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• Machine Learning
• Artificial Intelligence
• Cybersecurity
• +7 more

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 .

• Machine Learning
• Medical Imaging
• Computer Science
• +3 more

Šubonienė Aušra is a junior researcher and PhD student at the Cognitive Computing Group of Vilnius University's Institute of Data Science and Digital Technologies. She works on applying machine learning techniques to medical imaging, particularly for pancreatic cancer detection using CT scans. Field: Computer Science Supervisor: Prof. Dr. Olga Kurasova Study Period: 2023–2027 Research Focus : Her work centers on semi-supervised learning and pseudo-labelling methods for improving diagnostic accuracy in medical imaging. She has contributed to developing deep learning models that identify cut-off points for pancreatic cancer detection, with applications in CT scan analysis. Publication Trends : Recent articles demonstrate expertise in medical image segmentation , neural network optimization , and clinical decision support systems , primarily focused on oncology and radiology.

• Medical Image Analysis
• Machine Learning
• Computer Vision
• +5 more

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.

• Deep Learning
• Convolutional Neural Networks
• Medical Imaging
• +4 more

Sandra Virbukaite is a Lecturer at Vilnius University's Department of Lecturers. She is currently pursuing doctoral studies (2020–2024) at Vilnius University Institute of Data Science and Digital Technologies, focusing on deep learning methods for identifying pathological changes in fundus images under Dr. Jolita Bernatavičienė. Master’s degree in Applied Statistics (Vilnius Gediminas Technical University, 2011) Bachelor’s degree in Engineering Informatics (Vilnius Gediminas Technical University, 2009) Recent certificates from Oxford University's Machine Learning Summer Schools (2023–2024) and DeepLearn 2021 Summer Her research centers on medical imaging and artificial intelligence applications for eye disease detection, particularly glaucoma through optic disc and cup segmentation . Analysis of her 15 most recent publications (2020–2024) shows focus areas in convolutional neural networks , image preprocessing , and segmentation accuracy in fundus imaging. Presenter at 8 major conferences including DAMSS (2021–2022), WSCG (2022), and AI Technologies in Medicine (2023–2024) Contributor to 5 peer-reviewed publications in IEEE Access and Nonlinear Analysis: Modelling and Control She teaches Database Query Languages at Vilnius University since 2020, demonstrating both pedagogical and research expertise in applied statistics and deep learning domains.