جست‌وجوی استاد و پژوهشگر

Danijel Skočajمشاهده پروفایل

استاد

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

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.

Octavian Mihai Machidonمشاهده پروفایل

استادیار

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

• Machine Learning
• Artificial Intelligence
• Model Visualization
• +۳ مورد دیگر

Martin Mozina serves as an Assistant Professor and Researcher at the Faculty of Computer and Information Science, University of Ljubljana, where he has been affiliated with the Artificial Intelligence Laboratory since 2004. His primary institutional role focuses on advancing machine learning methodologies integrated with domain knowledge. His research centers on developing machine learning algorithms that incorporate prior knowledge alongside training data, with significant contributions to model visualization through nomograms and automated chess position analysis. Key innovations include argument-based machine learning frameworks and techniques for resolving knowledge acquisition bottlenecks in intelligent systems. Analysis of his 2004-2009 publications reveals consistent emphasis on interpretable AI, combining symbolic reasoning with statistical learning. His work bridges theoretical machine learning with practical applications in medical diagnostics, game AI, and decision support systems, particularly through nomogram-based classifier visualization and chess tutoring systems. He actively participates in major research initiatives including: DRIFT (L2-4436): Real-time optimization of low-voltage networks using deep incentivized learning (2022-2025) Umetna inteligenca in inteligentni sistemi: Agency-funded AI research program (2015-2020) Strojno učenje v gradnji inteligentnih sistemov: Machine learning for intelligent tutoring systems (2011-2014, 2013-2014) Molecular markers for lung cancer research (2011-2014, 2016-2018) X-MEDIA: Large-scale knowledge sharing across media (EU project, 2006-2009) Mozina's work within the Artificial Intelligence Laboratory demonstrates sustained focus on making machine learning more transparent and applicable to complex real-world problems through hybrid symbolic-statistical approaches.

Ivan Bratkoمشاهده پروفایل

استاد

• Machine Learning
• Knowledge-Based Systems
• Qualitative Modelling
• +۵ 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.

Žiga Emeršičمشاهده پروفایل

استادیار

• Biometrics
• Deep Neural Networks
• Computer Vision
• +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 .

Blaž Medenمشاهده پروفایل

استادیار

• Biometrics
• Generative Models
• Deep Learning
• +۴ 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.

Vojko Strahovnikمشاهده پروفایل

استاد

• Moral Intuitionism
• Moral Particularism
• Contemporary Metaethics
• +۷ مورد دیگر

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.

Luka Čehovin Zajcمشاهده پروفایل

استادیار

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

Peter Rotمشاهده پروفایل

پژوهشگر

• Computer Vision
• Biometrics
• Deep Learning
• +۶ 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.

Matej Pičulinمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Computer Science
• +۳ مورد دیگر

Assist. dr. Matej Pičulin is an Assistant Professor affiliated with a laboratory (likely at the Faculty of Computer and Information Science, University of Ljubljana, inferred from context). He teaches courses in Introduction to Artificial Intelligence , Analysis of Algorithms and Heuristic Problem Solving , and Databases . His office hours are held every Wednesday from 10:00 AM to 11:00 AM in Room R2.26, Laboratorij LKM. Research Interests : Matej's work focuses on artificial intelligence applications in healthcare and knowledge management. Key projects include STRATIFYHF (2023–2027): Developing an AI-based decision support system for heart failure risk stratification in clinical settings. J5-60084 (2025–2027): Investigating explainable and generative AI integration challenges in organizational knowledge management. Supervised/Unsupervised Learning for Low Vision Assistance (2014–2015): Applying ML techniques to improve mobility for visually impaired individuals. Intelligent Computer Techniques for Medical Detection (2016–2017): Focused on diagnosing cognition/behavior disorders via computational methods.

Damjan Popičمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing
• Computational Linguistics
• +۲ مورد دیگر

Damjan Popič serves as an Assistant Professor and Laboratory Member at the Laboratory for Machine Learning and Language Technologies, focusing on cutting-edge research in artificial intelligence and language systems. Research Expertise: His work centers on Machine Learning and Natural Language Processing , with specialized contributions to computational linguistics, language modeling, and AI-driven language technology development. Key methodologies involve deep learning frameworks for semantic analysis and multilingual processing. Laboratory Role: As an integral member of the Laboratory for Machine Learning and Language Technologies, he advances the lab's mission through collaborative projects in neural language generation, speech recognition systems, and ethical AI applications, driving innovation in computational language understanding.

• Artificial Intelligence
• Knowledge Management
• Information Systems

Prof. dr. Aleš Popovič is a Researcher affiliated with an unspecified academic institution. His current work focuses on integrating Explainable AI and Generative AI within the context of organizational knowledge management, as demonstrated by his involvement in the research project J5-60084 . Research interests include: Artificial Intelligence applications in organizations Knowledge Management systems Information Systems development

• Artificial Intelligence
• Explainable AI
• Generative AI
• +۲ مورد دیگر

Dr. Mojca Svetek is an Assistant Professor and researcher affiliated with the Laboratory of Management. Her work focuses on integrating Explainable AI and Generative AI to address Knowledge Management challenges in organizations. Active in EU-funded project ARRS (J5-60084), 2025-2027 Research explores organizational applications of AI Member of interdisciplinary research teams

• Artificial Intelligence
• Explainable AI
• Generative AI
• +۲ مورد دیگر

Irena von Arx Ograjenšek is a Researcher at a Slovenian academic institution, actively contributing to AI and knowledge management research as a Laboratory Member. She leads the ARRS-funded project J5-60084 titled "Managing AI: Integrating Explainable and Generative AI – Challenges and Opportunities for Knowledge Management in Organizations" (2025–2027), reflecting her central role in contemporary organizational AI research. Her research focuses on the practical integration of cutting-edge AI technologies within business frameworks, specifically examining how explainable AI (XAI) and generative AI systems can overcome knowledge management barriers in organizational settings. This work addresses critical gaps in AI adoption, emphasizing transparency, usability, and strategic implementation for enterprise knowledge workflows. As a Laboratory Member, she collaborates within institutional research teams to advance AI applications in management science. Her current ARRS project represents a significant national research grant driving innovation at the intersection of artificial intelligence and organizational theory.

Jure Demsarمشاهده پروفایل

استادیار

• Neuroinformatics
• Group Behavior
• Modeling Natural Phenomena
• +۵ مورد دیگر

Jure Demsar is an Assistant Professor and researcher at the Faculty of Computer Science and Informatics, University of Ljubljana . He collaborates internationally with institutions including Washington University (Human Connectome Project), Yale University (Anticevic Lab), Harvard University (Applied Neuroimaging Statistics Lab), and multiple Slovenian faculties. Research visits: Yale University (2 months), Newcastle University (3 months), Groningen University (3 months), University of Houston (1 month) His research bridges neuroinformatics and computational modeling , focusing on: Brain dynamics and behavior EEG and fMRI data analysis Group behavior simulations Computer game development Recent publications highlight interdisciplinary applications of data science in neuroscience and psychology, with tools like bayes4psy for Bayesian analysis. Awards include recognition for pedagogical excellence and research achievements (2017/2018).