Rimantas Kybartas , Associate Professor at Vilnius University's Faculty of Mathematics and Informatics , specializes in machine learning and software systems architecture . His research focuses on multi-class classification methodologies, including pair-wise classifiers and fuzzy template systems. Current academic affiliation: Vilnius University Key research domains: Neural Networks, Ensemble Learning, Pattern Recognition Teaching focus: Software Systems Architecture and Design His publication record from 2010-2012 demonstrates expertise in solving multi-classification challenges through innovative ensemble architectures and similarity feature engineering. Notably, he has developed frameworks for mineral recognition and generalized multi-category neural network systems. Recent publications reveal emphasis on: Optimizing pair-wise classifier ensembles Addressing complexity in neural network design Domain adaptation techniques for classification tasks Statistical learning in multi-class contexts
Prof. Dr. Virginijus Marcinkevičius is a Professor at Vilnius University , serving as the head of the Smart Technologies Research Group and the Artificial Intelligence Laboratory within the Institute of Data Science and Digital Technologies . He is also a Senior Researcher , Project Lead Researcher , and Group Leader . Based in Vilnius, Lithuania, he has been instrumental in advancing research in machine learning , artificial intelligence , cybersecurity , and natural language processing . Research Interests: Machine Learning & AI Cybersecurity & Threat Detection Natural Language Processing Hyperspectral Imaging & Remote Sensing Autonomous Systems & Robotics Big Data & Cloud Computing His work spans both theoretical and applied aspects, including IoT security , visual analytics , and intelligent decision support systems . Recent projects include the development of propaganda detection systems , hyperspectral unmixing algorithms , and autonomous driving agents . Doctoral Supervision: He has supervised 19+ PhD students and 5+ consultants , covering topics from machine learning in cybersecurity to neural machine translation and autonomous UAV navigation . Projects & Grants: He has led or contributed to 15+ national and EU-funded projects , including: CognitiveSTATS – COVID-19 data literacy platform Propaganda and Disinformation Research – ML-based detection DAMIS – Data mining system for national research Raštija 2 – Lithuanian language resource integration Publications: He has authored or co-authored 60+ peer-reviewed publications in journals like IEEE Access , Informatica , Frontiers in Psychology , and Machine Vision and Applications . Professional Memberships: He is a member of the Lithuanian Computer Society , Lithuanian Mathematical Society , and Lithuanian Operations Research Society .
Dr. Jolita Bernatavičienė serves as a Senior Researcher at Vilnius University's Institute of Data Science and Digital Technologies within the Image and Signal Analysis Group. With a Doctorate in Technological Sciences (Informatics), she has established herself as a leading researcher in medical image analysis and artificial intelligence applications in healthcare. Her extensive research portfolio spans over 15 years of continuous contributions to the field. Dr. Bernatavičienė's research interests primarily focus on medical image analysis, particularly in ophthalmology and oncology applications. Her work integrates advanced machine learning techniques with medical diagnostics, specializing in eye fundus image analysis for glaucoma detection and prostate MRI analysis for cancer identification. She has made significant contributions to deep learning architectures, signal processing methodologies, and data analysis frameworks applicable to biomedical challenges. Her publication record demonstrates strong trends in applying cutting-edge AI techniques to solve concrete medical problems, with a noticeable shift toward more sophisticated deep learning architectures in recent years. The research spans multiple medical domains including ophthalmology, cardiology, oncology, and renewable energy systems monitoring, reflecting her interdisciplinary approach to data science applications. Leader of International Conference 'Data Analysis Methods for Software Systems (DAMSS)' 2015-2024 Member of IEEE Computer Society section (since 2022) Member of the Council of the Lithuanian Computer Association, Artificial Intelligence Section Member of the Lithuanian Operations Research Society Expert at the Science, Innovation and Technology Agency (MITA) (2020-2022) Dr. Bernatavičienė actively supervises doctoral and master's students, with current doctoral student Roman Surkant working on prostate MRI analysis. She leads multiple significant research projects including 'Developing Talents in Artificial Intelligence to Solve Disruptive Environmental Problems' and serves as scientific leader for the Research Council of Lithuania funded project on cardiac MRI texture analysis. Her work has been supported by various national and international funding mechanisms including COST activities, EuroHPC programs, and Lithuanian national research grants. She is principal investigator for the long-term project developing a database of depersonalized fundus images (2018-2030) and has led numerous projects related to medical image analysis, AI applications in healthcare, and data science methodologies. Her research group maintains strong international collaborations through COST actions and other European research networks.
Dr. Jolanta Miliauskaitė serves as an Associate Professor and Researcher at the Cybersocial Systems Engineering Group within Vilnius University's Institute of Data Science and Digital Technologies. Her academic position reflects her expertise in cybersocial systems engineering and related fields, with a particular focus on the interface between cyberphysical and cybersocial systems. She maintains an active research profile with numerous publications and conference presentations focusing on fuzzy logic applications, quality of service modeling, and information systems. Dr. Miliauskaitė's research centers on cybersocial systems engineering, with significant contributions to understanding complexity issues in data-driven fuzzy inference systems and developing frameworks for membership function construction. Her work bridges theoretical computer science with practical applications in software engineering, particularly in fuzzy logic applications for quality of service planning in enterprise systems. She has conducted systematic literature reviews and developed methodologies for handling uncertainty in information systems. Her publication record shows a consistent research trajectory from foundational work on algorithm concepts to specialized research on interval type-2 fuzzy sets. Recent publications (2023-2024) demonstrate expansion into social factors affecting software quality and more sophisticated modeling of web service quality. Her work often combines theoretical insights with practical case studies, particularly in enterprise business services and web service quality modeling. DAMSS 2019 Best Poster Award for "On issues related to interval type-2 membership function development" Dr. Miliauskaitė actively mentors doctoral students, currently supervising Darius Sabaliauskas whose dissertation focuses on the "Reasoning mechanism of cognitive systems" (2024-2028). She has participated in significant research projects, including the National Complex Program Project "Theoretical and Engineering Aspects of the Development and Use of Internet of Services Technologies in High-Performance Computing Platforms" under Prof. G. Dzemyda's supervision (2012-2015). Her qualifications are continuously enhanced through Erasmus+ programs and specialized training in scientific methodology. As an active member of the academic community, Dr. Miliauskaitė serves on organizing committees for major conferences including Baltic DB&IS (2012, 2018, 2024) and DAMSS (2018), and participates in program committees for ICMarkTech'24, SAC 2025, SS AIEDUMED'25, and CompSysTech'25. She is also a member of the Lithuanian Computer Society (LIKS), contributing to the broader computer science community in Lithuania.
Assoc. Prof. Dr. Audronė Lupeikienė serves as an Associate Professor and Group Leader at the Cybersocial Systems Engineering Group within Vilnius University's Institute of Data Science and Digital Technologies (formerly Institute of Mathematics and Informatics). Holding a Doctor of Science degree, she has established herself as a leading researcher in information systems engineering with over two decades of scholarly contributions. Her academic profile demonstrates sustained excellence in research, teaching, and service within the Lithuanian and international academic community. Dr. Lupeikienė's research expertise spans Information Systems Engineering , Computer Service Systems Engineering , Knowledge Systems Engineering , and Software Systems Engineering . Her work explores both theoretical foundations and practical applications of information systems, with particular emphasis on service-oriented architectures, business process management systems, and ontology-based component programs. She investigates how these systems can be optimized for performance, quality of service, and effective business-IT alignment in digital environments. Her recent scholarly output (2020-2024) reveals a clear evolution in research focus from foundational work on component-based systems to contemporary investigations of digital business transformation. Notably, her research has expanded into interdisciplinary applications including telemedicine systems for cardiac rehabilitation and energy harvesting technologies, demonstrating versatility across domains while maintaining core expertise in information systems engineering. This trajectory reflects her ability to adapt theoretical frameworks to emerging technological and societal challenges. Dr. Lupeikienė has successfully led and participated in significant research projects including the EU structural support project "Theoretical and engineering aspects of the development and use of Internet of Services technologies in high-performance computing platforms" (2012-2015), the "PEN: Production Effectiveness Navigator" EuroStars project (2011-2014), and earlier work on "Engineering problems of ontology-based component programs" (2003-2005). She has served on organizing committees for numerous international conferences and is an active member of the Lithuanian Computer Association. As an educator, Dr. Lupeikienė has taught a comprehensive range of courses reflecting the evolution of information systems education: Agent technologies (2005-2008), Decision-making systems (since 2003), Information systems (since 2002), Database Theory and Practice (2000-2003), and Computerization of management processes (1995-2002). Her teaching portfolio demonstrates adaptation to technological advancements while maintaining focus on core principles of system design and implementation. Her leadership of the Cybersocial Systems Engineering Group focuses on the intersection of social systems and technological infrastructure, exploring how to design, implement, and optimize systems that effectively serve both organizational and social needs in today's increasingly interconnected digital landscape.
