جستجوی استاد راهنمای دانشگاهی

Blaž Zupan is a Full Professor at the University of Ljubljana, also affiliated with Baylor College of Medicine in Houston, teaching artificial intelligence and machine learning. He leads a fifteen-member bioinformatics laboratory and has authored over one hundred publications with more than ten thousand citations, reflecting significant impact in computational sciences. His research centers on explainable AI, machine learning, and data visualization, with deep applications in bioinformatics. He pioneered the Orange data mining suite—a visual programming tool for accessible analytics—and bioinformatics platforms like dictyExpress for gene expression analysis and GenePath for genetic network discovery, emphasizing user-friendly interfaces and real-world usability. Analysis of his recent publications reveals a trajectory from foundational AI (e.g., concept hierarchies in 1999) to contemporary bioinformatics, with current work focusing on single-cell genomics, batch-effect correction, and democratizing AI through visual programming. His tools bridge computational methods and biological discovery, particularly in systems biology and genomics. Zupan’s accolades include the Zois Award (2010), two University of Ljubljana Golden Plaques (2011, 2019), a Fulbright Scholarship (2013), and six student-voted Best Teacher Awards (2008–2017). He was named among the Top 100 Most Influential Innovators of Central and Eastern Europe (2016) by Res Publica, Financial Times, and Google. He secures substantial research funding, currently leading projects like KATARINA (computer science education for all), DALI4US (data literacy for primary schools), DANIO-ReCODE (genomics of regeneration), and L2-60154 (explainable AI for gene expression). Past projects span AI systems (2009–2020), drug discovery, and systems biology, demonstrating sustained interdisciplinary impact. As head of the Bioinformatics Laboratory, he fosters collaboration between computer science and biology, developing open-source tools that empower researchers globally. His consulting for industry and public organizations extends his influence into data-driven decision support and AI training.

• Artificial Intelligence
• Machine Learning
• Explainable AI
• +۴ مورد دیگر

Dr. Ajda Pretnar Žagar is a researcher at the University of Ljubljana's Faculty of Computer and Information Science and the Institute for Contemporary History. With a PhD in Anthropology from the University of Ljubljana (2021), she bridges computational methods with social sciences through interdisciplinary research. University of Ljubljana Institute for Contemporary History Her research focuses on: Quantitative Anthropology Computational Social Sciences Machine Learning Applications Algorithmic Futures Bioinformatics Recent projects include: REIMAGINE ADM (2022-2025): Reimagining public values in algorithmic futures DALI4US (2024-2026): Data Literacy for upper primary schools xAIM (2021-2024): Explainable AI in healthcare

• Computational Anthropology
• Machine Learning Applications in Social Sciences
• Data Mining
• +۳ مورد دیگر

Ivan Bratko is a Professor of Computer Science at the University of Ljubljana's Faculty of Computer and Information Science. He founded the Artificial Intelligence Laboratory in 1985 and served as its head until 2017, remaining an active member. Until 2002, he also directed the AI group at the Jožef Stefan Institute. His academic journey includes B.Sc., M.Sc., and Ph.D. degrees in electrical engineering and computer science, all from the University of Ljubljana. Bratko's research spans machine learning, knowledge-based systems, qualitative modeling, intelligent robotics, heuristic programming, and computer chess. His work focuses on learning from noisy data, combining learning with qualitative reasoning, constructive induction, Inductive Logic Programming, and applications in medicine and dynamic system control. He has authored over 200 scientific papers and influential books including Prolog Programming for Artificial Intelligence (third edition, 2001), KARDIO: A Study in Deep and Qualitative Knowledge for Expert Systems (MIT Press, 1989), and Machine Learning and Data Mining: Methods and Applications (Wiley, 1998). His publication portfolio demonstrates consistent contributions to AI, with recent work emphasizing argument-based machine learning, qualitative modeling applications, and medical AI systems. These publications reveal strong interdisciplinary connections between theoretical AI and practical applications in environmental science, healthcare, and robotics. Fellow of the European Coordinating Committee for Artificial Intelligence (ECCAI) Member of the Slovene Academy of Arts and Sciences (SAZU) Former editorial board member of Artificial Intelligence , Machine Learning , Journal of AI Research , and other leading journals Co-founder and first chairman of the Slovenian AI Society (SLAIS) Bratko has secured numerous research projects including ARRS programs on artificial intelligence (2009-2020), the PARKINSCHECK project for Parkinson's disease detection, and European projects like X-MEDIA and XPERO. His laboratory serves as the central hub for AI research at the University of Ljubljana, fostering collaborations across medical, environmental, and industrial domains. He has mentored numerous researchers and maintained active collaborations through visiting positions at institutions including Edinburgh University, University of New South Wales, and Delft University of Technology.

• Machine Learning
• Knowledge-Based Systems
• Qualitative Modelling
• +۵ مورد دیگر

Žiga Emeršič is an Assistant Professor at the University of Ljubljana, Faculty of Computer and Information Science , affiliated with the Computer Vision Laboratory . His work bridges biometrics , deep learning , and computer vision , with a focus on ear-based recognition systems and explainable AI. IEEE Member #98052610 Email: ziga.emersic@fri.uni-lj.si Office: R2.33, LRV Laboratory Office Hours: Tuesdays 12:30 or by arrangement Research interests include biometric recognition , deep neural networks , object detection , and privacy-preserving AI . He pioneered ear biometrics research, developing tools like the Ear Biometric Database in the Wild and ContexedNet for context-aware recognition. Recent publications analyze biometric model performance ( Neural Computing & Applications, 2018 ), explore k-Same-Net for face deidentification ( Entropy, 2018 ), and advance ear alignment using two-stack hourglass networks ( IET Biometrics, 2023 ). His 2021 work on context-aware ear detection addresses real-world variability. Awards include the European Association for Biometrics Award (2021) , SDRV Excellence Plaque (2023) , and multiple University of Ljubljana recognitions for teaching and research (2016, 2018, 2022). He co-organized the 1st Machine Learning Summer School in Central America (2018) . As co-founder of OOSM Ltd (2014-2015), he applied deep learning to smart city solutions. His 2017 doctoral thesis on visual ear detection in unconstrained environments solidified his expertise in biometric AI .

• Biometrics
• Deep Neural Networks
• Computer Vision
• +۵ مورد دیگر

Martin Žnidaršič serves as a Senior Research Associate at the Department of Knowledge Technologies, Jožef Stefan Institute, and holds an Assistant Professor position at the Jožef Stefan International Postgraduate School. His academic career, active since 2003, focuses on integrating machine learning with decision modeling for practical environmental applications. He teaches courses in machine learning, computational creativity, and artificial intelligence methodologies. His research centers on decision support systems under uncertainty, specializing in data-based revision of hierarchical rule-based models through DEX methodology. This work manifests in tools like proDEX and web applications deployed in environmental domains, particularly for cropping systems analysis and GMO risk assessment. His methodological innovations address knowledge revision in probabilistic qualitative models and multi-attribute decision frameworks. Publication trends from 2004-2010 reveal consistent application of decision modeling to agricultural and environmental challenges. Key themes include soil quality assessment, economic-ecological impact modeling of cropping systems, and risk frameworks for genetically modified organisms. His work bridges theoretical advances in uncertainty handling with real-world implementation through software tools. Dr. Žnidaršič has led significant research initiatives including EU H2020 projects RESILOC (2019-2022) and EMBEDDIA (2019-2021) as task leader, CF-Web (2017-2018) as project coordinator, and earlier collaborations like HEALTHREATS (2007-2010) as work package leader. His project portfolio spans environmental risk assessment, food security, and AI infrastructure development. Based at the Department of Knowledge Technologies in Ljubljana, he operates within interdisciplinary teams focused on data mining and decision support. His work involves extensive European collaboration through projects like e-LICO and ConCreTe, targeting scalable solutions for environmental science and agricultural policy challenges.

• Decision Support Systems
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

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.

• Machine Learning
• Data Mining
• Artificial Intelligence
• +۳ مورد دیگر

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.

• Network Science
• Machine Learning with Graphs
• Data Analysis
• +۱۲ مورد دیگر

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).

• Machine Learning
• Data Mining
• Recommender Systems
• +۷ مورد دیگر

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.

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +۳ مورد دیگر

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 ).

• Machine Learning
• Data Mining
• Computational Scientific Discovery
• +۷ مورد دیگر

Nejc Ilc serves as an Assistant Professor at the University of Ljubljana's Faculty of Computer and Information Science, where he has been employed since 2009 and teaches process automation and digital design courses. He earned his PhD in Computer and Information Science from the same institution in 2016 following undergraduate studies completed in 2009. His academic credentials include: PhD in Computer and Information Science, University of Ljubljana (2016) BSc in Computer and Information Science, University of Ljubljana (2009) Dr. Ilc's research spans machine learning with emphasis on cluster analysis algorithms, bioinformatics applications in inflammation modeling, computer simulation techniques, and parallel processing implementations. His machine learning work develops novel ensemble methods and validity indices, while bioinformatics research explores lipid mediator pathways in extracellular vesicles. Parallel computing applications appear in real-time computer vision systems for traffic sign recognition. Analysis of his 2012-2020 publications reveals persistent focus on clustering methodologies across data mining and biomedical contexts, with increasing interdisciplinary collaboration in bioinformatics after 2015. His work consistently bridges theoretical algorithm development with practical implementations in simulation environments. His recognition includes: Faculty award for assistants with best student evaluations (2020/2021) Current research leadership includes the ARRS program P2-0241 "Synergy of technological systems and processes" (2020-2026) and EUROCC2 competence center project (2023-2025). Past projects involved bilateral collaborations on complex dynamic systems modeling (2010-2011) and approximate computing (2019-2021). He organized the ICANNGA 2011 international conference and maintains office hours Tuesdays 13:00-14:00 in Room R2.31. While specific laboratory affiliations aren't detailed, his project involvement suggests computational research activities within the Faculty of Computer and Information Science.

• Machine Learning
• Cluster Analysis
• Bioinformatics
• +۲ مورد دیگر

Miha Janež serves as an Assistant Professor at the Faculty of Computer and Information Science, University of Ljubljana, where he contributes to both academic instruction and research innovation within Slovenia's premier computer science institution. His educational foundation includes a 2012 PhD in Computer Science from the University of Ljubljana, focusing on circuit layout design for quantum computing applications. Research interests span quantum computing architectures, wireless sensor network design with accessible hardware, and large-scale network data analytics, extended into pervasive computing systems, medical image compression techniques, and sustainable urban development through integrated data frameworks. This interdisciplinary approach connects hardware-level innovations with real-world societal challenges. Publication trends reveal an evolution from foundational quantum hardware research (2012) toward contemporary applications in mobile network analytics (2020) and urban sustainability modeling (2021), demonstrating consistent relevance across computing subfields while maintaining core expertise in unconventional information processing. As an active member of the Computer Structures and Systems Laboratory, he bridges theoretical research with practical implementation. His teaching portfolio includes critical infrastructure courses: Computer Systems Architecture, Computer Networks, Wireless Sensor Networks, and Unconventional Information Processing Methods. Project leadership encompasses significant ARRS-funded initiatives: the Pervasive Computing research programme (2013-2017), Medical Images Compression bilateral project (2010-2011), agency data utilization study (2017-2018), and the neighborhood sustainability assessment system J5-1798 (2019-2022), reflecting sustained research productivity across diverse funding mechanisms.

• Quantum computing
• Wireless sensor networks
• Data analysis in large networks
• +۶ مورد دیگر

Alenka Kavčič is an Assistant Professor at the Faculty of Computer and Information Science, University of Ljubljana, and a core member of the Laboratory for Computer Graphics and Multimedia. Her work integrates multimedia technologies, human-computer interaction, and computer graphics with applications in education, cultural heritage, and biodiversity monitoring. Her research spans Educational Technology , Multimedia Systems , and Human-Computer Interaction , with emphasis on self-regulated learning in digital environments, music information retrieval for ethnomusicology, and accessibility solutions for the visually impaired. She investigates agile development methodologies in educational software and vibrational communication in ecological contexts. Recent publications (2022-2004) reveal consistent focus on adaptive educational technologies, including self-regulation scaffolding, hypertext-based science learning, and fuzzy logic for user modeling. Her work bridges theoretical frameworks with practical applications in e-learning standards and engineering education. Dr. Kavčič has secured diverse research funding: National ARRS projects: MULTI-MON (biodiversity monitoring, 2023-2026), Vibroscape (vibrational communication, 2021-2024), J5-9437 (self-regulated e-learning), and J7-9426 (computational folklore) European projects: MiCREATE (migrant children, 2019-2021), CREA (entrepreneurship, 2015-2017), ASPECT (educational standards, 2008-2011) Structural Funds projects: ZaznajSpoznaj (accessibility for visually impaired, 2014-2015), NA-MA POTI (science literacy, 2016-2022), eEksperimenti (natural sciences teaching, 2015) As part of the Laboratory for Computer Graphics and Multimedia, she contributes to R&D in audio processing, VR/AR applications, medical imaging, and open data visualization, developing cross-platform software solutions for desktop, mobile, and cloud environments.

• Educational Technology
• Multimedia Systems
• Human-Computer Interaction
• +۴ مورد دیگر

Rok Rupnik is a Senior Lecturer in Information Systems at the Faculty of Computer and Information Science, University of Ljubljana. He holds a Ph.D. in Mobile Applications (2002) and a Master's in Information Systems Engineering (1998), both from the University of Ljubljana. Research Interests: Electronic Business, Information Systems Development Methodologies, Mobile Applications, Data Mining, CRM Professional Memberships: Member of AIS, Senior Member of PMI Slovenian Chapter, Member of ACM, Member of IEEE Projects: ARRS research programme P2-0359 (Ubiquitous Computing, 2023-2027), Pervasive Computing (2013-2017), AGROIT (2014-2016)

• Electronic Business
• Information Systems Development Methodologies
• Mobile Applications
• +۲ مورد دیگر

Marko Toplak is a Researcher at the Faculty of Computer and Information Science, University of Ljubljana, serving as teaching assistant for Programming 1, Business Intelligence, and Introduction to Bioinformatics courses. His research specializes in machine learning with emphasis on background knowledge integration for predictive modeling. He collaborates with Baylor College of Medicine analyzing Dictyostelium discoideum gene expression data and develops the Orange data mining toolkit with its Bioinformatics add-on using Python. Currently leading ARRS projects J3-4513 (Role and applicability of circular RNA in liver cancer, 2022-2025) and L2-60154 (Explainable Foundation Models for Human Gene Expression, 2025-2027), he maintains active membership in the Bioinformatics Laboratory. His work bridges computational methods with biological applications across genomics and systems biology domains.

• Machine Learning
• Bioinformatics
• Data Mining
• +۳ مورد دیگر