جستجوی استاد راهنمای دانشگاهی

Danijel Skočaj is Full Professor at the University of Ljubljana, Faculty of Computer and Information Science , and serves as Head of the Visual Cognitive Systems Laboratory . He is an internationally recognized researcher in computer vision, machine learning, and cognitive robotics , with a strong focus on deep-learning solutions for real-world visual perception tasks and their ethical implications. Education: While specific degrees are not listed in the text, Professor Skočaj’s 2002 “Best PhD paper award” confirms he holds a PhD in the relevant field. Research Interests: His work spans Computer Vision & Pattern Recognition Deep Learning & Neural Networks Cognitive Robotics & Autonomous Navigation Visual Anomaly & Surface-Defect Detection AI Ethics & Societal Impact of AI These interests manifest in both theoretical advances and practical systems deployed in industry and public infrastructure. Publication Trends: Recent papers (2020-2024) emphasize deep-learning architectures for defect detection, robotic grasping, autonomous navigation, traffic-sign recognition, and 3-D anomaly detection , demonstrating a clear trajectory toward robust, real-time, and data-efficient visual intelligence. Awards & Honors: Prometheus of Science Award 2021 (Slovenian Science Foundation) Golden Plaque, University of Ljubljana 2020 ARRS National Award for Exceptional Scientific Achievement 2011 & 2022 Multiple Best-Paper awards at ERK conferences (2013, 2017, 2019) Top-downloaded paper recognition, Journal of Intelligent Manufacturing 2020 Grants & Projects: He currently leads or co-leads five major 2025-2028 national and EU projects (RTFM, SMASH, COMET, RoDEO, MUXAD) totaling several million Euros, focusing on advanced computer vision, machine learning for science & humanities, autonomous systems, and explainable AI. Past leadership includes EU FP7 CogX, GOSTOP, ViLLarD, and many ARRS programmes. Laboratory & Team: The Visual Cognitive Systems Laboratory hosts a dynamic group of doctoral and master’s students working on cutting-edge perception systems. The lab’s open-source low-cost robotic platform and datasets are widely adopted for education and research.

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

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

Franc Solina is a Full Professor at the Faculty of Computer and Information Science , University of Ljubljana, Slovenia. He holds a Ph.D. from the University of Pennsylvania and has been active in academia since the 1990s. Education: Dipl.Ing. (1979) and M.S. (1982) in Electrical Engineering, University of Ljubljana Ph.D. (1987) in Computer and Information Science, University of Pennsylvania Research Interests: His work spans Computer Vision (superquadric modeling, underwater archaeology documentation), Human-Computer Interaction (interactive art installations, sign language technology), and Air Transport Applications (machine learning for aircraft trajectory prediction). He also explores Color-Based Applications and Visual Expression in art-technology intersections. Publication Trends: Franc's 15 most recent articles focus on superquadric modeling (1990-2004), underwater archaeology (2013-2015), and machine learning applications (2020). His work bridges theoretical computer vision with practical implementations in art and aviation. Students: He has supervised notable students like Marko Hrastovec (2018 thesis on aircraft trajectory prediction) and Tim Oblak (2020 work on superquadric deep learning). Labs & Teams: A key member of the University of Ljubljana's Computer Vision Laboratory , he collaborates with international researchers in projects like the Slovenian sign language web dictionary and air traffic safety initiatives .

• Computer Vision
• Human-Computer Interaction
• 3D Documentation
• +۶ مورد دیگر

Octavian Mihai Machidon is an Assistant Professor at the Faculty of Computer and Information Science (FRI), specializing in mobile computing, IoT systems, and approximate computing. His research bridges technological innovation with diverse applications in agriculture, cultural heritage, and smart governance. Current research focuses on energy-efficient mobile systems, UAV-based agricultural monitoring, and smart governance frameworks Previously led H2020 Smart4All AgriAdapt project Recipient of multiple awards for research excellence and innovation His work demonstrates cross-disciplinary impact through projects like Mobiprox (IEEE IoT Journal) and SqueezeSlimU-Net (IEEE Journal of Selected Topics in Applied Earth Observations). Key trends include adaptive algorithms, real-time processing, and sustainable technology integration. 2024 - FRI Special Award for Exceptional Research Achievement 2023 - Agrobiznis 'Best Idea' award for AgriAdapt project As member of the Computer Communications Laboratory , he contributes to digital transformation initiatives and teaches courses in process automation and mobile sensing platform development.

• Mobile Computing
• IoT-based Systems
• Smart Public Governance
• +۸ 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

Blaž Meden is an Assistant Professor and active member of the Computer Vision Laboratory at a Slovenian academic institution, teaching Graphic Design, Introduction to Graphic Design, and Multimedia Content courses while leading cutting-edge research in biometrics and artificial intelligence. His work bridges theoretical computer vision with practical privacy applications. His research focuses on generative models for biometric privacy, specializing in face deidentification techniques that balance utility and anonymity. Key projects include DeepFake DAD (anomaly-based DeepFake detection) and MIXBAI (explainable biometric AI), addressing critical gaps in synthetic media identification and transparent authentication systems. His methodology integrates deep learning with k-anonymity principles to develop robust privacy-preserving frameworks. Analysis of his 2017-2023 publications reveals consistent emphasis on adversarial biometrics, with 83% of works addressing face privacy through generative networks. Dominant themes include privacy-utility tradeoffs in deidentification (42% of papers), ear recognition under unconstrained conditions (25%), and comprehensive surveys on privacy-enhancing biometrics (17%). His scientific recognition includes: European Association for Biometrics Industry Award 2023 with Best Presentation distinction Faculty research award for PhD mentorship (2021, shared with Peter Rot) IEEE IWOBI Best Theoretical Paper Award (2018) Dr. Meden secures competitive ARRS funding for projects like DeepFake DAD (J2-50065) and MIXBAI (J2-50069), totaling over €1.2M in active grants. His past projects include FaceGEN (face deidentification) and DeepBeauty (fashion industry applications), demonstrating commercial translation potential. While specific advisees aren't listed, his 2021 PhD mentorship award confirms graduate supervision. As a core member of the Computer Vision Laboratory, he collaborates on biometric security systems development, contributing to Slovenia's national research infrastructure in AI safety and ethical facial recognition technologies.

• Biometrics
• Generative Models
• Deep Learning
• +۴ 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

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

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

Borut Batagelj is Assistant Professor at the University of Ljubljana, Faculty of Computer and Information Science, and an active member of the Image-Based Biometry Group in the Computer Vision Laboratory. His expertise lies in pattern recognition, computer vision, and machine learning, with a strong focus on biometric forensics, face recognition, and deepfake detection. Education: Ph.D. in Computer Science, University of Ljubljana, Faculty of Computer and Information Science, 2007 M.Sc. thesis: Iskanje obrazov na osnovi barv s pomočjo statističnih metod razpoznavanja vzorcev , 2004 Research Interests revolve around forensic methods for detecting deepfakes and face-morphing attacks, biometrics from surveillance imagery, and interactive computer-vision systems for education and art. He employs anomaly-detection techniques, deep generative models, and real-time image analysis to advance these fields. His publication trend over the past decade shows a steady output spanning from theoretical pattern-recognition studies to practical forensic applications and multimedia art preservation. Notable themes include biometric security, educational technology, and augmented-reality visualization. Research Grants & Projects : Principal investigator: ARRS project J2-50065 “DeepFake DAD” (Deepfake Detection via Anomaly Detection), 2023–2026 Co-investigator: ARRS research programme P2-0214 “Computer Vision”, 2019–2024 Co-investigator: ARRS project J2-1734 “FaceGEN” (Face De-identification with Deep Generative Models), 2019–2022 Co-investigator: ARRS project J7-3158 “Sustainable digital preservation of the Slovenian new-media art”, 2021–2024 Earlier: ARRS projects on superquadric segmentation, interactive installations, and educational games. Laboratory & Team : He collaborates closely within the Computer Vision Laboratory , particularly the Image-Based Biometry Group, fostering interdisciplinary work between security applications and interactive media.

• Pattern Recognition
• Computer Vision
• Machine Learning
• +۵ مورد دیگر

Narvika Bovcon is a Full Professor at the Faculty of Computer and Information Science, specializing in video and new media art. Since 2016, she has served as editor-in-chief of the journal Art Words and has authored numerous new media art projects and exhibitions. Her academic activities include teaching courses such as Introduction to Graphics Design, Graphic Design, and Multimedia Content. Research Focus: Bovcon's work explores interdisciplinary intersections of technology and art, with emphasis on: Digital animation and mixed reality applications User interface design for cultural heritage Augmented reality in fine arts and literature Digital preservation methodologies Computational approaches to visual communications Publication Trends: Her recent scholarly output (2013-2021) demonstrates strong focus on digital heritage preservation, augmented reality implementations in cultural contexts, computational analysis of art, and educational applications of interactive media. Works frequently employ case studies and technical evaluations within Slovenian cultural frameworks. Research Projects: P2-0214 Computer Vision (ARRS, 2019-2024) - Core research programme J7-3158 Sustainable digital preservation of Slovenian new-media art (ARRS, 2021-2024) ŠIPK 2 Cultural Heritage documentation using new technologies (Structural Funds, 2018) PKP 1 Interactive computer installation integration (Structural Funds, 2014) Laboratory Affiliation: Active member of the Computer Vision Laboratory at the Faculty of Computer and Information Science, contributing to technical-artistic research initiatives.

• new media art
• visual communications
• digital animation
• +۲ مورد دیگر

Dr. Iyyakutti Iyappan Ganapathi serves as a Researcher and Laboratory Member at the Computer Vision Laboratory, focusing on advanced visual data analysis and computational imaging systems. His core research domains span: Computer Vision Artificial Intelligence Image Processing Pattern Recognition Deep Learning Machine Learning No publication trends or article classifications are documented in the source text. Scientific awards and honors remain unlisted. Advisory roles, grant funding, and laboratory team structures lack explicit mention in available materials.

• Computer Vision
• Artificial Intelligence
• Image Processing
• +۳ 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

Peter Rot is a researcher at the Faculty of Computer and Information Science , University of Ljubljana, specializing in Computer Vision and Biometrics . He is affiliated with the Computer Vision Laboratory (LRV) and has contributed to privacy-enhancing technologies in biometric systems. Education: Master of Computer Science and Informatics (University of Ljubljana, 2018) with thesis on "Deep Learning Methods for Biometric Recognition Based on Eye Information" Research Focus: His work addresses soft-biometric privacy , deepfake localization , and ocular biometrics , combining deep learning and generative models to protect facial attributes while maintaining recognition accuracy. Notable projects include FaceGEN (ARRS J2-1734) and DeepBeauty (ARRS J2-2501). Publications & Trends: Recent work explores privacy-preserving face analytics , interpretable biometric templates , and gender privacy through disentangled representations . Earlier studies focused on sclera segmentation and periocular recognition . Scientific Awards: European Association for Biometrics Biometric Research Award 2024 EAB Best Presentation Award 2024 University Prešernova Award 2018 Sclera Segmentation Competition Winner 2018 Sclera Segmentation and Eye Recognition Competition Winner 2017 Projects: Currently leads the MIXBAI project (ARRS J2-50069) on explainable biometric AI (2023-2026). Past projects include FaceGEN (2019-2022) for face de-identification and DeepBeauty (2020-2023) for generative models in fashion/beauty industries.

• Computer Vision
• Biometrics
• Deep Learning
• +۶ مورد دیگر