Exploration Methods, School of Mining, Geology and Geotechnology, Siberian Federal University. With 37 years of specialized service and a Candidate of Geological and Mineralogical Sciences degree (1993), he teaches core disciplines including Geology of Mineral Deposits and Mathematical Methods of Modeling in Geology. His educational background includes: Mining Engineer-Geologist specializing in Geological Survey, Prospecting and Exploration of Deposits from Krasnoyarsk Institute of Non-Ferrous Metals (1980) Candidate of Geological and Mineralogical Sciences (1993) Advanced training in Cloud Technologies for Educational and Scientific Activities (SFU, 2017) Labushev's research centers on mathematical modeling of equal and unequal masses across physics, chemistry, geology and ecology using information theory equations and numerical proportionality indices. His pioneering work focuses on establishing the scientific foundation for the Declaration of the Periodic System of Chemical Compounds, bridging geological modeling with theoretical chemistry. This integrates mineral classification, earth systems analysis, and computational methods to solve fundamental problems in substance classification. His recent publications demonstrate consistent application of mathematical frameworks to geological challenges, particularly in mineral/rock classification systems and ore body modeling. These works reveal strong interdisciplinary connections between geological survey techniques, environmental mass balance studies, and computational chemistry, with increasing emphasis on data transformation methodologies for geological modeling. No scientific awards were documented in the source material. While no formal advisees are listed, Labushev leads the correspondence department and drives the Declaration of the Periodic System of Chemical Compounds project. His advanced training in cloud technologies indicates active integration of modern computational approaches into geological research and education. The department's focus on exploration methods and deposit geology provides the operational framework for his research activities.

• data analysis in biology and medicine
• innovations in medicine
• integration of medical systems
• +۶ مورد دیگر

Dmitry Igorevich Ryabtsev is an Associate Professor at the Faculty of Computer Science, Department of Software Engineering at the National Research University Higher School of Economics (HSE), where he began working in 2024. With a unique interdisciplinary background bridging medicine and computer science, he brings over a decade of medical experience to his academic role. His educational background includes a Master's degree in Software Engineering from HSE (2024), Candidate of Medical Sciences (2014), and a Doctor qualification in General Medicine from Stavropol State Medical University (2007). Prior to joining HSE, he worked as an ophthalmologist at various institutions including the Helmholtz Research Institute of Eye Diseases, Bascom Palmer Eye Institute in the USA, and Russian Railways medical services. Ryabtsev's research bridges computer science and medical applications, with particular focus on data analysis in biology and medicine, artificial intelligence in medicine, medical imaging, and medical information systems. His scholarly work demonstrates a consistent integration of medical expertise with computational approaches, as evidenced by his publications spanning ophthalmology, medical imaging, and computer vision applications in healthcare. His recent publications show a clear trajectory toward applying computer vision and AI to medical problems, culminating in his 2025 preprint on CV systems for medical applications. This represents a natural evolution from his earlier clinical research in ophthalmology to computational approaches in medicine. As an educator, he teaches courses including Basics of C++ programming, Fundamentals of Medical Systems Design, and Python programming language to undergraduate students in Software Engineering and Applied Mathematics programs. His teaching reflects his interdisciplinary expertise, connecting software engineering principles with medical applications. Ryabtsev is actively involved in research projects connecting computer science with medicine, including the EYAS system (for which he co-authored a 2025 software patent) and has served as a mentor for the 'Big Challenges' program at the Sirius educational center, where students developed AI-based medical devices.