جست‌وجوی استاد و پژوهشگر

Alfredo Hernandez Sanchezمشاهده پروفایل

پژوهشگر ارشد

• FinTech
• International Political Economy
• Computational Social Sciences
• +۵ مورد دیگر

Dr. Alfredo Hernandez Sanchez is a Research Fellow at the Institute for International Relations and Political Science (TSPMI) at Vilnius University and a Senior Fellow at the Institute for Studies on the Mediterranean and the Middle East (IBEI). He holds a PhD in Political Science from Central European University and a BA in International Relations from UNAM, with expertise in Computational Social Sciences, Natural Language Processing (NLP), and Quantitative Text Analysis. His work bridges FinTech, International Political Economy, and anti-corruption research, including policy contributions for UNESCO, Transparency International, and the IADB. PhD in Political Economy, Central European University (2020) BA in International Relations, UNAM His research focuses on FinTech regulation , Big Data applications in governance, and corruption risk measurement using large-scale datasets. Current projects include the Political Economy of FinTech grant and the Water Integrity Risk Index initiative with UNESCO. Publications span Springer, Bloomsbury, and Emerald, covering topics like pandemic-era procurement ethics and defense corruption networks. Recent work highlights FinTech policy , anti-corruption metrics , and quantitative methods in political economy, with a trend toward AI-driven analysis of governance structures. He is also a Data Visualization enthusiast, contributing to the D·Viz blog and academic discourse via Bluesky. Notable affiliations include: Marie-Curie ERA Postdoctoral Fellow (Vilnius University) Research Fellow (IBEI) Contributor to UNESCO and IADB projects

• Generalized Nets
• Intuitionistic Fuzzy Sets
• Decision Making Under Uncertainty
• +۳ مورد دیگر

Assoc. Prof. Vassia Atanassova, PhD is an Associate Professor in the Bioinformatics and Mathematical Modelling Department at the Institute of Biophysics and Biomedical Engineering , Bulgarian Academy of Sciences. She holds a PhD in Informatics and Computer Sciences (2013) and has been actively contributing to generalized nets, intuitionistic fuzzy sets, and decision-making under uncertainty since 2002. Education : PhD in Informatics and Computer Sciences (2013), Institute of Information and Communication Technologies – BAS Master in Marketing (2009), University of National and World Economy Bachelor in Informatics (2004), Faculty of Mathematics and Informatics, Sofia University Her research focuses on intuitionistic fuzzy logic applications, generalized net modeling , and Wiki technologies for knowledge transfer . She has developed novel intuitionistic fuzzy operators and conducted extensive work on intercriteria analysis for complex systems. Recent publications emphasize fuzzy decision-making frameworks (2015-2019), with applications in Algorithm optimization Economic modeling Bioinformatics Medical data analysis Scientific Awards : Youngest Researcher Award 'Ivan Evstratiev Geshov' (2011) 2nd Award, VIII Youth Session of Federation of Scientific-Technical Unions (2010) She serves as Guest Editor for MDPI Mathematics and technical editor for international journals. Her teaching includes PhD-level courses on Wikipedia-based knowledge transfer and fuzzy set theory at Bulgarian universities.

• Theater Studies
• Cultural Studies
• Intercultural Communication
• +۳ مورد دیگر

Ina Pukelytė is an Associate Professor at the Department of Theater Studies , Faculty of Arts , Vytautas Magnus University . Her research focuses on intercultural art exchange in Eastern and Central Europe, with particular emphasis on global contexts and local practices. Active in creative industries research since 2017 Leads the research cluster on intercultural art exchange Specializes in cultural policy and community-based cultural projects Notable research trends identified through her work include: Impact of cultural branding initiatives on regional development Integration of digital technologies in cultural institutions Volunteer motivation dynamics in performing arts organizations Evolving cultural communication genres in mediatized environments Her projects have examined: Kaunas 2022 European Capital of Culture program Intercultural festivals like Palanga Jurginės Cultural centers' role in regional communities Visual arts investment frameworks in Lithuania

• Land Economics
• Management and Development
• Urban Regeneration and Sustainable Communities
• +۳ مورد دیگر

Vida Malienė is a Visiting Professor at the Department of Land Use Planning and Geomatics, Faculty of Water and Land Management, Vytautas Magnus University Agriculture Academy. She contributes to the Bioeconomy Research Institute since 2023 and participated in international collaborations with Liverpool John Moores University. European Academy of Land Use and Development (Executive Board Member) International Council for Research and Innovation in Building and Construction (CIB) European Group of Operational Research Chartered Property Valuer Her research spans real estate markets , urban regeneration , land management economics , and application of multi-criteria evaluation methods . She specializes in sustainable housing , land consolidation , and affordable housing policies , with focus on Baltic and European contexts. Key publication trends include land use planning (63% of work), environmental engineering (58%), civil engineering (47%), and management sciences (13%). Recent articles explore bio-economy applications , agricultural land transformation , and value capture mechanisms across Europe. She holds a PhD in Technological Sciences (2000) and has authored over 100 publications, including 50+ peer-reviewed journal articles, 3 monographs, 20+ book chapters, and editorials. Her work is cited 2949 times (2023 metrics), with h-index-23 and i10-index-36. Languages: Lithuanian (native) English (fluent) German (fluent) Russian (fluent)

• Cybersecurity
• Machine Learning
• Network Analysis
• +۵ مورد دیگر

Linas Bukauskas is a Professor at Vilnius University's Department of Informatics under the Faculty of Mathematics and Informatics. Since 2005, he has supervised academic projects and taught courses in cybersecurity, with a focus on practical skill assessment, network analysis, and human factors in security systems. Research Interests: Cybersecurity, Machine Learning, E-Vehicle Infrastructure, Cyber Defense Training Key Contributions: Development of cybersecurity training platforms, behavioral analysis in cyber exercises, and novel network flow modeling techniques Recent Work: Focus on maritime cybersecurity resilience, individualized risk assessment frameworks, and AI integration in smart learning environments

• Cyber and information security
• Application of machine learning methods
• Information systems audit
• +۴ مورد دیگر

Viktoras Bulavas is an Adjunct Professor at Vilnius University's Faculty of Physics and a PhD student in the Cognitive Computing Group at the Institute of Data Science and Digital Technologies. He works at Saulėtekio al. 9, ITTC (JK2) room 207, Vilnius, with contact number +370 5 236 6202. His educational background includes a Master's degree in Physics from Vilnius University (1991) and a Master's degree in Public Administration from BI Norwegian School of Management (1997). Since 2004, he has been teaching Introduction to Project Management to 4th-year undergraduate students at the Faculty of Physics. Bulavas specializes in cyber and information security, with research focusing on applying machine learning methods for early detection of cyber incidents. His work spans information systems audit, information technology project management, and management of scientific research projects. His doctoral research, supervised by Prof. Habil. Dr. Gintautas Dzemyda with consultant Prof. Dr. Virginijus Marcinkevičius, runs from October 1, 2017 to September 30, 2026. His publication record demonstrates consistent contributions to network security and intrusion detection, with a focus on machine learning applications. His work shows progression from exploring data visualization methods (2018) to investigating fractal dimensionality (2019) and ultimately optimizing machine learning model performance (2021). Professional certifications include: ECPC-B DPO Professional from the European Center on Privacy and Cybersecurity (2019) Certified Scrum Master from Scrum Alliance (2011) CRISC certification from ISACA (2011) CGEIT certification from ISACA (2009) CISA certification from ISACA (2006) Bulavas has participated in significant academic activities including an Erasmus+ Doctoral Internship at Gdańsk University of Technology (2020-2021) and multiple International Summer Schools on Deep Learning at the same institution (2018, 2019).

• 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.

• Reinforcement Learning
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Oskaras Klimašauskas is a Researcher affiliated with the Cognitive Computing Group at Vilnius University's Institute of Data Science and Digital Technologies. His work focuses on reinforcement learning applications in autonomous vehicle navigation and route optimization. His research explores Artificial Intelligence , Machine Learning , and Visual Environment Development . Recent publications (2024-2025) demonstrate his expertise in applying reinforcement learning to autonomous driving scenarios, including route navigation, track driving, and interactive route computing environments. The articles reflect interdisciplinary work at the intersection of Computer Science , Data Science , and Software Engineering . Key sub-fields include simulation, optimization, intelligent navigation systems, and vehicle control algorithms. Though no formal awards are listed, his publications indicate active research contributions.

• Cybersecurity
• Machine Learning
• Keystroke Dynamics
• +۶ مورد دیگر

Arnold Budžys is a Junior Researcher at the Vilnius University Institute of Data Science and Digital Technologies , focusing on cybersecurity, machine learning, and behavioral biometrics. His work addresses critical infrastructure security, insider threat detection, and keystroke dynamics-based authentication. Research Highlights : Keystroke biometrics, anomaly detection, deep learning, data fusion, and red team tactics. Technical Focus : Behavioral analysis, neural networks, security frameworks, and adversarial attack modeling. His publications reveal a trend toward integrating advanced AI techniques with cybersecurity protocols to enhance authentication accuracy and threat prevention in sensitive systems.

Šarūnas Paunksnisمشاهده پروفایل

استاد

• Interdisciplinary Studies
• Philosophy
• Sociology
• +۲ مورد دیگر

Šarūnas Paunksnis is a Professor at Kaunas University of Technology's Faculty of Social Sciences, Arts and Humanities. His research emphasizes interdisciplinary approaches to philosophy, sociology, media, and technology, with a focus on critical cultural analysis developed through international experiences in New York, London, Damascus, and India. His research explores technological shifts in 21st-century society, examining how digital platforms shape cultural perceptions. Key interests include: Critical analysis of technology's societal impact Cultural representations in media Interdisciplinary research methodologies Digital culture evolution Publications focus on cultural transformations in Indian cinema and critical analyses of technology's societal impacts, consistently examining the intersection of media representations and cultural identity.

Goda Klumbytėمشاهده پروفایل

مدرس

• Critical Algorithm Studies
• Science and Technology Studies
• Human-Computer Interaction Design
• +۷ مورد دیگر

Goda Klumbytė is a Lecturer and post-doctoral researcher at the University of Kassel, working within the Participatory IT Design department in the Faculty of Electrical Engineering and Computer Science. She is an interdisciplinary scholar bridging informatics with humanities and social sciences, with particular expertise in feminist new materialism, posthumanism, and human-computer interaction. Her research focuses on creating more contextualized and accountable machine learning systems through feminist and critical theoretical approaches. Her research interests include Critical Algorithm Studies, Science and Technology Studies, Human-Computer Interaction Design, Feminist Epistemology, Critical Theory, Posthumanism, and New Materialism. She approaches the study of algorithmic systems from a feminist perspective that emphasizes situated knowledges, intersectionality, and material-semiotic approaches to technology design. Her recent publications demonstrate a clear trend toward developing feminist frameworks for explainable AI and accountable machine learning systems. Her work examines how critical theoretical concepts from social sciences and humanities can be integrated into computing practices, with particular attention to how power relations and structural inequalities manifest in algorithmic systems. She has been particularly active in exploring how feminist intersectional perspectives can reshape approaches to AI explainability and accountability. Co-edited 'More Posthuman Glossary' with R. Braidotti and E. Jones (Bloomsbury, 2022) Published in 'Posthuman Glossary' (Braidotti & Hlavajova, 2018) Contributed to 'Everyday Feminist Research Praxis' (Leurs & Olivieri, 2015) Published in journals including Online Information Review, Digital Creativity and ASAP Presented at major informatics conferences including ACM's CHI, nordiCHI and FAccT Dr. Klumbytė leads significant research projects including 'AI Forensics: Accountability through Interpretability in Visual AI Systems' (funded by Volkswagen Foundation, 2022-2025) and 'CF+: Reconfiguring Computing Through Cyberfeminism and New Materialism' (University of Kassel, 2018-2019). She also serves as one of the editors of the critical computing blog 'engines of difference,' which provides a platform for critical perspectives on computing and technology.

Daunys Gintautasمشاهده پروفایل

استاد

• Computer Science
• Environmental Science
• Biometrics
• +۷ مورد دیگر

Roles & Affiliation: Professor at the Regional Development Institute of Šiauliai Academy (Vilnius University). Previously served as Professor and Head of the Department of Electronics at Šiauliai University. Specializes in Computer Science, Environmental Science, and Biometrics, with a focus on airborne pollen recognition, deep neural networks, and bioaerosol monitoring. Doctorate in Electrical and Electronic Engineering from Kaunas University of Technology (1999). Research Interests: Combines computer vision and machine learning to advance automated pollen classification, allergen forecasting, and health impact analysis. Explores applications of AI in environmental monitoring, biometrics, and medical diagnostics. Publications: Over 50 peer-reviewed articles, with recent work emphasizing real-time pollen detection systems, health correlations of airborne allergens, and automated bioaerosol monitoring. Key projects include EU-funded initiatives on synergistic effects of pollen and air quality, and real-time pollen forecasting. Grants & Projects: Led EU FP6 projects (COGAIN, MICOLE) on eye-tracking technology for disabled users. Active in Lithuania’s Research Council and EU Structural Funds projects focusing on pollen and environmental health. Labs & Teams: Collaborates with interdisciplinary teams in Šiauliai Academy’s Department of Electronics and bioaerosol research groups. Part of international networks like ISCA and IEEE, contributing to standards in eye-tracking and environmental monitoring.

• Analytic Number Theory
• Riemann Zeta Function
• Dirichlet L-functions
• +۵ مورد دیگر

Professor Igor Belov is a Senior Researcher and Professor at Vilnius University's Institute of Data Science and Digital Technologies, specializing in analytic number theory, information security, and mathematical modeling. His research spans theoretical mathematics with practical applications in finance and computer science, particularly focusing on zeta functions, prime number theory, and stable distribution models. Education: Doctor of Physical Sciences (Mathematics) from Vilnius University and Vilnius Gediminas Technical University (2004) Master's degree in Statistics from Vilnius University (1999) Bachelor's degree in Mathematics Applications from Vilnius University (1997) Professor Belov's research interests center on analytic number theory with emphasis on Riemann zeta function and Dirichlet L-functions, combinatorial analysis, information security, and mathematical modeling of financial data using stable distributions. His recent work explores fractal structures related to zeta functions, efficient algorithms for zeta function calculations, and applications of machine learning in financial document analysis and securities price forecasting. His publication record demonstrates a strong trajectory from pure mathematical research toward interdisciplinary applications. While maintaining a robust foundation in analytic number theory, his recent work increasingly bridges theoretical mathematics with practical computing applications, particularly in financial modeling and information security. This evolution reflects a strategic expansion of his research impact across multiple domains. Scientific Awards: 1st place at the Vilnius Young Mathematicians' Olympiad (1990) Honorable mention at the Lithuanian Young Mathematicians Olympiad (1991) Letter of Commendation at the Lithuanian Young Mathematicians Olympiad (1992) Professor Belov actively supervises doctoral research and has served on numerous dissertation defense committees. He currently mentors four doctoral students working on zeta function algorithms, financial forecasting, document recognition, and blockchain acceleration. His research has been supported by multiple grants including the LMT project P-SV-23-9 on Mandelbrot bulbs visualization associated with the Riemann zeta function. He has also participated in international research collaborations at CINECA supercomputing center and Karlsruhe Institute of Technology. As a member of the Smart Technologies Research Group, Professor Belov contributes to Vilnius University's leadership in mathematical research and its applications, particularly in the areas of zeta function analysis and computational finance.

• Stochastic Programming
• Mathematical Modeling
• Financial Mathematics
• +۷ مورد دیگر

Prof. habil. dr. Leonidas Sakalauskas is an Affiliated Scientist at the Smart Technologies Research Group within the Institute of Data Science and Digital Technologies at Vilnius University. His extensive research career spans mathematical modeling, stochastic programming, and statistical analysis with significant contributions across multiple disciplines. He maintains an active research profile with recent publications extending into 2025. Professor Sakalauskas' research focuses on stochastic programming, mathematical modeling, financial mathematics, statistical analysis, optimization, and queueing theory. His work demonstrates a consistent pattern of interdisciplinary research, bridging theoretical mathematics with practical applications in finance, social sciences, and computer science. He has developed innovative approaches to agent-based modeling, fractal analysis, and Monte Carlo methods, contributing significantly to both theoretical frameworks and practical implementations. His recent publications reveal a continuing evolution of research interests, with increasing emphasis on data science applications, computational social science, and advanced statistical modeling techniques. The articles demonstrate sophisticated methodological approaches to complex problems across diverse domains including financial modeling, social cohesion analysis, and network performance optimization. Throughout his career, Professor Sakalauskas has maintained a strong publication record in high-impact journals and conference proceedings, reflecting his ongoing engagement with the international research community. His work shows consistent methodological rigor combined with practical relevance across multiple application domains. Professor Sakalauskas has collaborated extensively with researchers across Lithuania and internationally, demonstrating strong teamwork and interdisciplinary engagement. His research has practical applications in financial modeling, social science analysis, and computational systems optimization, contributing to both theoretical advances and real-world implementations.

Laura Ringienėمشاهده پروفایل

پژوهشگر

• Educational Data Analysis
• Statistical Modeling
• Multilevel Regression
• +۴ مورد دیگر

Laura Ringienė is a Researcher and Information Technology Administrator at Vilnius University's Institute of Data Science and Digital Technologies, where she works in the Interdisciplinary Statistical Research Group. She holds a PhD in Computer Science Engineering obtained in 2014 from Vilnius University's Institute of Mathematics and Informatics. Her professional activities span research, teaching, and technical administration within the academic environment. Dr. Ringienė earned her educational credentials at Vilnius Pedagogical University, completing her Bachelor's degree in Informatics in 2006 and Master's degree in Informatics in 2008, both from the Faculty of Mathematics and Informatics. Her doctoral dissertation, Hybrid Neural Network for Multidimensional Data Visualization , was defended in 2014 and falls under Technological Sciences, Computer Science Engineering. Her research focuses on statistical analysis of educational data, with particular expertise in multilevel regression, structural equation modeling, and analysis of international large-scale assessment data (PISA, TIMSS, PIRLS). She has developed the R program package EFECTAS specifically designed for analyzing international education research data. Her work examines educational equity, reading achievement gaps across EU countries, socioeconomic factors affecting student performance, and the impact of preschool education on later academic outcomes. Analysis of her publication record from 2020-2025 reveals a strong concentration on educational data science, with recurring themes of statistical modeling of international assessment data, educational equity analysis, and application of advanced statistical techniques to understand educational systems across Europe. Her work frequently employs PISA, TIMSS, and PIRLS datasets to examine cross-national educational patterns and policy implications. Dr. Ringienė has been actively involved in the EFECTAS project (2018-2022), which was financed by the European Social Fund under a grant agreement with the Research Council of Lithuania. This project focused on analyzing the efficiency and productivity of education systems in EU countries using secondary large-scale data. She teaches undergraduate courses at Vilnius University, including Big Data Analytics and Business Process Robotization since 2019. Her professional development includes extensive training in Robotic Process Automation (UIPath), Structural Equation Modeling, Multilevel Linear Modeling, and various Big Data technologies. She is part of the Interdisciplinary Statistical Research Group, which focuses on applying advanced statistical methods to solve complex problems in education and other domains.