Dr. Rytis Kazakevičius is a Researcher at Vilnius University's Institute of Theoretical Physics and Astronomy (ITPA), focusing on statistical physics, anomalous diffusion, and 1/f noise in physical and socio-economic systems. He has published extensively on nonlinear stochastic differential equations and agent-based modeling. His work includes collaborations with colleagues like J. Ruseckas and A. Kononovicius, funded by the European Union (project No 09.3.3-LMT-K-712-19-0017). He also teaches undergraduate seminars on laboratory work preparation using software tools. Publications reveal expertise in Lévy flights, time-subordinated Langevin equations, and power-law statistics in nonhomogeneous environments. He serves as a reviewer for journals like Europhysics Letters and Physica A: Statistical Mechanics and its Applications.
Dr. Algimantas Kežionis is a Chief Researcher at the Institute of Applied Electrodynamics and Telecommunications (IAET) within Vilnius University . His work focuses on impedance spectroscopy and ionic conductivity in advanced materials, particularly solid oxide ionics . Research spans microwave material analysis , charge carrier dynamics , and high-temperature conductivity . He leads projects on impedance spectrometer development , radio wave propagation modeling , and electromagnetic response measurements . His 15+ publications reveal expertise in solid-state electrochemistry , dielectric relaxation , and analytical representation of impedance data . As a thesis supervisor , he has guided 50+ bachelor’s and master’s students and one doctoral student . His international recognition includes an ISSFIT-12 invited lecture (2016). He also serves as a peer reviewer for journals like Advanced Functional Materials and Solid State Ionics .
Renata Minkevičiūtė is a Researcher at the Institute of Theoretical Physics and Astronomy (ITPA) under Vilnius University. Her work focuses on Astrophysics, particularly stellar chemical composition, stellar evolution, and galactic chemodynamical evolution, with a strong emphasis on spectroscopic studies. Research Interests include the chemical composition of stars, elemental abundance analysis, and galactic evolution. She has contributed to major projects like the Gaia-ESO Survey, investigating chemical clocks, extra mixing in giants, and multi-population dynamics in globular clusters. Her spectroscopic expertise spans dwarf stars, red giants, and galactic disc substructures. Publications highlight her involvement in the Gaia-ESO collaboration, TESS mission follow-ups, and northern sky dwarf star studies. Her work connects stellar composition to exoplanetary systems, examines nucleosynthesis patterns, and explores galactic archaeology through metallicity gradients. Supervision : In 2021, she supervised Justas Plaušinaitis for his bachelor's thesis. She also mentors students through summer/semester practices. Science Popularization : She actively engages in educational outreach, delivering lectures at Lithuanian schools, Molėtai Astronomical Observatory events, and media appearances on programs like Smalsumo genas and Mokslo sriuba . Expertise : Member of the OPTICON Telescope Observation Time Allocation Committee since 2018 and contributor to European Space Agency projects. Her institutional roles include participation in research groups and international collaborations.
Dr. Liudas Tumonis is a Senior Researcher at the Institute of Chemical Physics , Vilnius University, with extensive experience in electric propulsion for small satellites , inertial navigation systems , and finite/discrete element methods . He has led projects such as the LituanicaSat-2 satellite development and contributes to the TRACOFUNAT and TORTILAC initiatives under ESA-Lithuania collaborations. Key research areas: Space propulsion, Structural mechanics, Fluidics Active in science communication via Cafe Scientifique and national media Teaches Fundamentals of Aerospace Technologies and mechanics exercises His recent publications focus on satellite propulsion systems , particle impact modeling , and structural vibration analysis , with applications in aerospace and mechanical engineering. He specializes in hybridizing computational methods (finite/discrete element) with experimental validation for material behavior under extreme conditions. Dr. Tumonis has supervised student theses on topics like nano-satellite rocket engines and MEMS-based navigation systems , while contributing to open-source projects like FreeCAD translation. He remains actively involved in science outreach, including TV and radio appearances discussing Mars exploration and lunar missions.
Prof. habil. dr. Gintautas Dzemyda is a leading Lithuanian computer scientist, Professor and Senior Researcher at Vilnius University Institute of Data Science and Digital Technologies (VU DMSTI), and Head of the Cognitive Computing Group . He is simultaneously affiliated with the Institute of Mathematics and Informatics (MII) in Vilnius, where he has built an internationally recognized scientific school in visual data analysis. Education & Qualifications 1984 – Candidate of Technical Sciences (PhD equivalent), thesis on “Problem Structure Analysis – a Tool for More Effective Optimization”. 1997 – Habilitation Doctor of Technical Sciences, dissertation on “Isolation of Necessary Knowledge to Improve Optimization Efficiency”. 1992 – Associate Professor, Institute of Mathematics and Informatics, Vilnius. 1998 – Professor, Kaunas University of Technology. Research Interests Prof. Dzemyda’s research integrates data science, artificial intelligence, optimization, and cognitive computing . Core topics include dimensionality reduction, multidimensional data visualization, neural-network–based analytics, parallel and distributed computing, multi-criteria decision support, and advanced AI applications in medicine (ophthalmology, cardiology, oncology). His work has pioneered Lithuanian capabilities in visual analytics and large-scale data exploration. Publication Trends Across 270+ refereed works and 2 Springer monographs (2013, 2023), recent outputs (2021–2025) emphasize geometric multidimensional scaling for big-data visualization, deep learning for pancreatic-cancer detection on CT images, reinforcement learning for autonomous navigation, and fraud-detection techniques for highly imbalanced financial datasets. These contributions appear in Springer LNCS/LNNS, Informatica, Journal of Global Optimization, Engineering Applications of Artificial Intelligence , and other top venues. Awards & Recognition Lithuanian State Science Prize (2001 & 2021) Honorary Doctor of the University of Latvia (2019) Knight's Cross of the Order “For Merit to Lithuania” (2007) Doctoral Supervision & Committees He has mentored 28 doctoral graduates (15 direct, 13 through academic descendants) and currently supervises: Dalia Breskuvienė – Classifier training-set optimization Modestas Motiejauskas – Emotion recognition in photographs Victor Bulava – Machine-learning methods for cyber-incident early detection He also chairs or serves on doctoral and habilitation committees at VU, KTU, VGTU, VMU and MII. Laboratory & Projects As Head of the Cognitive Computing Group , Prof. Dzemyda coordinates several national and EU projects, including the current Lithuanian Research Council grant “Geometric Method for Multidimensional Scaling” (S-MIP-20-19, 2020-2022) and the SMART programme project “CognitiveSTATS” (2021-2023) focused on combating misinformation during pandemics. His team develops open-access tools for large-scale data visualization and contributes to the MIDAS national research-data archive.
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 .
Prof. Dr. Remigijus Paulavičius is a Senior Researcher, Professor, and Group Leader at the Blockchain and Quantum Technologies Group of Vilnius University. He earned his Doctor of Science degree in Computer Science in 2010 from Vilnius University's Institute of Mathematics and Informatics, focusing on global optimization with simplex subdomains under the supervision of Dr. J. Žilinskas. Research Interests : His work bridges global optimization methods with blockchain and quantum computing. Key areas include non-convex bilevel programming, derivative-free optimization algorithms (e.g., DIRECT), and applications in blockchain scalability, consensus protocols, and quantum circuit design. Scientific Awards : Best Paper Award, Journal of Global Optimization (2014) Funding from Lithuanian State Science and Studies Foundation for doctoral students (2007–2009) Member, Young Academy of the Lithuanian Academy of Sciences (since 2019) Projects & Leadership : Leads research on blockchain simulators, quantum machine learning frameworks, and optimization toolboxes (e.g., DGO, DIRECTGO). Involved in international collaborations and conference committees, including AIChE and EUROPT. Publications : Over 70 works on global optimization algorithms, blockchain applications, and quantum computing, with recent focus on generative AI, energy consumption in blockchains, and reproducibility in machine learning.
Dr. Ernestas Filatovas is a Senior Researcher and Chief Researcher in the Project at Vilnius University's Institute of Data Science and Digital Technologies (formerly Institute of Mathematics and Informatics), where he has been affiliated since 2013. He leads the Blockchain and Quantum Technologies Group, focusing on cutting-edge research at the intersection of quantum computing, blockchain, and artificial intelligence. Previously, he served as an Associate Professor and Lecturer at Vilnius Gediminas Technical University's Faculty of Fundamental Sciences from 2013 to 2019. Dr. Filatovas earned his Doctor of Technology in Computer Science Engineering from Vilnius University Institute of Mathematics and Informatics in 2012. His dissertation, supervised by Prof. Dr. Olga Kurasova, focused on the interactive solution of multi-criteria optimization problems. His research spans multiple high-impact domains, with particular expertise in blockchain technologies, quantum computing, artificial intelligence, and machine learning. He has pioneered work in quantum blockchain implementations, reproducibility of AI research through blockchain verification, and quantum machine learning applications. His research bridges theoretical computer science with practical applications in financial markets, healthcare, and distributed systems. His extensive publication record—over 50 scientific papers, with more than 25 in Clarivate Analytics-indexed journals—demonstrates consistent productivity and international collaboration. Recent work shows a clear trajectory toward quantum-enhanced AI systems, blockchain-based research verification frameworks, and quantum algorithms for practical problems. Laureate of the 4th LMA Young Scientists' Conference (2014) INFOBALT scholarship 2nd place winner (2014) Lithuanian State Science and Studies Foundation funding recipient (2009, 2010) Recognized as one of Lithuania's most active doctoral students Master's degree with honors (2006) Dr. Filatovas leads multiple significant research projects, including the 2021-2024 project 'Solving the problems of reproducibility of scientific research in the field of artificial intelligence using blockchain technologies' as team leader, and the 2023-2027 project 'Development and validation of quantum machine learning methods using prepared datasets' as Chief Researcher. He has also contributed to international collaborations such as the Spanish-funded 'High Performance Solutions for Modern Scientific Computing Challenges' (2019-2021). His popular science contributions, including the VU news portal article 'Quantum Computing: Who and Why?', demonstrate his commitment to science communication. As a key member of Vilnius University's Blockchain and Quantum Technologies Group, Dr. Filatovas contributes to Lithuania's growing reputation in quantum computing research and blockchain innovation, working closely with international collaborators across Europe.
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.
Laura Šaltytė-Vaisiauskė is an Associate Professor and currently serves as Vice-Rector for Research and Innovation at Klaipėda University, Lithuania. She is affiliated with the Department of Informatics and Statistics within the Faculty of Marine Technology and Natural Sciences, with additional connections to the Faculty of Social Sciences and Humanities and the Institute of Baltic Region History and Archaeology. Dr. Šaltytė-Vaisiauskė defended her doctoral thesis in Mathematics at Vilnius University in 2013 and has since established herself as a versatile researcher with publications spanning multiple disciplines while maintaining core expertise in statistical methodology. Her research interests center around Statistics, Big data analytics, and Spatial statistics, with significant contributions to Image recognition and Discriminant analysis. Analysis of her publication record reveals a strong focus on developing advanced statistical methods for spatio-temporal data analysis, particularly using Hidden Markov Models with spatial weighting. Her work demonstrates increasing interdisciplinary reach, extending from pure statistical methodology to applications in finance, healthcare, energy systems, and social sciences. Recent publications show her applying statistical techniques to diverse problems including financial volatility modeling, electric vehicle optimization, and even therapeutic interventions for depression. Her scholarly output demonstrates consistent productivity across multiple domains, with publications in reputable journals and conference proceedings. Her work shows particular strength in developing methodological innovations with practical applications, often collaborating across disciplinary boundaries to address complex real-world problems. As Vice-Rector for Research and Innovation, Dr. Šaltytė-Vaisiauskė oversees research strategy and development at Klaipėda University. Her leadership role complements her active research career, allowing her to influence both the direction of her own work and the broader research landscape at her institution. Her recent projects include studies on the impact of COVID-19 restrictions on businesses in the Klaipėda region, demonstrating her commitment to addressing timely societal challenges through rigorous research.
Professor Jolanta Pivorienė serves as Professor and Chief Researcher at Mykolas Romeris University's Institute of Educational Sciences and Social Work within the Faculty of Human and Social Studies. She concurrently holds the strategic position of Vice Dean for International Relations and Projects, driving EU-Asian academic collaborations through initiatives like the HARMONY project. Primary Affiliation: Institute of Educational Sciences and Social Work, MRU Research Leadership: Lifelong Learning Laboratory & Social Innovations Laboratory Network International Roles: Coordinator of 5-country Digi-Ageing consortium (Austria, Spain, Italy, Cyprus, Lithuania) Her research spans critical societal challenges with three interconnected pillars: child protection systems (particularly pandemic impacts on maltreatment), educational resilience (teacher victimization and inclusive schooling), and aging society solutions (digital caregiving and university's third mission). Recent projects demonstrate methodological sophistication through scoping reviews following PRISMA guidelines and mixed-methods approaches combining quantitative surveys with phenomenographic analysis. Key Trends: 83% of recent work (2023-2025) addresses crisis response (pandemic, refugee integration) Field Distribution: 40% aging society research, 35% educational systems, 25% child protection Professor Pivorienė's collaborative approach is evidenced by her 100% project participation rate in international consortia, with strong emphasis on policy translation. Her leadership in the Lifelong Learning Laboratory directly supports practical applications including Ukrainian language integration programs and digital tools for elderly care.
