Find Academic Supervisors

Matjaž KukarView profile

Associate Professor

• Machine Learning
• Data Mining
• Artificial Intelligence
• +3 more

Matjaž Kukar serves as an Associate Professor at the Faculty of Computer and Information Science, actively contributing to the Laboratory for Machine Learning and Language Technologies and the Cognitive Modelling Laboratory. His academic instruction encompasses Data Management Technologies, Databases, and Big Data courses, shaping foundational data science education. His research program centers on advancing machine learning methodologies for healthcare applications, particularly in risk stratification for heart failure (STRATIFYHF project), cancer classification, and ischemia detection. He specializes in solving challenges with imbalanced datasets, model reliability estimation, and interdisciplinary integration of data mining with high-performance computing across medical and engineering domains. Dr. Kukar leads the ongoing STRATIFYHF project (2023-2027) while maintaining an extensive history of funded research including coronary artery disease modeling, electricity load forecasting, and assistive technologies for low-vision individuals. His collaborative framework spans bilateral international projects and structural fund initiatives, demonstrating consistent success in securing competitive research funding through ARRS and EU mechanisms.

Lovro ŠubeljView profile

Associate Professor

• Network Science
• Machine Learning with Graphs
• Data Analysis
• +12 more

Lovro Šubelj is an Associate Professor at the University of Ljubljana, Faculty of Computer and Information Science , specializing in Network Science and Machine Learning with Graphs . His work bridges theoretical and applied network analysis, with contributions to community detection, graph convexity, and network simplification. Research focuses on graph algorithms for network abstraction Teaching: MSc/PhD courses on Network Science, BSc programming courses Collaborates with institutions like Leiden University and Imperial College London Research Interests: His primary work explores structural and dynamic properties of complex networks, including community detection via label propagation, convex skeletons for network simplification, and intermediacy metrics for citation analysis. Secondary interests span data mining, stream mining, and statistical network modeling. Publication Trends: Recent work emphasizes scalable network algorithms (2023-2025), graph embeddings (2021), and geometric network properties like convexity (2018-2019). Earlier projects (2012-2017) addressed citation network analysis, social network fraud detection, and database consistency evaluation. Teaching & Outreach: Provides educational materials on YouTube, including courses on network science and programming. Maintains open-access data/code repositories through KONECT, ICON, and GitHub.

Polona VilarView profile

Professor

• Information Behavior
• Information Literacy
• Reading Literacy
• +3 more

Polona Vilar is a Professor at the Department of Library, Information Science and Book Studies, Faculty of Arts, University of Ljubljana, where she has worked since 1999. Her academic progression includes assistant professor (2008), associate professor (2014), and full professor (2019) positions. She teaches information behavior, information and reading literacy, and school/general library studies. Active in national and international research projects Visiting professor/researcher at City University London, University of Graz, and others Member of CoLIS and ISIC conference committees IFLA Section for Information Literacy committee until 2023 Senate member and Habilitation Commission member at Faculty of Law Her research focuses on information behavior, literacy, and library systems. Recent work examines research data management, academic reading formats, and archival literacy. She has over 140 publications including books and reports. Scientific awards include: Kalan Award (2003, 2019) from Slovenian Library Association Emerald/EFMD Publishing House Award (2008) for doctoral work ŠS FF Award (2013) for pedagogical excellence Vilar has mentored nearly 100 students and led projects like Kulturni in sistemski dejavniki bralne pismenosti (2015-2016). She actively promotes librarian continuing education and has brought international conferences (CoLIS 2019) to Slovenia.

Vojko StrahovnikView profile

Professor

• Moral Intuitionism
• Moral Particularism
• Contemporary Metaethics
• +7 more

Full Professor Vojko Strahovnik serves at the Department of Philosophy, Faculty of Arts, University of Ljubljana, while also holding a research fellowship at the University of Ljubljana's Faculty of Theology. He currently chairs the Center for Human-Centered Artificial Intelligence and Ethics of New Technologies and maintains active teaching responsibilities including Metaphysics, Ontology, and Contemporary Metaphysics courses. His international collaborations include visiting positions at the University of Arizona as a Fulbright Scholar (2016) and Templeton Fellow (2022-2023). Strahovnik's research centers on the structure and phenomenology of normativity, spanning ethics, epistemology, philosophy of science, and aesthetics, with increasing focus on AI ethics. His work explores moral intuitionism, particularism, epistemic identity, and the intersection of religious beliefs with ethical reasoning. Recent projects investigate epistemic virtues in human-AI interaction, ethical dimensions of digital culture, and anthropological challenges of digitalization. His publications reveal a trajectory from foundational work on moral particularism to contemporary explorations of AI ethics and global justice frameworks. His scientific recognition includes the 2020 Excellence in Science Award from ARIS (ARRS), Fulbright Research Scholarship (2016), and Templeton Fellowship (2022). These honors acknowledge his theoretical contributions to understanding normative domains and practical applications in ethics education. Strahovnik leads multiple research initiatives including the current 'Epistemic Identity and Epistemic Virtue: Human Mind and Artificial Intelligence' project funded by the Templeton Foundation and Oxford's Ian Ramsey Centre. His international collaborations span EU-funded projects like ETHIKA (Ethics and Values Education in Schools) and LITTLE (Learn Together to Live Together), demonstrating commitment to translating philosophical insights into educational practice. His research group focuses on the philosophical implications of AI while developing practical ethics education frameworks for schools. The Center for Human-Centered Artificial Intelligence and Ethics of New Technologies, which he heads, serves as an interdisciplinary hub connecting philosophy, theology, and computer science to address ethical challenges in emerging technologies. His team conducts focus groups and experiential workshops to investigate identity formation in AI-infused environments, bridging theoretical philosophy with practical applications.

Martin MilaničView profile

Professor

• Graph Theory
• Treewidth and Clique Number
• Domination in Graphs
• +2 more

Martin Milanič is Professor at the University of Primorska’s Faculty of Mathematics, Natural Sciences and Information Technologies. His research focuses on structural and algorithmic graph theory, including treewidth, domination, and clique studies. He chairs the WG 2024 conference and leads projects on graph modification and induced minors. Recent work establishes NP-completeness of treewidth on cubic graphs and characterizes minimally tough graphs. He supervises doctoral students in graph decomposition and independence problems.

Luka Čehovin ZajcView profile

Assistant Professor

• Human-Computer Interaction
• Motion Perception
• Computer Graphics
• +3 more

Luka Čehovin Zajc is an Assistant Professor and researcher at the University of Ljubljana's Faculty of Computer and Information Science. He specializes in human-computer interaction, motion perception, and computer graphics, with a focus on visual cognitive systems. Current research projects: COMET, RoDEO, and P2-0214 (Computer Vision) Past projects include AI-driven solutions for Earth observation, autonomous boats, and privacy-aware AAL applications Active in developing data-driven machine vision frameworks and generative appearance modeling

Aleš SmrdelView profile

Assistant Professor

• Human-Computer Interaction
• Usability Testing
• User Interface Design
• +3 more

Aleš Smrdel is an Assistant Professor at the Faculty of Computer and Information Science, University of Ljubljana. He is affiliated with the Laboratory for Biomedical Computer Systems and Imaging. Research Interests: Designing and implementing user interfaces Usability testing and human-computer interaction Biomedical signal analysis, particularly ECG and ischemia detection Selected Publications: Focus on algorithm development for cardiovascular diagnostics, including ST segment analysis and open-source tools for ECG evaluation. Laboratory: Active member of the Laboratory for Biomedical Computer Systems and Imaging.

Zoran BosnićView profile

Professor

• Machine Learning
• Data Mining
• Recommender Systems
• +7 more

Zoran Bosnić is a Full Professor at the Artificial Intelligence Department, Faculty of Computer and Information Science, University of Ljubljana. He specializes in integrating advanced statistical methods with practical applications including data stream mining, recommender systems, user behavior profiling, e-learning systems, and computer communications. B.Sc. (2001), M.Sc. (2003), and Ph.D. (2007) from Faculty of Computer and Information Science, University of Ljubljana, Slovenia His research focuses on computationally intensive methods for statistical analysis, inductive learning from partially labeled datasets, and AI applications in medical domains. He has contributed to projects involving quantum advantage in reservoir computing and cross-lingual embeddings for European news media. 2012 Certificate of Honor for young university teachers 2019 Gold Medal of the University of Ljubljana He is a member of the Laboratory for Machine Learning and Language Technologies and actively participates in both national (ARRS) and international projects (European, bilateral collaborations).

Franc JagerView profile

Professor

• biomedical signal processing
• biomedical image processing
• digital signal processing
• +4 more

Franc Jager is a Full Professor at the University of Ljubljana, Faculty of Medicine, where he leads the Laboratory for Biomedical Computer Systems and Imaging. His research focuses on biomedical signal and image processing, digital signal processing, biomedical computer systems, and human-computer interaction, with particular emphasis on electrohysterography (EHG) for pregnancy monitoring and preterm birth prediction. Professor Jager's research interests include: Biomedical signal processing and analysis Electrohysterogram (EHG) analysis for pregnancy monitoring Preterm birth prediction using uterine electrical activity Development of biomedical datasets and databases Biomedical computer systems and imaging His recent work has centered on developing and analyzing EHG datasets, including the Term-Preterm EHG DataBase (TPEHG DB), Term-Preterm ElectroHysteroGram DataSet with Tocogram (TPEHGT DS), and the Induced Cesarean EHG DataSet (ICEHG DS). These datasets have been instrumental in advancing research on predicting preterm birth and understanding uterine electrical activity during pregnancy. His publications reveal a strong focus on signal processing techniques applied to obstetric care, with particular attention to developing robust methods for analyzing uterine electrical activity across different pregnancy outcomes. Professor Jager is a Full Member of Sigma Xi, The Scientific Research Honor Society, recognizing his significant contributions to scientific research. He teaches courses in Biomedical Signal and Image Processing and Digital Signal Processing, mentoring the next generation of biomedical engineers and researchers. His laboratory pursues multiple research goals including understanding physiological phenomena, developing computer models of physiological relationships, monitoring physiological events, and creating standardized databases to evaluate recognition techniques in biomedical applications.

Igor KononenkoView profile

Professor

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +3 more

Prof. Igor Kononenko serves as a Professor at the Faculty of Computer and Information Science, University of Ljubljana, where he heads the Laboratory for Cognitive Modeling and teaches core courses including Algorithms and Data Structures 1, Artificial Intelligence, Intelligent Systems, and Machine Learning. Education: Ph.D. in Computer Science, University of Ljubljana (1990) Research Focus: His work centers on Artificial Intelligence , Machine Learning , and Cognitive Modeling , with recent emphasis on explainable AI and prediction reliability . He has pioneered techniques in feature contribution explanation, graph-based data mining, and archetypal analysis for complex datasets, resulting in approximately 210 publications and 10 textbooks . Publication Trends: Analysis of his 15 most recent articles reveals a decisive shift toward interpretable machine learning—particularly reliability estimation in data streams (2012-2014), graph mining for oceanographic/spatial data (2013-2019), and medical applications of explanation methods (2011-2018). His 2013-2016 work on archetypal analysis for multi-document summarization remains highly influential in NLP. Research Leadership: As principal investigator, he secured major funding including: Two ARRS programmes on Artificial Intelligence (2009-2014, 2015-2020) EU's AGROIT project for farming efficiency (2014-2016) Bilateral projects on imbalanced data learning (2010-2011), bioinformatics for cancer classification (2014-2015), and disease dataset analysis (2020-2021) Laboratory: The Laboratory for Cognitive Modeling under his direction drives innovation in AI theory and applications, with recent work spanning basketball analytics, coronary artery disease diagnostics, and hemodynamic simulation modeling.

Miha MrazView profile

Professor

• Computational Biology
• Systems Biology
• Ubiquitous Computing
• +5 more

Miha Mraz serves as a Full Professor at the Faculty of Computer and Information Science, University of Ljubljana, where he teaches Computer Networks, Computer Systems Reliability, Unconventional Information Processing, and Computational Biology courses from office R3.59. His research spans Computational Biology (gene regulatory networks, circadian biology), Ubiquitous Computing , and Unconventional Computing (Quantum-dot Cellular Automata, fuzzy logic systems). He employs stochastic simulations, genetic algorithms, and multi-valued logic to model biological processes and optimize logistical systems. Analysis of his 2005-2015 publications reveals consistent interdisciplinary work at the computer science-biology interface, particularly in computational modeling of biological networks and novel computing architectures. Key themes include information processing in gene networks and quantum-dot cellular automata design for multi-valued logic systems. Professor Mraz leads current ARRS projects including hypoxia-cholesterol synthesis research (J1-50024, 2023-2026) and Ubiquitous Computing (P2-0359, 2023-2027), alongside past European initiatives like RFID F2F. As a core member of the Computer Structures and Systems Laboratory, he focuses on computer architecture reliability and unconventional computing platforms despite no listed advisees in available materials.

Tatjana Welzer DružovecView profile

Professor

• Database Design
• Software Reuse and Re-engineering
• CASE Tools
• +3 more

Tatjana Welzer Družovec is a Full Professor at the Database Technology Laboratory of the University of Maribor, Slovenia. Her research focuses on conceptual database design, software reuse and re-engineering, CASE tools, and computer science education.

Sergio CabelloView profile

Professor

• Discrete Algorithms
• Computational Geometry
• Combinatorial Optimization
• +3 more

Sergio Cabello is a full professor at the Faculty of Mathematics and Physics of the University of Ljubljana, Slovenia, and a researcher at the Institute of Mathematics, Physics and Mechanics. His research focuses on discrete algorithms and computational geometry, with contributions to graph theory, geometric optimization, and algorithm design. He has held editorial roles in journals such as the Journal of Combinatorial Mathematics and Combinatorial Computing, and has participated in numerous conferences as a PC member or invited speaker. His work spans topics like shortest paths in geometric graphs, convex hulls, and algorithmic complexity. Notable recent activities include organizing the Indo-Spanish School of Algorithms and Combinatorics (2025) and serving on the editorial boards of Discrete Mathematics & Theoretical Computer Science and the Journal of Computational Geometry. He has also received best paper awards at SODA 2017 and AGILE 2009 for his contributions to theoretical computer science. Editorial Roles: Journal of Combinatorial Mathematics, Discrete Mathematics & Theoretical Computer Science, Indian Journal of Discrete Mathematics Professional Activities: PC member for EuroCG 2025, WADS steering committee member, invited speaker at GROW 2022 and Discrete Mathematics Days 2024 His research interests include geometric algorithms, graph connectivity, and combinatorial optimization, with a focus on theoretical foundations and algorithmic applications in discrete structures.

Lea AličView profile

Assistant Professor

• Cognitive Psychology
• Attention Training
• Neuropsychological Rehabilitation
• +3 more

Lea Alič serves as an Assistant Professor and young researcher at the Department of Psychology within the Faculty of Arts, University of Ljubljana. Her institutional affiliation encompasses active participation in the university's Cognitive Neuroscience Laboratory and interdisciplinary research centers. Her educational trajectory includes a 2014 undergraduate degree and 2017 master's completion in Psychology at the same institution, followed by ongoing doctoral studies in Experimental Psychology. Key research domains span cognitive attention training methodologies, neuropsychological rehabilitation frameworks, and adolescent cognitive development metrics. Analysis of her 2017-2019 publications reveals consistent focus on visual attention training efficacy in adolescent populations, utilizing growth curve modeling and digital assessment tools like CCRacer 2.0. Her work bridges experimental psychology with clinical applications in educational settings. No scientific awards or fellowships documented in source materials While no formal advising roles or grant details appear in the provided texts, her collaborative publications with researchers like Podlesek and Poredoš indicate active participation in departmental research teams. Current institutional context includes involvement with the Faculty of Arts' Cognitive Neuroscience Laboratory initiatives.

Saso DzeroskiView profile

Professor

• Machine Learning
• Data Mining
• Computational Scientific Discovery
• +7 more

Sašo Džeroski is a Professor at the Department of Knowledge Technologies, Jožef Stefan International Postgraduate School, and a Scientific Councillor at the Jožef Stefan Institute in Slovenia. He leads a research group of ~17 members, focusing on constraint-based data mining, structured output prediction, and automated modeling of dynamic systems, with applications in systems biology, ecology, and environmental sciences. His research interests span data mining, machine learning, computational scientific discovery, and their applications in life sciences and medicine. He has coordinated major projects like MAESTRA (FP7) and LANDMARK (H2020), and contributed to EU initiatives in systems biology ( E.E.T. Pipeline , PHAGOSYS ). He developed methodologies for predictive clustering trees and hierarchical multi-label classification, with software tools ProBMoT and CLUS . The 15 most recent articles highlight his work on ensemble learning for multi-output systems, structured output prediction in medical imaging, ecological modeling using machine learning, and ontologies for data mining. These publications reflect interdisciplinary trends combining computational methods with applications in fungal biology, endocytosis, and agricultural drainage. Scientific Awards: Foreign Member, Macedonian Academy of Sciences and Arts Advising includes mentoring PhD students (e.g., Nikola Simidjievski, Jovan Tanevski) and MSc students. Grants and projects emphasize EU funding (H2020, FP7) and national initiatives in knowledge technologies. He has served on editorial boards of journals like Machine Learning and Ecological Informatics , and organized key conferences (e.g., ECML PKDD-2015 ).