جست‌وجوی استاد و پژوهشگر

• Remote Sensing
• Geographic Information Systems (GIS)
• Forest Ecology
• +۵ مورد دیگر

Sergey Im is an Associate Professor in the Department of Geography at Siberian Federal University's School of Ecology and Geography. With 20 years of professional experience in his specialty, he holds a Candidate of Technical Sciences degree (equivalent to PhD) awarded in 2004 for his dissertation on Microwave and spectroradiometric surveys in forest area research . He graduated from Krasnoyarsk State Technical University in 2001 with a specialization in information systems in geoinformation systems. Dr. Im's research focuses on the application of remote sensing data and GIS technologies for forest area research, with particular emphasis on climate change impacts on Siberian forests, permafrost dynamics, and vegetation monitoring. His work spans several key areas including forest-tundra ecotone dynamics, larch forest responses to warming, and satellite monitoring of environmental changes across Siberia. His extensive publication record shows a clear trend toward increasingly sophisticated remote sensing techniques applied to pressing environmental questions, particularly the interaction between climate warming, permafrost degradation, and vegetation dynamics in Siberia. Recent work demonstrates growing integration of multiple satellite data sources and advanced analytical methods to monitor ecosystem changes at various spatial and temporal scales. Krasnoyarsk City Mayor's Prize for Young Talents (2007) Dr. Im teaches courses in Remote sensing of the Earth, Geographic information databases, Mathematical statistics, and GIS in geography. His advanced training includes multiple certifications in information and communication technologies, modern GIS applications, e-learning methodologies, and pedagogical approaches. His research collaborations span numerous Siberian institutions and involve extensive fieldwork across diverse Siberian ecosystems from the Arctic to mountainous southern regions.

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.

• Process Mining
• Software Process Mining
• Object-Oriented Programming
• +۷ مورد دیگر

Sergey Shershakov is an Associate Professor at the Faculty of Computer Science, Department of Software Engineering at the National Research University Higher School of Economics (HSE University). He serves as the Academic Director of the Systems and Software Engineering educational program and has been with HSE University since 2010. His academic journey includes a PhD from HSE University (2020) and a Master's degree in Software Engineering from the same institution (2012). Dr. Shershakov's research focuses primarily on Process Mining and Software Engineering, with specific interests in: Process Mining methodologies and tools Software Process Mining and analysis Object-Oriented and Component-Oriented Programming Information Systems Architecture Verification of Algorithms Embedded Systems development His scholarly contributions demonstrate a consistent focus on developing practical tools and methodologies for process mining, with particular emphasis on creating graphical interfaces (like VTMine for Visio), improving performance of process mining algorithms, and applying these techniques to real-world systems. His work bridges theoretical computer science with practical software engineering applications, especially in the domain of business process analysis and optimization. Dr. Shershakov has received numerous recognitions for his academic work: Best Teacher award (2014, 2017-2021) Best Academic Supervisor in the category 'Admission of Foreign Students' (2024) Multiple Gratitude awards from HSE University leadership (2017-2024) Academic Work Allowance (2016-2021) Member of the 'New Researchers' category in the High Professional Potential Group (2014-2015) As an educator, Dr. Shershakov teaches multiple courses in C++ programming, Algorithms and Data Structures, and Introduction to Programming across different departments at HSE University. He leads research projects including an RFBR grant focused on 'Development of methods for efficient implementation of algorithms of process mining based on large event logs' (2018). He is also an active member of the IEEE Task Force on Process Mining. Dr. Shershakov is affiliated with the Laboratory of Process-Aware Information Systems (PAIS Lab) at HSE University, where he conducts research on process mining techniques and their applications. His work has significant implications for business process optimization, system verification, and software engineering practices.

• Labor Economics
• Education Economics
• Skills Development
• +۳ مورد دیگر

Travkin Pavel Viktorovich is an Associate Professor at the Department of Applied Economics within the Faculty of Economic Sciences at the National Research University Higher School of Economics (HSE University). He also serves as a Senior Research Fellow at the Laboratory of Labor Market Research and holds the position of Deputy Vice-Rector at HSE University. With 19 years of scientific and teaching experience, he has been working at HSE since 2007. His educational background includes: 2014: Candidate of Economic Sciences 2010: Master's degree in Economics from HSE University 2008: Bachelor's degree in Economics from HSE University 2008: Bachelor's degree in Applied Economics from HSE University Travkin specializes in Labor Economics and Labor Resources, with research focusing on the relationship between education and labor market outcomes. His work examines how additional professional training affects wages, the transition from education to work, and the returns to different levels of education in the Russian labor market. He has conducted extensive research on vocational education, higher education outcomes, and skills development, often employing advanced econometric methods to analyze large-scale survey data. His recent publications show a strong focus on the evolving Russian higher education system and its connection to labor market dynamics. His scientific achievements include the Medal "Recognition - 15 years of successful work" (December 2022), Certificate of Honor of HSE University (December 2020), and recognition as a winner in the Competition for the Best Russian-Language Scientific and Popular Science Works by HSE Employees (2021). He has also received multiple publication bonuses for articles in international peer-reviewed journals, reflecting his consistent research productivity. Travkin has been actively involved in numerous research projects, particularly those related to labor market monitoring and education economics. As part of the Education Economics Monitoring project, he has conducted sociological surveys to study vocational education and its interaction with the labor market. He has also contributed significantly to the development of the "Jobs and Skills Navigator," an algorithmic tool designed to assist in career path building by ranking available vacancies and corresponding professional skills based on current labor market requirements. As a key member of the Laboratory of Labor Market Research, Travkin collaborates with a team of researchers on projects analyzing various aspects of the Russian labor market, including graduate employment outcomes, skill development, and the impact of education policies. His work bridges academic research and practical policy applications, making significant contributions to understanding the dynamics of the Russian labor market and education system.

• Information Systems Architecture
• Design Patterns
• Object-Oriented Programming
• +۵ مورد دیگر

Sergey Aleksandrovich Videnin is an Associate Professor at the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE University) since 2022. His academic background includes a Candidate of Pedagogical Sciences degree (2010) and extensive professional experience in both academia and industry. Prior to joining HSE, he served as Deputy Director of the IT Education Development Center at Moscow Institute of Physics and Technology (2021-2022) and as Head of the Department of Information Systems at Siberian Federal University (2010-2021). Videnin's educational background includes graduation from Krasnoyarsk State Pedagogical University named after V.P. Astafyev in 2005 with a specialty in "Informatics with an additional specialty in pedagogy-psychology" and qualification as a "Teacher-psychologist." He has completed numerous professional development courses in educational technologies, digital transformation of education, and software engineering from HSE University, Siberian Federal University, and other institutions between 2011 and 2025. His research interests span information systems architecture, design patterns, object-oriented programming theory, theoretical foundations of programming, programming languages, and application software. Videnin has made significant contributions to educational technology, particularly in implementing active learning methods in programming education within the CDIO (Conceive-Design-Implement-Operate) engineering education framework. Videnin's recent publications demonstrate a strong focus on the intersection of software engineering principles and educational practices, with particular attention to practical applications in real-world contexts including real estate market analysis, biological image processing, and industrial process control. His work shows a consistent trend toward developing practical solutions that bridge theoretical concepts with tangible applications across diverse domains. Gratitude from the Department of Software Engineering, HSE (November 2023) Best Teacher - 2023-2025 High professional potential group (HSE personnel reserve) Category "New teachers" (2023) Winner of the All-Russian competition "League of Lecturers" organized by the Russian society "Knowledge" (May 2023) Videnin has been actively involved in teaching various computer science courses including Software Design, Computer System Architecture, Operating Systems, and Java Programming. He has participated in significant research projects funded by RFBR, the Ministry of Education RF, and RSF, focusing on information systems architecture, digital transformation of education, and industrial process control. His work demonstrates a strong commitment to both theoretical research and practical applications in software engineering and educational technology.

• Information systems in economics and management
• Logic programming
• Programming teaching methods
• +۵ مورد دیگر

Irina Nikolaevna Lesovskaya is an Associate Professor in the Department of Software Engineering at the Faculty of Computer Science, National Research University Higher School of Economics (HSE). She began her tenure at HSE in 2004 and has accumulated 41 years of scientific and teaching experience. Her academic journey spans multiple institutions including the N.E. Zhukovsky Air Force Engineering Academy, MATI, and MISiS, where she served as Associate Professor before joining HSE. Beyond her faculty position, she has held significant administrative roles as Deputy Dean of both the Faculty of Business Informatics and the Faculty of Business and Management. Lesovskaya earned her Candidate of Technical Sciences degree in 1992 and completed her undergraduate studies at the Kiev State Institute of Culture in 1980, specializing in Library Science and Bibliography. Her professional development includes extensive advanced training, with recent courses in 2024-2025 focused on software engineering education and pedagogical excellence in computer science teaching. She has also completed English language training at HSE at both Pre-intermediate and Intermediate levels. Her research interests center on information systems in economics and management, logic programming, programming teaching methods, and analysis of educational programs. She has made significant contributions to computer science education through the development of curricula and teaching materials aligned with the Federal State Educational Standards. Her work bridges theoretical computer science with practical educational applications, particularly in secondary and higher education contexts. Lesovskaya's publication record demonstrates a consistent focus on computer science education, programming methodologies, and information systems. Her recent work shows increasing emphasis on software engineering education and innovative teaching approaches, while her earlier publications reflect expertise in information retrieval systems and library science. She has contributed to numerous educational materials for state examinations and has developed comprehensive programs for grades 10-11 at the HSE Lyceum. Medal "Recognition - 15 years of successful work" of HSE (February 2020) Honorary Diploma of HSE (November 2013) Honorary Diploma of HSE (December 2012) Gratitude from HSE (November 2007) Medal "For Labor Valor" of the Ministry of Defense of the Russian Federation (April 2004) Throughout her career, Lesovskaya has been actively involved in educational innovation projects including the HSE Internet School of Informatics (2015), development of entrance examination materials for HSE's bachelor's program in Informatics, and creation of comprehensive computer science programs for the HSE Lyceum. She has served as Coordinator of MicrosoftRUS Student Programs and Head of the Laboratory of Educational Innovations at the ITHub Academy, demonstrating commitment to practical student development and industry-academia collaboration. Lesovskaya maintains an active role in the HSE community, including consultation hours for students (particularly for the "Programming in C#" course) and participation in scientific seminars. Her work bridges academic research with practical educational implementation, making significant contributions to computer science education in Russia.

• Algorithms
• Information System Architecture
• Petri Nets
• +۵ مورد دیگر

Alexey Alexandrovich Mitsyuk serves as Associate Professor at the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE), where he also holds the position of Deputy Dean for Research and Senior Research Fellow at the Research and Educational Laboratory of Process-Oriented Information Systems (POIS). He has been working at HSE since 2013 with 12 years of scientific and teaching experience. Mitsyuk is also a member of the Academic Council of HSE. His educational background includes a PhD from HSE (2019) with a dissertation on "Correction of process models while preserving their structure based on event logs" and a specialist degree in Applied Mathematics from Moscow State Institute of Electronics and Mathematics (2009). He is actively involved in professional associations including IEEE Task Force on Process Mining and BPM Association. Mitsyuk's research focuses on process mining, Petri nets, software architecture, data visualization, and algorithms. His work bridges theoretical computer science with practical applications in software engineering and educational analytics. He has supervised numerous student theses across bachelor's and master's programs, with students completing research on topics ranging from software architecture analysis to process mining applications. His publication record shows consistent contributions to the field of process mining and software engineering, with recent work focusing on advanced visualization techniques, process model correction, and applications of process mining in educational and mobile contexts. His research demonstrates a clear progression from theoretical foundations of process modeling to practical applications in software development and education. Honorary certificate from HSE (May 2025) Gratitude from the Faculty of Computer Science (August 2022) Best teacher awards (2015-2025) High professional potential group (HSE reserve staff) Competition for best Russian-language scientific works (2024) Mitsyuk has coordinated research activities of the faculty, created new research groups, monitored grants, and analyzed publication activities. He led a student team that won first place in the BPI Challenge 2017 student category. His teaching includes courses on Software Systems Architecture and Mathematical Methods of Process Analysis in Software Engineering. He is actively involved in numerous conferences as committee member and reviewer, particularly in the fields of process mining and software engineering.

• Adaptive Control
• Robust Control
• Nonlinear Systems
• +۳ مورد دیگر

Vladimir Nikiforov is the Vice Rector for Research at ITMO University and a Professor at the Faculty of Control Systems and Robotics. He serves as editor-in-chief of the Scientific and Technical Journal of Information Technologies, Mechanics and Optics (Scopus-cited) and chairs the Academic Degree Council. His career spans over three decades at ITMO University, transitioning from researcher to professor and administrative leadership. Education: BSc in Electrical Engineering (1986), Leningrad Institute of Fine Mechanics and Optics (now ITMO University) PhD (1991), thesis: 'Adaptive control of trajectory motion of electro-mechanical systems' DSc (2001), thesis: 'Adaptive and robust control with compensation of external disturbances' Nikiforov's research focuses on adaptive and robust control systems , particularly for nonlinear systems, spark ignition engines, and ship propulsion systems. His work includes high-precision control algorithms, disturbance compensation, and stability analysis in multivariable systems. He has contributed to theoretical advancements in backstepping design, high-order tuners, and regressor extension techniques. Part-time roles include: Senior Researcher at the Institute of Problems of Mechanical Engineering (1993-1994, 2000-2005), Associate Professor at St. Petersburg University of Printing Industry (1994-1997), and Technical Director at LOMO Company (2004-2013). His recent publications emphasize adaptive control frameworks with dynamic regressor extension and memory regressor techniques. Key projects include computer-based control systems for ship screw-propeller motors, adaptive compensation of external disturbances, and digital control for brushless DC motors in mechatronic systems.

Vladimir Ulyantsevمشاهده پروفایل

دانشیار

• Bioinformatics
• Metagenomics
• Comparative Metagenomics
• +۶ مورد دیگر

Vladimir Ulyantsev is an Associate Professor at the Faculty of Information Technologies and Programming, ITMO University, where he leads the International Laboratory 'Computer Technologies' and the Discrete Optimization and Formal Methods Lab. He earned his PhD in 2015 (title: 'Finite-State Machine Synthesis Using SAT and CSP Solvers') after completing his Bachelor’s (2011) and Master’s (2013) degrees in the Department of Computer Technologies at ITMO University. His research spans bioinformatics, combinatorial optimization, and computational methods for finite-state machine synthesis. Key contributions include developing software tools like MetaFast and MetaCherchant for metagenomic analysis, and advancing genetic algorithms for demographic history inference (GADMA/GADMA2). He has secured multiple grants from Russian scientific foundations and leads interdisciplinary collaborations, including a partnership with Aalto University, Finland, from 2016-2019. His 15 most recent publications (2012-2025) focus on metagenomics, SAT solvers, evolutionary algorithms, and bioinformatics applications in oncology and disease diagnostics. He has supervised 25+ student theses, including Ekaterina Noskova’s PhD on demographic history inference. He contributes to academic governance as a member of ITMO University’s scientific, technical, and academic councils.

• measure theory
• Gaussian measures
• measures on infinite-dimensional spaces
• +۴ مورد دیگر

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.

• convex optimization
• stochastic optimization
• probability theory
• +۳ مورد دیگر

Egor Leonidovich Gladin serves as both Associate Professor in the Department of Big Data and Information Retrieval and Senior Research Fellow at the Laboratory of Theoretical Foundations of Artificial Intelligence Models within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE). He began his formal appointment at HSE in 2025, though he has been affiliated with the university as a Research Intern since 2022. His educational background includes a PhD from Humboldt University of Berlin (2024), a Master's degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology (2021), and a Bachelor's degree in the same field from the same institution (2019). Gladin is proficient in Russian, English, and German, facilitating his international research collaborations. Gladin's research focuses on convex optimization and stochastic optimization methods, with significant contributions to probability theory and mathematical statistics. His work addresses fundamental challenges in optimization theory, particularly for problems with dimensional constraints, developing algorithms with provable convergence properties. His publications span theoretical foundations of optimization algorithms with applications to artificial intelligence and machine learning, demonstrating expertise in minimax problems, Markov decision processes, and convex minimization with inexact oracles. Among his scientific achievements is a bonus for publication in a journal from List A (2025-2026), recognizing the quality and impact of his research. His scholarly work has appeared in prestigious venues including the Journal of Optimization Theory and Applications, Proceedings of Machine Learning Research, and NeurIPS. As an educator, Gladin teaches Mathematical Statistics 1 and 2 for undergraduate students in the Applied Mathematics and Computer Science program, and Modern Algorithmical Optimization for both undergraduate and graduate students. His teaching emphasizes theoretical foundations while connecting concepts to practical applications in data science and artificial intelligence. He is supervised by Naumov A.A. and Puchkin N.A. at HSE and maintains active collaborations with prominent researchers including Gasnikov A. and Dvurechensky P. in the optimization and machine learning communities.

• Population genomics
• Human genome
• Coalescence theory
• +۵ مورد دیگر

Vladimir Lvovich Shchur is a Professor at the Department of Big Data and Information Retrieval within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE). He serves as Head of the International Laboratory of Statistical and Computational Genomics at the Institute of Artificial Intelligence and Digital Sciences and is a Member of HSE's Academic Council. Dr. Shchur began working at HSE in 2018 and has accumulated 12 years of scientific and teaching experience across multiple prestigious institutions. Dr. Shchur's educational background includes: Doctor of Physical and Mathematical Sciences from HSE (2023) PhD from University of Paris XI (2013) Specialist degree in Mathematics from Lomonosov Moscow State University (2009) His research focuses on population genomics, human genome analysis, coalescence theory, hidden Markov models, and mathematical approaches to genomic data. Dr. Shchur has developed sophisticated computational methods that bridge theoretical mathematics with practical applications in genomics and population genetics. His work demonstrates a consistent progression from pure mathematical theory to applied computational biology, with recent emphasis on machine learning integration. Analysis of his recent publications reveals a strong focus on developing advanced computational tools for genomic analysis, with applications ranging from human population history reconstruction to viral epidemiology. His work shows increasing sophistication in integrating machine learning techniques with traditional population genetic methods, particularly evident in his deep learning approaches for inferring coalescence times and ancestry. His laboratory has made significant contributions to understanding SARS-CoV-2 transmission dynamics in Russia through genomic epidemiology. Dr. Shchur has received numerous scientific recognitions: Letter of thanks from HSE Vice-Rector (December 2024) Allowance for doctoral dissertation defense (2023-2026) Multiple publication bonuses for high-impact journals (2019-2026) Membership in HSE Personnel Reserve (High Professional Potential Group) Dr. Shchur actively supervises student research, with Khomutov E. V. currently working on machine learning applications in population genomics. He has secured multiple competitive research grants, including RSF projects on genetic mixing modeling and deep learning applications for population structure analysis. As laboratory head, he leads a multidisciplinary team developing tools like VGsim (viral genealogy simulator) and AncestryGNN (neural network for population prediction), with growing industry partnerships in agriculture and healthcare.

Denis Vladimirovich Kapulinمشاهده پروفایل

دانشیار

• Space Instrumentation
• Satellite Navigation Systems
• Radio-Electronic Equipment Design
• +۴ مورد دیگر

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.

• Political Sociology
• Organizational Culture
• Social Structure
• +۳ مورد دیگر

Denis Vladimirovich Lvov is an Associate Professor at the Public Relations and Communication Department of Siberian Federal University. Holding a Candidate of Philosophical Sciences degree, his work bridges political sociology, organizational culture, and archetypal theory. Academic Rank: Associate Professor Department: Public Relations and Communication Specialization: Sociocultural Processes, Political Image Modeling His research focuses on archetypes in social systems, including the role of corporate and hierarchical structures in education, societal order, and democratic processes. Recent work examines the psychological safety of social groups and the existential foundations of societal hierarchies. Key areas in his publications include archetypal analysis of organizational culture, the interplay between Jungian collective unconscious and symbolic interactionism, and impacts of e-learning on social identity. He has extensively explored archetypes of corporate culture in globalization and institutional legitimacy. Denis Lvov's educational contributions include certifications in e-learning technologies, Cambridge exam preparation, and Moodle-based course development. He has accumulated over 7 years of work experience in his specialty, with a particular emphasis on public relations within governmental bodies.

• Automatic text analysis
• Information search
• IT project management
• +۲ مورد دیگر

Natalia Sergeevna Belova is an Associate Professor in the Department of Software Engineering at the Faculty of Computer Science, National Research University Higher School of Economics (HSE University) in Moscow. She has been working at HSE since 2012 with 13 years of scientific and teaching experience. Education: 2010: Candidate of Technical Sciences from Moscow State University of Instrument Engineering and Computer Science, specialty 05.13.11 "Mathematical and software support for computing machines, complexes and computer networks" 2009: Postgraduate study from Moscow State University of Instrument Engineering and Computer Science 2005: Engineer qualification in "Computers, complexes, systems and networks" from Moscow State Academy of Instrument Engineering and Computer Science Research Interests: Dr. Belova's research focuses on automatic text analysis, information search, IT project management, embedded databases, and project-based learning in engineering education. Her work bridges theoretical computer science with practical applications in software engineering education and industry. She has made significant contributions to pattern recognition, face identification systems, and the development of computationally efficient methods for intelligent systems processing multimedia information. Publications Trend: Dr. Belova's research has evolved from foundational work on embedded databases to more recent contributions in computer vision, affect recognition, and AI applications. Her early work (2009-2013) focused on database systems reliability and project-based learning methodologies. Since 2015, her research shifted toward computer vision, pattern recognition, and deep learning applications. Her most recent publications (2022-2025) demonstrate expertise in AI applications across various domains including transportation systems and video analysis. Scientific Achievements: Recipient of the Grant of the President of the Russian Federation for young doctors of science MD-306.2017.9 (2017-2018) Gratitude from the Vice-Rector of HSE University (February 2025) Gratitude from the Faculty of Computer Science, HSE University (July 2023) Multiple publication bonuses for journals in List A and international peer-reviewed publications (2016-2025) Best Teacher award for 2016-2017 Member of the High Professional Potential Group (HSE personnel reserve) Teaching and Mentoring: Dr. Belova has supervised over 25 bachelor's theses on diverse software engineering topics including mobile applications, web platforms, biometric identification systems, and educational software tools. She teaches courses on "Group Dynamics and Communications in Professional Software Engineering Practice" and "Economics of Software Engineering." Her commitment to project-based learning methodology is evident in both her research and teaching practice. Professional Development: Dr. Belova actively participates in advanced training programs, including recent courses on modernization of educational programs in software engineering (2025) and problems of training modern specialists in software engineering (2024).