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.
Roles & Affiliations: Assistant Professor at the Department of Organizational Information and Communication Research, Faculty of Communication, Vilnius University. Active in research projects, academic conferences, and editorial roles. Education: PhD in Mathematics and Informatics (2012), Vilnius University, Thesis: 'The applications of datamining methods to personalized learning environments.' MA in Informatics (1995), Vilnius Pedagogical University. Research Interests: Focus on e-learning methodologies, big data processing, educational technology, and business intelligence. Explores applications of machine learning in finance and personalized learning systems. Publications & Projects: Over 15 articles in peer-reviewed journals and conferences (e.g., Applied Sciences, Mykolas Romeris University Proceedings). Led the EU-funded project 'Development and Introduction of Multilingual Teacher Education Programmes in Georgia and Ukraine (DIMTEGU)' (2012–2016). Active in conference organizing and editorial work. Grants & Memberships: Participated in EU-funded projects. Member of the National Association of Distance Education (NADE), Lithuanian Association of Distance and e-Learning (LieDM), and Lithuanian Computer Society (LIKS). Labs & Teams: Involved in research groups focused on educational technology, data analytics, and digital transformation initiatives within the Faculty of Communication.
Arūnas Gudinavičius is a Professor and Vice-Dean for Science at Vilnius University's Faculty of Communication, Department of Digital Cultures and Communication. He holds a PhD in Communication and Information Sciences (2012) from Vilnius University, following a Master's in Electrical Engineering from Kaunas University of Technology (1999) and a Bachelor's in Electrical Engineering (1997). His research focuses on digital publishing, human-computer interaction, and usability in digital media, with notable projects like the 'Digital Publishing in Lithuania' initiative (2014) and contributions to the COST Action E-READ (2014-2018). Key research interests include digital book quality, e-book markets, museum website usability, and accessibility in publishing. He has published extensively on topics such as reading behavior, piracy dynamics, and digital literacy, with over 30 peer-reviewed articles and several books. Notable awards include the 2017 Vilnius University best article award (shared with colleagues). He teaches courses on digital publishing and media technologies, advising PhD students like Alisa Žarkova and Arūnas Šileris. His professional roles include editorial board memberships for journals like Information & Media and leadership in organizations such as the Lithuanian Publishers Association. He has participated in international conferences globally and led projects on digital literacy, museum accessibility, and scholarly communication.
Dr. Dervinis Donatas is an Assistant Professor at the Department of Electrical and Electronic Engineering, VU Šiauliai Academy. His research focuses on Renewable Energy, Automation, Computer Vision, and Cybersecurity, with a strong emphasis on practical applications in industrial systems and educational technologies. He holds a Doctor of Science in Electrical and Electronics Engineering and has over 22 months of academic experience. His educational background includes advanced studies in electrical engineering, complemented by a prolific career in research. Key research areas include solar energy systems, image processing, and automated systems for transportation and security. He contributed to the development of a textbook on Image Processing (2012) and has been affiliated with the eLABa research group. Donatas has authored or co-authored over 15 peer-reviewed publications, exploring topics such as energy-efficient cloud computing, password security, and real-time video analysis for human recognition. His work bridges theoretical advancements with practical implementations in fields like industrial automation and biomedical engineering. While no specific awards are listed, his publications appear in reputable journals like Applied Scientific Research and Professional Studies: Theory and Practice . His academic advising and grant activities are not explicitly detailed, though his research often involves collaborative projects with institutions like Tallinn University of Applied Sciences and Šiauliai State College. Donatas is actively involved in the eLABa research team, focusing on innovative solutions in electrical engineering and technology education. His future work continues to emphasize sustainable energy systems and advanced computer vision applications.
Vytautas Žalys is an Associate Professor and PhD at the VU Šiauliai Academy, primarily affiliated with the Department of Informatics Engineering. His research focuses on audiovisual technologies in music education, computer-assisted data analysis, and the integration of digital tools in special education contexts. He has led multiple international projects, including the 'ART HOUSE: Restoration of the Zubov Palace' and 'Digital Competence and Digitized Musical Heritage,' highlighting his commitment to innovative educational infrastructure and cultural preservation. Žalys holds a PhD and has over 35 years of professional experience, spanning roles as a music teacher, radio show creator, and project leader in educational technology. His educational background includes advanced studies in music and informatics. Key projects include developing distance education courses on ICT in music education and contributing to EU-funded initiatives like the Leonardo da Vinci project on digital technologies. His publications emphasize the application of multimedia and AI in autism education, music pedagogy, and cross-disciplinary arts integration. He actively participates in academic associations such as EERA and ATEE, furthering research in educational innovation and lifelong learning.
Linas Petkevičius serves as an Associate Professor at Vilnius University's Faculty of Mathematics and Informatics, actively teaching courses including Introduction to Quantum Computing across 10 consecutive academic years from 2016/2017 through 2025/2026 as evidenced by institutional schedules. His research demonstrates remarkable interdisciplinary breadth spanning quantum computing algorithm optimization, medical diagnostics through digital pathology analysis, and satellite-based environmental monitoring. He develops machine learning solutions for breast cancer prognosis using Ki67 heterogeneity metrics, creates quantum circuit schemes adapted to hardware constraints, and implements deep learning models for algal bloom detection in Baltic waters using Sentinel-2 data. His work consistently bridges theoretical computer science with practical healthcare and environmental applications. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research thrusts: 1) Quantum computing optimization for NISQ devices, 2) Medical image analysis focusing on spatial tumor microenvironment characterization in breast cancer, and 3) Remote sensing applications using transformer models and few-shot learning for satellite change detection. His publications show increasing specialization in combining deep learning architectures with domain-specific constraints across these fields. Scientific Awards: No scientific awards were mentioned in the provided materials. Advising and Grants: The provided texts contain no information regarding student advisement, research grants, or funded projects.
Vladimir Dolgopolov is a Senior Researcher at the Educational Systems Group of Vilnius University. His work focuses on computational thinking, STEM education, and curriculum design, with a particular emphasis on integrating digital technologies into teaching practices. Research Interests: Computational Thinking, STEM/STEAM Education, Artificial Intelligence Literacy, Curriculum Transformation Key Collaborations: Valentina Dagienė, Tatjana Jevsikova, Eglė Jasutė Recent publications highlight his contributions to Industry 5.0 education, AI literacy frameworks, and model-centered approaches to scientific programming. His work often addresses the pedagogical challenges of digital transformation and the VUCA (volatility, uncertainty, complexity, ambiguity) paradigm in higher education. He has explored semiotics perspectives in computational thinking and co-developed methodological guidelines for software learning objects in scientific programming education. Notable projects include the DECART initiative for agile curricula and studies on novice software engineering students' temperament styles. His research spans case studies on Android game-based programming motivation, inverted classroom models, and queueing system simulations for teaching scientific computing.
Assoc. Prof. Dr. Asta Slotkienė is an Associate Professor and Researcher at the Cybersocial Systems Engineering Group , Institute of Mathematics and Informatics, Vilnius University , Lithuania. She has been a faculty member since at least 2009 and is based at Akademijos St. 4, Vilnius. Education PhD in Computer Science Engineering, Kaunas University of Technology (2009) MSc in Computer Science Engineering, Kaunas University of Technology (2004) BSc in Physics and Computer Science, Šiauliai University (2002) Research Interests Dr. Slotkienė’s research spans software quality assurance , development process improvement , e-learning systems , and cognitive decision-making . She investigates how rigorous evaluation methodologies and AI techniques can enhance the reliability and usability of software products and services. Her recent work explores the intersection of large language models and automated software testing , as well as the modeling of web service quality using fuzzy logic and ontology-based approaches. Research Trends Across her latest publications, a clear trend emerges toward leveraging AI and machine learning , particularly large language models , to automate and improve software testing practices. Simultaneously, she continues to deepen the theoretical foundations of software and service quality modeling , integrating fuzzy logic , ontology engineering , and bibliometric analyses to build robust frameworks for quality evaluation. Scientific Service & Awards Program Committee Member: ACM/SIGAPP SAC (2023–2025) Organizing Committee Member: Baltic DB&IS 2024 Program Committee Member: SS AIEDUMED’25, CompSysTech’25 Reviewer for Informatica, Baltic Journal of Modern Computing, New Trends in Computer Sciences Projects & Funding 2022–2026 Master of Science in Smart, Secure and Interconnected Systems (EU Grant 101083531) 2022–2024 Embracing RAD Skills for Employability and Innovation 2020–2022 AI-Enhanced Accounting and Business Management Systems (Grant 01.2.1-LVPA-K-856-01-0083) 2014–2018 Erasmus+ “Open University for Virtual Mobility” (2014-1-LT01-KA203-000550) 2012–2015 Tempus “High Objectives of National Organizational Reform” (530284-TEMPUS+1-2012-1-ES-TEMPUS-JPHES) International Collaboration & Training Through multiple Erasmus+ teaching and learning visits (Las Palmas de Gran Canaria, Madeira, Azores, Maia), as well as participation in DeepLearn schools and professional training (Devbridge/Cognizant Softvision, Robotic Process Automation, Creative Commons, Contextual Modeling), Dr. Slotkienė actively fosters cross-border academic cooperation and continuous professional development.
Aida Pliuškevičienė serves as an Associate Professor and Affiliated Scientist at Vilnius University's Institute of Data Science and Digital Technologies within the Cybersocial Systems Engineering Group. Her research is centered at the intersection of mathematical logic and theoretical computer science. Her primary research interests include Temporal Logic , Modal Logic , and Proof Theory , with significant contributions to sequent calculi, loop-check elimination, and termination methods in automated deduction. Her work demonstrates consistent focus on formal verification systems and computational logic frameworks. Analysis of her 25+ publications reveals sustained expertise in developing decision procedures for temporal and modal logics, with recent work advancing cyclic sequent calculus strategies (2025) and loop-check specifications (2022). Her research trajectory shows evolution from foundational work on Gentzen-type calculi (1992) to contemporary applications in distributed knowledge systems. As an active researcher at Vilnius University's Akademijos St. 4 campus, she collaborates extensively with Romas Alonderis, Regimantas Pliuškevičius, and Haroldas Giedra on temporal logic frameworks. Her publication record in journals like Lithuanian Mathematical Journal and Journal of Automated Reasoning demonstrates sustained scholarly output over three decades.
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.
Achilleas Achilleos serves as a Lecturer at Frederick University's School of Engineering, Department of Electrical and Computer Engineering and Informatics, and co-directs the Mobile Devices Laboratory (MDL) within the Frederick Research Center. His academic leadership spans software architecture design for adaptive systems and pervasive computing environments. Ph.D. in Computer Science, University of Essex (EPSRC/BT co-funded) M.Sc. in Computer and Information Networks B.Sc. in Computer Engineering His research centers on engineering methodologies for context-aware systems, with emphasis on IoT integration and smart city applications. He develops model-driven frameworks bridging service-oriented architectures and cloud computing infrastructures to address real-time adaptability challenges in mobile environments. As MDL Lab co-director, he manages a 5-member research team executing 10 active and 3 completed projects including EUROSTARS AURA-CARE, Erasmus+ OLMEdu (as coordinator), and EU H2020 initiatives. His work demonstrates strong industry-academia collaboration through British Telecom partnerships and national innovation projects like SportsTraveler76.
Jūratė Urbonienė is a researcher at the Utena University of Applied Sciences, specializing in educational technology and digital learning. She has collaborated with colleagues like Rūta Puidokaitė-Savickienė and Giedrė Šakalytė on studies addressing e-learning trends and student needs. Her work intersects with technology, sustainability, and higher education systems, reflected in her participation in Erasmus+ and National Education Agency projects. Key affiliations: Association of Computing Machinery (ACM), Lithuanian National Distance and e-Learning Association (LieDM), Lithuanian Computer Society (LIKS). Projects: 'Discover Vyžuona' mobile app development, 'Digital Reality in Foreign Language Teaching for Medical Specialists (DR FLEMP)', and 'Digital Education Transformation (EdTech).' Her research focuses on integrating digital tools into education, leveraging artificial intelligence for teaching processes, and aligning technology use with sustainable development goals. She has explored energy consumption patterns influenced by tech habits and contributed to EU-focused initiatives on educational integration. Jūratė actively collaborates through conference presentations, including talks on 'Technology Use and Sustainability' and 'Innovation and Sustainable Development in Technology-Based Learning.' She serves as the editor-in-chief of the Utena College scientific journal 'Insights.'
Ingrida Lagzdinytė-Budnikė serves as an Associate Professor and Head of Department at the Faculty of Informatics, Kaunas University of Technology (KTU), based at Studentų g. 50 in Kaunas, Lithuania. Her institutional role centers on academic leadership within Lithuania's premier technical university. Her research profile spans core computing disciplines including Computer Science, Information Systems, Software Engineering, Data Science, Artificial Intelligence, and Cybersecurity, reflecting the Faculty of Informatics' strategic focus areas. These fields drive KTU's contributions to Baltic technology innovation and digital infrastructure development. As departmental head, she oversees academic operations and faculty development while maintaining active teaching responsibilities. Her leadership shapes curriculum design and research initiatives across undergraduate and graduate programs in informatics.
Dovilė Kurpytė-Lipnickė is a Lecturer at Vilnius Tech and a Visiting Lecturer at ISM. She is pursuing a PhD in Electrical and Electronics Engineering at Vilnius Tech. Her academic journey includes an MSc with Honors in Informatics Engineering (Vilnius Tech), a BMBA in Accounting and Auditing (Vilnius University), and a BSc in Electrical and Electronics Engineering (Vilnius Tech). Her research focuses on Electronics Engineering and Informatics Engineering , with teaching expertise in these fields, as well as E-Business Systems , Android Programming , and Script Programming . She is the first and only recipient in the Baltic States of the IEEE Award , recognizing her contributions across 58 countries in Europe, Africa, and the Middle East. Her technical proficiencies span programming languages (C/C++, Java, JavaScript), mathematical tools (Matlab), and platforms like OpenCV and Android development. She holds strong expertise in MS Office, Linux, and various engineering software (Altium, LabVIEW).
Janis Lanka serves as a Visiting Lecturer at ISM and Head of Product Management. He is an experienced leader in software product development, bridging business priorities, user needs, and technology across ventures including startups, biotechnology firms, and global consultancies. With 19 years of expertise, he specializes in scaling impactful products and mentoring cross-functional teams of product managers, designers, and engineers. His professional practice spans diverse industries such as global telecommunications, life sciences, retail, and platform brands like Nike, Microsoft, Starbucks, and others. Janis focuses on clarifying client visions, validating product ideas, conducting Due Diligence for Product departments, and optimizing customer engagement strategies. He teaches New Product Development and Service Innovation (GRAV025) at ISM, integrating academic rigor with real-world industry challenges. Awards: None explicitly listed. Advising & grants: No specific details provided. Labs/teams: Not mentioned in available text.
