جستجوی استاد راهنمای دانشگاهی

Solntsev Sergey Andreevich 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). He also serves as Deputy Head of the Laboratory of Labor Market Research. With over 23 years of scientific and teaching experience since joining HSE in 2004, he specializes in labor economics, corporate governance, and personnel policy. Candidate of Economic Sciences (2006), Lomonosov Moscow State University Master's degree in Economics (2003), Lomonosov Moscow State University Bachelor's degree in Economics (2001), Lomonosov Moscow State University His research focuses on labor market dynamics, particularly examining wage structures, personnel policies in Russian companies, top management labor markets, and the relationship between higher education and labor market outcomes. He has conducted extensive empirical research on how Russian firms adjust wages, recruit employees, and manage executive turnover, with a particular emphasis on corporate governance mechanisms. His work often utilizes unique Russian enterprise and household survey data to provide insights into labor market functioning in the Russian context. His publication portfolio demonstrates a consistent focus on Russian labor market issues, with particular attention to higher education outcomes, wage setting practices, and executive labor markets. His research combines rigorous empirical methodology with practical policy implications, contributing significantly to understanding labor market dynamics in Russia during periods of economic transition and crisis. Letter of thanks from the Rector of HSE (December 2022) Gratitude from the Faculty of Economic Sciences of HSE (February 2020) Academic Work Allowance (2014-2015, 2008-2009) Bonus for publication in a List B journal (2023-2025) Professor Solntsev teaches multiple courses including Labor Economics, Labor and Personnel Economics (in Russian and English), and Russian Economy at both bachelor's and master's levels. His teaching reflects his research expertise, providing students with insights into contemporary labor market issues in Russia. His research has been supported through institutional mechanisms at HSE, including participation in the Laboratory of Labor Market Research activities and various research projects. As Deputy Head of the Laboratory of Labor Market Research at HSE's Faculty of Economic Sciences, he contributes to one of Russia's leading research centers focused on labor market analysis. The laboratory conducts empirical studies on various aspects of the Russian labor market, often in collaboration with government agencies like Rostруд (Federal Labor and Employment Service). Professor Solntsev works closely with colleagues including Professor Sergey Roshchin, the laboratory head, on multiple research initiatives.

• Labor Economics
• Corporate Governance
• Personnel Policy
• +۴ مورد دیگر

Alexander Alexandrovich Kharlamov serves as a Professor at the National Research University Higher School of Economics (HSE), specifically within the Faculty of Computer Science and Department of Software Engineering. He joined HSE in 2015 and has accumulated 42 years of scientific and teaching experience. His academic profile includes prominent identifiers such as ORCID: 0000-0003-2942-5101, ResearcherID: E-3760-2014, and Scopus AuthorID: 57193909855. He maintains an office at the Pokrovsky Boulevard campus (AUK "Pokrovsky Boulevard", Pokrovsky blvd, 11, office S913) and serves as the Editor-in-chief of the journal "Speech Technologies" since 2008. Doctor of Technical Sciences (2010) from Moscow State Institute of Electronics and Mathematics Candidate of Technical Sciences (1983) from Moscow State Technical University named after N.E. Bauman Postgraduate study (1980) at Moscow State Technical University named after N.E. Bauman Mathematics degree (1976) from Lomonosov Moscow State University Thermal Physics degree (1970) from Moscow Power Engineering Institute Professor Kharlamov's research focuses primarily on neuroinformatics, with significant contributions to neural networks, semantic representations, and intelligent information systems. His work bridges computational approaches with cognitive modeling, exploring how semantic networks can be used for text analysis, speech recognition, and situation monitoring. His research interests span both theoretical foundations of neuroinformatics and practical applications in areas such as social media analysis, smart city development, and digital transformation. He has developed the TextAnalyst technology for automatic semantic analysis of text and has made significant contributions to understanding how humans process information through neural network models. His recent scholarly output demonstrates a clear trajectory toward multimodal systems, digital transformation in urban environments, and advanced semantic analysis techniques. The publications reveal a consistent focus on applying neuroinformatics principles to real-world problems, particularly in analyzing social dynamics through digital footprints, developing intelligent monitoring systems, and creating semantic frameworks for information processing. His work increasingly addresses contemporary challenges such as pandemic response, social stress analysis, and digital conflict zones, showing adaptability to emerging societal needs while maintaining theoretical rigor. Corresponding Member of the International Academy of Informatization (1994) Professor Kharlamov has secured significant research funding through grants from the Russian Foundation for Basic Research (No. 14-06-00363) and the Russian Humanitarian Science Foundation (No. 15-03-00860). His research leadership spans decades, with documented projects from 1996 to present, covering areas such as neural network modeling, speech recognition systems, semantic analysis technologies, and intelligent information systems. He has served as principal investigator for numerous projects, often collaborating with institutions like IITP RAS and Bauman Moscow State Technical University. His teaching portfolio includes advanced courses in neuroinformatics, neuromathematics, and neural network theory for both bachelor's and minor programs at HSE. As Editor-in-chief of the journal "Speech Technologies" since 2008, Professor Kharlamov has shaped discourse in his field while continuing his own research on semantic networks and neural modeling. His work on homogeneous semantic networks represents a significant contribution to the field, providing frameworks for text analysis, situation monitoring, and knowledge representation. The integration of his theoretical work on neural networks with practical applications in information systems demonstrates a career-long commitment to bridging theoretical computer science with real-world implementation challenges.

• Neuroinformatics
• Neural Networks
• Semantic Networks
• +۶ مورد دیگر

Grigory Gelmutovich Kantorovich is a distinguished Research Professor at the National Research University Higher School of Economics (HSE), where he has been working since 1993. He serves as Head of the Scientific and Educational Laboratory of Macrostructural Modeling of the Russian Economy within the Faculty of Economic Sciences. He holds a tenured professorship since 2018 and has been recognized as a Distinguished Professor by HSE. With 54 years of scientific and teaching experience, Kantorovich has made significant contributions to the field of econometrics and economic modeling. His educational background includes a Candidate of Physical and Mathematical Sciences degree (1974) from Moscow Institute of Physics and Technology, where he specialized in Automatic Regulation and Control Theory. He graduated with honors from the same institution in 1971 with a degree in Flight Dynamics and Motion Control of Aircraft. His extensive professional development includes numerous international programs at Erasmus University Rotterdam, University of Paris 1 - Sorbonne, Harvard University, and the London School of Economics. Kantorovich's research spans multiple areas of econometrics, including macroeconometrics, microeconometrics, financial econometrics, and time series modeling. His work focuses on dynamic modeling of economic development, macrostructural modeling of the economy, and econometric modeling of socio-economic processes. His publications demonstrate a consistent focus on applying rigorous statistical methods to economic problems, with particular attention to risk evaluation in financial markets, structural shifts in time series, and the impact of investments on economic efficiency. Throughout his career, Kantorovich has received numerous prestigious awards including the Medal of the Order "For Merits to the Fatherland" (both I and II degrees), multiple Honorary Certificates from HSE, and recognition as Best Teacher in multiple academic years. He was awarded the "Golden HSE" Award twice for his contributions to teaching and school development. As an academic advisor, Kantorovich has supervised doctoral research and mentored students including Lana Zakharova (on economic crises determinants), Nikolai Shugal (on gross value added modeling), and Elena Nazrullaeva (on capital investments impact). He has also participated in numerous international research projects, including a World Bank project on energy price impacts and grants from the MacArthur Foundation. He leads the Scientific and Educational Laboratory of Macrostructural Modeling of the Russian Economy, where he conducts research on economic modeling and advises on policy-related economic issues. His work bridges theoretical econometrics with practical applications in Russian economic policy and education.

• Econometrics
• Macroeconometrics
• Microeconometrics
• +۷ مورد دیگر

Attila Kertesz-Farkas is a Hungarian-born academic currently serving as Assistant Professor at the Faculty of Computer Science, Department of Data Analysis and Artificial Intelligence, at the National Research University Higher School of Economics (HSE) in Moscow. Since 2021, he has also been Head of the Research and Educational Laboratory of Artificial Intelligence for Computational Biology. He joined HSE in 2015 after completing postdoctoral positions at the University of Washington and the International Centre of Genetic Engineering and Biotechnology. His educational background includes: Doctor of Science (2022) from National Research University Higher School of Economics PhD (2010) from University of Szeged Master's degree in Computer Science (2004) from University of Szeged Kertesz-Farkas's research focuses on the intersection of artificial intelligence and computational biology, particularly in mass spectrometry data analysis. His work spans computational proteomics, human gait analysis, and medical applications of machine learning. He develops novel algorithms for peptide identification, protein classification, and single-cell analysis, with applications ranging from cancer research to environmental contamination analysis. His research group actively explores how deep learning can improve the analysis of biological data that is inherently non-human readable. His scientific contributions have been recognized with several awards including a Letter of thanks from the Rector of HSE (December 2022), a Letter of gratitude from the Faculty of Computer Science (September 2021), and the Best presentation award at ICMLC 2023 conference. As an academic supervisor, Kertesz-Farkas mentors multiple PhD students working on diverse projects including generative models for mass spectrometry data, human gait control systems for prosthetics, and deep learning applications for single-cell analysis. His research is supported by the allowance for defending a doctoral dissertation (2022-2025) and various research projects at HSE. He leads the Laboratory of Artificial Intelligence for Computational Biology, which focuses on developing AI methods specifically tailored for biological data analysis problems. The laboratory conducts research in computational proteomics, medical applications of machine learning, and the development of tools for mass spectrometry data interpretation.

• Computational Biology
• Bioinformatics
• Mass Spectrometry Data Analysis
• +۵ 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.

• Diagnostic Features
• Testing Electronic Means
• Charging of Polymers
• +۳ 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.

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

Kseniya Adamovich is a Senior Lecturer and Senior Research Fellow at the Institute of Education, HSE University. She holds a Candidate of Sciences (PhD, 2023) and a Master’s in Public Administration (2017), both from HSE University. Her work focuses on educational inequality, digital learning, and school infrastructure, with a regional emphasis across Russia. Research Interests: Educational inequality and spatial econometrics Digital learning and EdTech adoption Policy evaluation in post-Soviet education Time management in adult education Recent Publications examine digital gaps in Russian schools, peer editing behaviors in language learning, and the effects of school consolidation policies. Her work frequently employs multilevel and spatial econometric analyses. Scientific Recognition: Winner, HSE University Best Russian Research Paper Competition (2024) She has presented at ECER, CIES, and EDULEARN conferences, and received grants like the Evidence-Based Policy 2020 award. Her teaching includes Data Analysis in Education, EdTech practices, and machine learning applications in pedagogical research.

• Educational Inequality
• Digital Learning
• EdTech
• +۳ مورد دیگر

Natalia Anatolyevna Saprykina serves as Associate Professor and Deputy Director at the Industrial Technology Department of Yurga Technological Institute, a branch of Tomsk Polytechnic University. With a Candidate of Technical Sciences degree (equivalent to PhD), she has established herself as a prominent figure in mechanical engineering education and research within the Siberian academic community. Education: Graduated in 2000 from Yurga branch of Tomsk Polytechnic University with specialization in Mechanical Engineering Technology Completed postgraduate studies (2008-2011) at Tomsk Polytechnic University in specialty 05.02.07 - Technologies and equipment for mechanical and physical-technical processing Defended PhD thesis in 2013 on 'Improving the technology for forming the surface layer of products obtained by layer-by-layer laser sintering' Extensive professional development with over 20 advanced training courses from 2014-2025 in areas including neural networks, digital education, and smart manufacturing technologies Dr. Saprykina's research focuses on additive manufacturing technologies, particularly selective laser melting and sintering processes. Her work centers on improving surface quality and accuracy of metal prototypes, with special emphasis on aluminum-silicon-magnesium (AlSiMg) alloys and cobalt-chromium-molybdenum (Co-Cr-Mo) systems. She has published extensively on powder characteristics, process parameter optimization, and microstructure-property relationships in additively manufactured components. Her research bridges fundamental materials science with practical industrial applications. Analysis of her recent publications reveals a strong trajectory in metal additive manufacturing research, with increasing focus on multi-component alloys, process optimization, and educational applications of these technologies. Her work demonstrates consistent progression from fundamental studies of laser-material interactions to applied research on specific alloy systems with industrial relevance. Dr. Saprykina actively mentors students in research projects related to additive manufacturing, robotics, and smart production technologies. Her educational contributions include developing electronic courses and implementing project-based learning approaches in mechanical engineering education. She has been instrumental in modernizing the curriculum at Yurga Technological Institute to incorporate emerging digital manufacturing technologies and pedagogical methods. Her professional activities demonstrate strong integration of research and teaching, with particular emphasis on preparing engineering students for modern manufacturing environments through hands-on experience with advanced production technologies and digital tools.

• Additive Manufacturing
• Selective Laser Melting
• Materials Science
• +۳ مورد دیگر

Muchkina Elena Yakovlevna is a Professor at the Department of Ecology and Nature Management in the Institute of Ecology and Geography , Siberian Federal University. With a Doctor of Biological Sciences degree (2004), her work focuses on environmental monitoring, heavy metal pollution, and aquatic microbiology. Education: Biology, Krasnoyarsk State University (1977) Key Publications: Over 200 works including monographs, journal articles, and conference proceedings Research Areas include: Urban environmental quality assessment Heavy metal distribution in soil-plant systems Bioremediation with bacterial communities Nanoparticle ecological risk assessment Aquatic ecosystem dynamics Recent scientific awards include: Certificate of honor from Russian Ministry of Agriculture Member, Russian State Botanical Society Her teaching includes: Eco-adaptive technologies in urban environments History and methodology of ecology Notable Trends across 15 recent articles (2020-2024) show focus on: Biogenic nanoparticle impacts on aquatic plants Urban soil contamination mapping Industrial pollution effects on flora Integrated bioassay development Ecological monitoring frameworks

• Ecology
• Environmental Monitoring
• Heavy Metal Pollution
• +۵ مورد دیگر

Yuri Alexandrovich Kalinin is a Doctor of Geological and Mineralogical Sciences and Professor at the Department of Geology of Deposits and Methods of Exploration of Mineral Resources within the Institute of Mining, Geology and Geotechnology at Siberian Federal University. With 39 years of experience in the field, he specializes in the geology of gold deposits and metallogeny, with extensive research in ore-magmatic systems and mineralization processes across Siberia and Kazakhstan. Dr. Kalinin graduated from the geological and geophysical faculty of Novosibirsk State University in 1979 with a degree in engineer-geologist-geochemist. He earned his Candidate of Geological and Mineralogical Sciences degree in 1989 and his Doctor of Geological and Mineralogical Sciences degree in 2004. His academic journey reflects deep commitment to mineral deposit studies and exploration methods. His research primarily focuses on gold deposit geology and metallogeny, with particular expertise in antimony and gold mineralization relationships, ore-magmatic systems, and fluid regimes in various geodynamic settings. Dr. Kalinin has led numerous research projects examining the spatial-temporal and genetic relationships of mineralization in Transbaikalia, the Yenisei Ridge, and Eastern Kazakhstan, contributing significantly to understanding gold-bearing processes in Northern Asia. Analysis of Dr. Kalinin's recent publications reveals a consistent focus on gold deposit studies across Siberia and Kazakhstan, with particular emphasis on spatiotemporal relationships between different mineralization types. His work spans economic geology, mineralogy, and sedimentology, with significant contributions to understanding unconventional gold placers, stockwork mineralization, and the geological controls on gold distribution in various tectonic settings. Dr. Kalinin has served as principal investigator for multiple research projects, including: Basic project of the IGM SB RAS for 2013-2016 on intraplate ore-magmatic systems Basic project of the IGM SB RAS for 2017-2020 on metallogeny of Northern Asia RFBR Grant 13-05-00998 on spatio-temporal relationships of antimony and gold mineralization RFBR Grant 16-05-00353 on genetic relationships of gold-bearing copper-skarn deposits He has supervised 2 graduate students and serves on dissertation councils D 212.099.09 at Siberian Federal University and D 003.067.03 at the Institute of Geology and Mineralogy SB RAS. His industry collaborations include contracts with Tetis-T LLC, NPO AkademGEO LLC, and GEO.KZ on gold prospecting and assessment projects in Siberia and Kazakhstan. Dr. Kalinin is actively involved in the Center for Geotechnical Research 'Prognoz' at SFU, which conducts applied prospecting and scientific-methodological research for gold mining enterprises in the Siberian region (Yenisei Ridge, Eastern Sayan). His work bridges academic research and practical applications in mineral exploration.

• Geology of gold deposits
• Metallogeny
• Antimony mineralization
• +۳ مورد دیگر

Ruslan Aglyamovich Sharafutdinov is a distinguished academic and researcher serving as Director of the Institute of Ecology and Geography at Siberian Federal University (SFU) in Krasnoyarsk, Russia. Holding the Candidate of Geographical Sciences degree (equivalent to PhD), he has established himself as a leading expert in environmental geochemistry and urban ecology within Siberian academic circles. His work bridges theoretical research with practical environmental management solutions for the Krasnoyarsk region and broader Siberian territory. His educational background includes graduation from Krasnoyarsk State University as a bioecologist in 2002, followed by his Candidate of Geographical Sciences degree in 2007. His dissertation focused on Geochemical properties and mineral composition of peat deposits of the southern forest-steppe of the Minusinsk Basin and mountain taiga of the central part of the Western Sayan . He has completed extensive advanced training in environmental safety, radiation safety, radioecology, educational presentation, quality assessment of educational programs, strategic management, project management, and anti-corruption in education. Sharafutdinov's research primarily centers on geochemistry of floodplain ecosystems and ecology of urbanized areas, with particular emphasis on elemental distribution in trees, pollution assessment of urban floodplain soils, and paleoenvironmental reconstruction. His work demonstrates how dendrochemical analysis can serve as a proxy for environmental changes, with significant implications for understanding climate change impacts on Siberian ecosystems. His studies often focus on the Krasnoyarsk region, examining how urban development affects floodplain ecosystems along the Yenisei River. His recent publications reveal a consistent focus on dendrochemistry as an environmental indicator, with particular attention to Scots pine as a bioindicator species. The research shows how elemental distribution in tree rings correlates with environmental conditions, providing valuable insights into historical pollution patterns and climate variations. His work bridges fundamental ecological research with practical environmental monitoring applications. Member of the V. V. Dokuchaev Soil Science Society Letter of thanks from the Governor of Krasnoyarsk Krai Certificate of honor from the Governor of Krasnoyarsk Krai Sharafutdinov has secured substantial research funding from multiple sources including the Krasnoyarsk Regional Science Foundation, Russian Foundation for Basic Research (RFBR), Russian Science Foundation (RSF), and the Ministry of Natural Resources and Forestry of Krasnoyarsk Krai. His grants have supported research on floodplain soil dynamics, carbon sequestration in boreal forests, late Holocene environmental changes, and sustainable development of Siberian monocities. He has served as principal investigator for projects examining biogeochemical cycling in Siberian ecosystems and the environmental impacts of urbanization. As Director of the Institute of Ecology and Geography, Sharafutdinov oversees research programs that integrate field studies with laboratory analysis, particularly focusing on the unique ecosystems of the Sayan Mountains and Yenisei River floodplains. His leadership has positioned the institute as a key center for environmental research in Siberia, with particular expertise in dendrochemistry, soil science, and urban ecology. The institute maintains strong connections with regional environmental agencies and participates in international research collaborations focused on boreal forest ecosystems.

• Geochemistry of floodplain ecosystems
• Ecology of urbanized areas
• Soil science
• +۵ مورد دیگر

Pesotskaya Elena Yuryevna is an Associate Professor at the Faculty of Computer Science, Department of Software Engineering, National Research University Higher School of Economics (HSE), where she has worked since 2009. With 26 years of scientific and teaching experience, she holds a Candidate of Economic Sciences degree (2008) and a specialization in Applied Informatics in Economics (2002). Education: Candidate of Economic Sciences (2008), Moscow Institute of Economics and Statistics (2002) Her research focuses on Information Systems in Economics , Risk Management , Business Process Optimization , and IT Strategy Development . Her recent work explores AI-driven cybersecurity, blockchain applications, and pandemic-induced shifts in IT workforce requirements. She has authored 15 notable publications across 2007–2025, including conference chapters and journal articles. Her research trends span Software Engineering Education , Blockchain in Charity , and Agility-Driven Learning . Scientific Awards: Letter of thanks from HSE Rector (2024) Medal 'Recognition - 10 years of successful work' (2022) Gratitude from Higher School of Economics (2013) Academic Work Allowance (2012–2014) Best Teacher Award (2011–2012) Advising & Grants: Supervises final qualification works at HSE and has participated in multiple research grants and projects, particularly in AI and blockchain domains. Conferences: Regularly presents at international conferences like FICC, FTC, and CAISE, including topics on cybersecurity, digital government, and educational platforms.

• Information Systems in Economics and Management
• Risk Management
• Business Process Optimization and KPI Development
• +۱ مورد دیگر

Viktor Vyacheslavovich Kulyamin is an Associate Professor at the Faculty of Computer Science of the National Research University Higher School of Economics (HSE), affiliated with the Basic Department 'System Programming' of the Institute for System Programming (ISP RAS). With 25 years of scientific and teaching experience , he has been actively contributing to HSE since 2015. Education: 1995: Specialist in Mathematics (Applied Mathematics) from Lomonosov Moscow State University 2000: Candidate of Physical and Mathematical Sciences 2009: Academic Title of Associate Professor His research interests span software engineering , formal methods , verification and validation of operating systems, and security policy modeling . His recent publications focus on dynamic software analysis , runtime verification , multi-level security models , and formal testing techniques , reflecting a deep engagement with automated testing and system validation frameworks. Teaching : He has consistently taught Quality Assurance and Testing in the Software Engineering program at HSE since 2020, covering topics such as test construction , model-based testing , and system conformance . Professional Affiliation : Since 1998 , he has worked at the Institute for System Programming of the Russian Academy of Sciences , becoming a leading research fellow by 2014. He also held positions at Moscow State University's Department of System Programming (Senior Lecturer: 2008, Associate Professor: 2009).

• Software Engineering
• Formal Methods in Software Development
• Verification and Validation of Operating Systems
• +۲ مورد دیگر

Vyacheslav Kulagin is an Associate Professor and Senior Researcher at ITMO University's Faculty of Secure Information Technologies. He holds a PhD and serves as a Tutor within the university structure. Education: Graduated from LITMO Radiotechnical Department in 1960 Research Interests: Implementation of distributed control systems Enterprise solution development Distributed database systems Web application design Mobile application design Publications: Dr. Kulagin has authored over 60 research papers and holds 5 patents in his field. Contact: Email: koulagin@mail.ifmo.ru

• Distributed Control Systems
• Enterprise Solution Development
• Distributed Databases
• +۲ مورد دیگر

Daniil Nikolaevich Tyapkin is a Junior Research Fellow and Postgraduate Student at the National Research University Higher School of Economics (HSE), affiliated with the Faculty of Computer Science. He works within the Institute of Artificial Intelligence and Digital Sciences and the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis under the supervision of Alexey Alexandrovich Naumov. Education: 2021: Bachelor's degree in Applied Mathematics and Computer Science from HSE Currently in 2nd year of postgraduate studies with dissertation topic: "Randomized trial for reinforcement learning" Research Interests: His work focuses on reinforcement learning and stochastic optimization, including exploration strategies, generative flow networks, and theoretical analysis of learning algorithms. He develops efficient methods for complex decision-making problems with applications in AI and data science. Publications: His research appears in top venues (ICLR, NeurIPS, ICML, AISTATS) covering reinforcement learning, optimization, and probabilistic modeling. Recent works explore GFlowNets, entropy regularization, and high-probability bounds for learning algorithms. Awards & Honors: Letter of gratitude from HSE Faculty of Computer Science (2022) Publication bonus for List A journal articles (2023-2024) HSE Personnel Reserve - New Researchers category (2022-2023) Teaching & Advising: Teaches courses in Mathematical Statistics and Matrix Computations. No formal student advising mentioned. Laboratory Affiliation: Member of the International Laboratory of Stochastic Algorithms and Multidimensional Data Analysis, focusing on algorithmic development for machine learning challenges.

• Reinforcement Learning
• Stochastic Optimization