جست‌وجوی استاد و پژوهشگر

Aleksejus Kononovičiusمشاهده پروفایل

پژوهشگر

• Sociophysics
• Econophysics
• Opinion dynamics
• +۵ مورد دیگر

Aleksejus Kononovičius is a Senior Researcher at Vilnius University's Institute of Theoretical Physics and Astronomy within the Faculty of Physics. His research spans interdisciplinary applications of physics principles to complex social and financial systems, with particular expertise in modeling collective behavior through statistical and computational approaches. Dr. Kononovičius's primary research interests focus on sociophysics, econophysics, and the physics of complex systems. His work explores opinion dynamics through various voter models (noisy voter model, compartmental voter model, scaled voter model), long-range memory phenomena in both physical and social contexts, and agent-based modeling of social and financial systems. He investigates how nonlinear stochastic dynamics can explain patterns in parliamentary elections, financial markets, and semiconductor physics. His research demonstrates how fundamental physical principles can elucidate complex phenomena across diverse domains. Analysis of his publication record reveals a consistent focus on developing and applying mathematical models to understand complex systems. His recent work (2023-2024) examines delayed interactions in voter models and 1/f noise in semiconductors, while maintaining his longstanding interest in long-range memory phenomena. The interdisciplinary nature of his research bridges statistical physics, social sciences, and finance, with applications ranging from understanding political behavior to financial market dynamics and physical material properties. 2020 Young scientist scholarship 'Effect of non-linearity on long-range memory properties of fractional Gaussian noise' awarded by Lithuanian Academy of Sciences Promotional scholarships for doctoral candidates (2013-2015) granted by Research Council of Lithuania IARIA Best Paper Award (2011) Dr. Kononovičius has supervised 3 bachelor degree theses, 1 master degree thesis, and 4 internship projects, demonstrating his commitment to mentoring the next generation of researchers. His research has been supported by multiple grants and scholarships from the Research Council of Lithuania. He actively contributes to the scientific community through his participation in the Complex Physical and Social Systems Group at Vilnius University. He maintains an active presence in the scientific community through the 'Physics of Risk' science blog (https://rf.mokslasplius.lt/), which serves as a platform for science popularization and educational activities related to his research interests. His work exemplifies the growing field of applying physics methodologies to understand complex social and economic phenomena.

• Blockchain
• Cryptocurrency
• Quantum Computing
• +۳ مورد دیگر

Dr. Mindaugas Juodis is a Researcher at the Blockchain and Quantum Technologies Group within Vilnius University's Institute of Data Science and Digital Technologies. His work centers on advanced statistical modeling of blockchain systems and decentralized networks. His research spans blockchain, cryptocurrency, quantum computing, and probability theory. Key investigations include Bitcoin price regime shifts using Bayesian methods, Ethereum transactional decentralization metrics, and wealth distribution analysis in blockchain networks. Earlier theoretical work focused on self-normalized sums, central limit theorems, and functional limit theorems for dependent processes. Publications reveal a clear trajectory from theoretical statistics (2004-2007) to applied blockchain analytics (2024-2025). Recent work bridges mathematical rigor with cryptocurrency applications, appearing in Mathematics, ICT Express, and IEEE conferences. His research demonstrates expertise in translating complex statistical frameworks to real-world decentralization problems. As part of the Blockchain and Quantum Technologies Group, he contributes to cutting-edge research in blockchain analytics and quantum computing intersections, focusing on empirical validation of decentralization metrics and network properties.

• Blockchain Technology
• Quantum Computing
• Machine Learning
• +۳ مورد دیگر

Marco Marcozzi is a researcher at the Vilnius University Blockchain and Quantum Technologies Group. His work focuses on blockchain systems, quantum computing, and performability analysis of fault-tolerant protocols. Research Interests : Blockchain technology, quantum computing, Byzantine fault tolerance, consensus protocols, and data-driven system performance modeling. Key Contributions : Led studies on quantum-enhanced machine learning, performability analysis of PBFT systems, and classification of DLT consensus protocols using clustering algorithms. Publications Trend : Recent works emphasize quantum computing applications in blockchain systems, performability modeling for fault-tolerant architectures, and machine learning approaches to consensus protocol analysis across disciplines like computer science and system reliability engineering. Current Affiliation : Blockchain and Quantum Technologies Group, Vilnius University, Akademijos St. 4, Vilnius.

• Computer Science Education
• Computational Thinking
• STEM Education
• +۲ مورد دیگر

Dr. Anita Juškevičienė is a Senior Researcher at the Educational Systems Group of Vilnius University's Institute of Data Science and Digital Technologies. Her work focuses on computational thinking, STEM education, and digital competence development. Research Interests : Computational thinking in primary/secondary education, STEAM integration, gender balance in STEM, educational technology adoption, and digital competence frameworks. Publications Trends : Recent work addresses pedagogical approaches for informatics education, teacher motivation, physical computing in STEM, and data modeling techniques for educational systems. Supervision : Currently supervising Snow White Bagocienė on modeling automatic assessment systems for design thinking. Projects : Active in analyzing global trends in computing education and implementing mobile learning scenarios for computer engineering training.

• Random processes with distant dependence
• Applied statistics
• Extreme value theory
• +۲ مورد دیگر

Dr. Marijus Vaičiulis is a researcher at the Institute of Mathematics and Informatics (Vilnius University) , affiliated with the Interdisciplinary Statistical Research Group . He holds a Doctor of Mathematics degree (awarded in 2004 by Vilnius Gediminas Technical University and MII). Education Bachelor's degree in Mathematics and Computer Science from Šiauliai University (1995) Master's degree in Mathematics and Computer Science from Šiauliai University (1997) Research interests focus on random processes with distant dependence and applied statistics , particularly in extreme value theory, tail index estimation, and network analysis. His work bridges theoretical probability with practical applications in stochastic processes and heavy-tailed data modeling. Publications demonstrate expertise in tail index estimation techniques, evolving random graph analysis, and extreme value statistics. Collaborations with Natalia Markovich and Maxim Ryzhov highlight interdisciplinary approaches to network theory and statistical inference. Pedagogical activities include teaching probability theory , mathematical statistics , and random processes at Šiauliai University and Vilnius University. Current affiliation is with the Interdisciplinary Statistical Research Group at Vilnius University's Institute of Mathematics and Informatics. His work address is Akademijos St. 4, room 218, Vilnius.

• Stochastic Processes
• Fractional Calculus
• Statistical Inference
• +۳ مورد دیگر

Prof. Kęstutis Kubilius serves as an Adjunct Professor within the Interdisciplinary Statistical Research Group at Vilnius University's Institute of Data Science and Digital Technologies. His research office is located at Akademijos Street 4, room 208 in Vilnius, with contact numbers +370 5 210 9731 and +370 618 06064. His research program centers on advanced stochastic processes, specializing in fractional Brownian motion and fractional stochastic differential equations (FSDEs). Key contributions include developing existence-uniqueness frameworks for FSDEs with stochastic forcing, creating numerical approximation schemes like the implicit Euler method, and advancing parameter estimation techniques for Hurst and Orey indices. His work bridges theoretical probability with applications in financial mathematics and statistical modeling of long-range dependent phenomena. Analysis of his 15 most recent publications reveals consistent focus on fractional calculus applications, with increasing emphasis on numerical methods since 2020. The research demonstrates methodological evolution from theoretical foundations toward practical implementation, particularly in volatility modeling and boundary-conditioned SDEs. Recent collaborative works (notably with Medžiūnas and Mishura) highlight interdisciplinary approaches combining statistical inference with computational mathematics. Prof. Kubilius actively supervises doctoral candidates, having guided Aidas Medžiūnas through completion of the 2018-2022 dissertation 'Parameter evaluation for mixed SDLs'. His research group maintains strong connections with international probability theory communities, evidenced by co-authorships with leading scholars in fractional calculus. As a core member of the Interdisciplinary Statistical Research Group, he contributes to Vilnius University's strategic focus on advanced statistical methodologies for complex data systems, with particular relevance to financial engineering and time-series analysis applications.

Rimantas Rudzkisمشاهده پروفایل

استاد

• Probability Theory
• Mathematical Statistics
• Econometric Modeling
• +۳ مورد دیگر

Rimantas Rudzkis is an Affiliated Professor at Vilnius University's Institute of Mathematics and Informatics, specifically within the Interdisciplinary Statistical Research Group. He serves as the Head of the Applied Statistics Department and has been working at the Institute since 1978. His academic credentials include a Doctor of Mathematics from Vilnius University (1978), a Habilitation Doctor from the Institute of Mathematics and Informatics (1993), and Professor title from Vytautas Magnus University (1996). Dr. Rudzkis has extensive educational background, having graduated from Kaunas Polytechnic Institute in 1973 with a specialization in computing technology and engineering mathematics. His professional journey began as an assistant at KPI (1973-1974), followed by postgraduate studies at the Institute of Mathematics and Informatics (1974-1977). His research primarily focuses on probability theory , mathematical statistics , and econometric modeling . He has developed methods for data clustering, nonparametric density estimation, and created mathematical models of Lithuanian macroeconomic indicators using VAR methodology. His work spans theoretical developments in statistical decision algorithms and practical applications in economic forecasting. Analysis of his recent publications reveals a consistent focus on statistical methodology development, particularly in goodness-of-fit testing, multivariate analysis, and applications to economic and financial data. His research shows a clear progression from theoretical probability work toward increasingly applied econometric modeling, with significant emphasis on Baltic region economic analysis in recent years. Dr. Rudzkis maintains significant professional engagement through multiple editorial roles, including membership on the editorial boards of 'Lithuanian Mathematical Collection' (since 1999), 'Lithuanian Statistical Works' (since 2000), and 'Money Studies' (since 2000). He has also served as Editor for proceedings of the '8th International Conference on Probability Theory and Mathematical Statistics'. His academic service includes leadership as Head of the Applied Statistics Department Seminar, membership on the program committee for international conferences, and serving as an Expert member of the Lithuanian Academy of Sciences since 1994. He has also been actively involved with professional societies, serving on the boards of both the Lithuanian Mathematical Society and Lithuanian Statistical Union since 1998. Dr. Rudzkis teaches probability theory, mathematical statistics, and specialized courses including multivariate statistics, time series analysis, correlation-regression analysis, and econometrics at multiple universities including VDU, KTU, and VGTU.

• Physical Sciences
• Mathematics
• Random Processes
• +۳ مورد دیگر

Kanišauskienė Karolina is an Assistant and Lecturer at Vilnius University Šiauliai Academy. Her academic career spans roles as an Assistant (2007-2014), Lecturer (2014-2017, 2021-present), and Associate Professor (2017-2020) at Šiauliai University and its successor institution. Doctoral studies in Mathematics at Vilnius University Multiple degrees in Mathematics and Humanities from Šiauliai University Her research focuses on random processes and their prediction , statistical analysis for olympiads , and graphical models with linguistic applications . She teaches courses in Graph Theory , Algorithms , and Statistical Modeling . Key affiliations include: Institute of Education Researchers Researchers' Excellence Network (RENET) Doctoral Studies at Vilnius University

• Agricultural Sciences
• Animal Science
• Biology
• +۳ مورد دیگر

Ramutė Mišeikienė is an academic researcher at the Lithuanian University of Health Sciences (LSMU), affiliated with the Faculty of Veterinary Medicine and the Institute of Animal Husbandry Technologies. She holds a Doctor of Science degree (2005) and focuses on agricultural and biological sciences, particularly in dairy cattle productivity, milk composition analysis, and livestock management. Her research explores breed-specific productivity differences, lactation physiology, and technological impacts on dairy farming efficiency. Primary Affiliations: Institute of Animal Husbandry Technologies (43%) Institute of Biological Systems and Genetic Research (30%) Faculty of Veterinary Medicine (11%) Her work integrates genetics, animal husbandry, and technological applications to optimize dairy production. Key areas include milking system effects on milk yield, breed comparisons (Holstein vs. Lithuanian Black-and-White), and somatic cell count analysis as indicators of milk quality. She has supervised multiple theses addressing topics like milking time optimization, gene polymorphism impacts, and automated milking technologies. Her studies frequently involve partnerships with agricultural centers like the J. Taco Dairy Centre and robotic farms like R. Svipo's.

• Mathematical Modeling
• Stochastic Differential Equations
• Biological Populations
• +۳ مورد دیگر

Petras Rupšys is a Professor at the Department of Forest Sciences within the Faculty of Forest Sciences and Ecology at Vytautas Magnus University. His academic career spans over four decades, with a focus on applying stochastic differential equations (SDEs) to model biological populations and forest growth dynamics. Education: Graduated from Vilnius University in 1975; earned a Ph.D. in Physics and Mathematics in 1982. Research Interests: Petras Rupšys specializes in mathematical modeling of biological populations , stochastic differential equations , and statistical methods in forestry . His work bridges theoretical mathematics with practical forestry applications, developing nonlinear mixed-effects SDE models to analyze forest stand growth, stem taper, and resource dynamics. Advising and Projects: He has supervised doctoral and master's theses, including Martynas Narmontas (2023) on SDE-based forest growth models and Rokas Šturma (2016) on stochastic stand volume estimation. His projects emphasize data-driven calibration of SDEs using empirical datasets from Lithuania's forests.

Vygintas Gontisمشاهده پروفایل

استاد پژوهشی

• Statistical physics
• Dynamically chaotic systems
• Econophysics
• +۱ مورد دیگر

Vygintas Gontis is a Research Professor at Vilnius University's Faculty of Physics, working at the Experimental nuclear and particle physics center. His research spans statistical physics, dynamically chaotic systems, econophysics, and agent-based stochastic modeling with significant contributions to financial market analysis. Professor Gontis has developed influential theoretical frameworks applying physics principles to financial phenomena, creating stochastic models that explain volatility patterns, return intervals, and long-range memory effects in markets. His interdisciplinary work bridges statistical physics and economic theory, revealing universal patterns in complex market behaviors. Stochastic modeling of financial markets Long-range memory phenomena Agent-based computational finance 1/f noise analysis Complex systems dynamics Econophysics applications His publication record shows consistent scholarly output from 1987 through 2016, with recent work focusing on financial applications while maintaining connections to fundamental physics concepts. The research demonstrates evolution from quantum physics topics toward interdisciplinary financial modeling. Professor Gontis has supervised doctoral student Aleksejus Kononovičius (2011-2015) and postdoctoral researcher Rytis Kazakevičius (2020-2022). He leads the Group of Complex Physical and Social Systems and has held significant international roles including national representative for COST projects on Physics of Risk (2003-2008) and Physics of Competition and Conflicts (2008-2012).

• Wireless networks
• Gravitation
• Computer networks

Dr. Kęstutis Svirskas is a researcher at the Institute of Applied Electrodynamics and Telecommunications (IAET) at Vilnius University. His work bridges wireless network technologies with theoretical physics, particularly gravitation and particle dynamics. Research Interests include wireless networks, gravitation, and computer networks. He has contributed to electromagnetic compatibility studies and channel modeling for next-generation telecommunications. His article trends reveal interdisciplinary work, combining gravitational theory (e.g., Kerr black holes) with practical wireless network challenges (e.g., LTE performance, DVB-T compatibility, LOS/NLOS channel models). Teaching involves courses like Theory of Relativity, Routing in Local Area Networks, and Computer Communication Technologies at the bachelor's level. He also supervised thesis projects on anechoic chamber calibration and LTE network analysis. Scientific activities include translating Stephen Hawking and Leonard Mlodinov's The Grand Project into Lithuanian, contributing to science education through academic projects.

• Density Functional Theory
• Electronic Structure
• Photoelectron Spectroscopy
• +۳ مورد دیگر

Dr. Jelena Tamulienė is a Senior Researcher at the Institute of Theoretical Physics and Astronomy (ITPA) at Vilnius University. Her work focuses on computational physics, density functional theory, and electronic structure analysis of organic and inorganic materials. Affiliation: Vilnius University, Institute of Theoretical Physics and Astronomy Research: Investigates quantum mechanical properties of clusters, materials science phenomena, and phase separation dynamics using computational methods. Her publications span topics like cluster physics , electronic structure , and computational materials science , with a focus on inorganic nanomaterials and organic semiconductors. She has supervised doctoral student Laura Baliulytė and postdoc Šarūnas Masys, and contributed to science popularization through educational outreach and public lectures. She led the 2014–2016 Lithuanian-Belarus research program and participated in high-performance computing initiatives. Her collaborative work includes studies on photoelectron spectroscopy, quantum chemistry, and nanodiamond functionalization.

• Machine Learning
• Data Mining
• Fraud Detection
• +۲ مورد دیگر

Dalia Breskuvienė is a PhD student and junior researcher at the Cognitive Computing Group of Vilnius University’s Institute of Data Science and Digital Technologies. Her research spans Machine Learning, Data Mining, and Fraud Detection , focusing on optimizing classifier training for highly imbalanced data in financial contexts. Doctoral Studies : Enrolled from 2021 to 2025 under supervisor Prof. Gintautas Dzemyda. Research Focus : Addresses challenges in fraud detection by innovating feature selection, encoding, and training strategies for imbalanced datasets. Publications : Explores autoencoders, clustering techniques, and concept drift in machine learning models. Conferences : Presented her work at annual Computer Science Engineering PhD Student Conferences in Vilnius (2022–2023).

Povilas Treigysمشاهده پروفایل

استاد

• Digital Signal Processing
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Professor Povilas Treigys is a Senior Researcher and Group Leader at the Image and Signal Analysis Group within the Institute of Data Science and Digital Technologies at Vilnius University's Faculty of Mathematics and Informatics. With extensive experience in digital signal processing and machine learning applications, he leads research efforts in medical image analysis, speech processing, and maritime traffic modeling. Dr. Treigys earned his Doctor of Science in Computer Science Engineering in 2010 with a dissertation on "Development and application of graphical methods for analyzing ophthalmological and thermovision data." His academic journey has been marked by significant contributions to interdisciplinary research connecting computer science with medical applications. His research primarily focuses on digital signal processing across multiple domains including medical imaging (MRI, eye fundus), audio signals, and maritime traffic data. A key emphasis of his work is the development and application of deep learning methods to solve real-world problems in healthcare diagnostics, retail automation, and transportation safety. His recent work demonstrates a strong trend toward explainable AI in medical applications and sophisticated time series analysis for prediction tasks. Professor Treigys serves in numerous leadership roles including as a EuroHPC JU Board Member representing Lithuania, VU MIF representative on the Lithuanian Quantum Technology Association board, and as a delegate to multiple professional committees. He is an active reviewer for several prestigious journals including Computer Science, Nonlinear Analysis, Baltic Journal of Modern Computing, MDPI Sensors, and MDPI Electronics. His laboratory focuses on bridging theoretical machine learning advancements with practical applications, particularly in medical diagnostics where his team has made significant contributions to prostate cancer detection, arrhythmia classification, and ophthalmological image analysis. The group maintains strong international collaborations and regularly presents findings at major conferences in computer vision, medical imaging, and artificial intelligence.