Find Academic Supervisors

Octavian Mihai MachidonView profile

Assistant Professor

• Mobile Computing
• IoT-based Systems
• Smart Public Governance
• +8 more

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.

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.

Ratko PilipovićView profile

Assistant Professor

• High Performance Computing
• Ubiquitous Computing
• RISC-V Architecture
• +3 more

Ratko Pilipović is an Assistant Professor affiliated with the Laboratory for Adaptive Systems and Parallel Processing (LASPP). He specializes in high-performance computing, ubiquitous computing, and RISC-V vector processors, with extensive involvement in European and Slovenian research projects. Current project: EUROCC2 (National Competence Centres in EuroHPC Phase 2, 2023-2025) Current project: P2-0359 (Ubiquitous Computing, 2023-2027) Past project: P2-0359 (Vseprisotno računalništvo, 2018-2023) Past project: BI-HR/23-24-009 (RISC-V vector processors, 2023-2025) His teaching responsibilities include courses in Digital Design , Computer Systems , and Digital Logic Design . Research focuses on adaptive systems, parallel processing architectures, and scalable computing solutions.

Davor SlugaView profile

Assistant Professor

• High-Performance Computing
• Approximate Computing
• Parallel and Distributed Systems
• +4 more

Assistant Professor Davor Sluga is a member of the Laboratory for Adaptive Systems and Parallel Processing (LASPP). His research focuses on high-performance computing, approximate computing, and parallel/distributed systems, with applications in sensor networks, medical video processing, and RISC-V architecture. His work spans multiple projects including: Synergy of technological systems (ARRS P2-0241, 2020-2026) EUROCC2 National Competence Center (2023-2025) ARISA AI Skills Alliance (2022-2026) Context-aware on-device approximate computing (ARRS J2-3047, 2021-2024) He has previously contributed to projects involving medical video annotation (2014-2015), soft computing for dynamic systems (2010-2011), and hypercomputing in Parkinson’s research (2019).

Uroš LotričView profile

Associate Professor

• Soft Computing
• Distributed Processing
• High Performance Computing

Uroš Lotrič is an Associate Professor at the Faculty of Computer and Information Science, University of Ljubljana, Slovenia. His academic and professional work spans research in soft computing methods, distributed processing, and high-performance computing applications. Education: BSc in Physics (1994), MSc in Computer Science (1997), PhD in Computer Science (2000), all from the University of Ljubljana. Research Interests He focuses on soft computing techniques, distributed systems, and their applications in industrial and computational domains. His work integrates neural networks, wavelet transforms, and predictive modeling to solve complex problems in fields like rubber processing and time series analysis. Scientific Awards Best Assistant 2007 Best Professor 2009 Projects and Laboratory He is involved in national and European research programs such as P2-0241, EUMaster4HPC, and ARISA. Additionally, he is a member of the Adaptive Systems and Parallel Processing laboratory, contributing to advancements in adaptive algorithms and parallel computing.

Marko TopičView profile

Professor

• Photovoltaics
• Solar Energy
• Semiconductor Devices
• +3 more

Dr. Marko Topič is a Full Professor and Dean of the Faculty of Electrical Engineering at the University of Ljubljana, specializing in photovoltaics and optoelectronics. A recipient of the European Becquerel Prize and Slovenia's highest scientific honor (Zois Award), he leads research advancing solar energy technologies and quantum photonic systems. Education: PhD in Electrical Engineering (University of Ljubljana, 1996) Leadership: Chairman of European Technology and Innovation Platform Photovoltaics (2014-2022); Slovenian representative in European Science Advisors Forum Research Impact: 200+ SCI publications, 13,000+ citations, supervision of 16 doctoral dissertations. Current work focuses on high-efficiency solar cells and quantum photonic integration. Major Awards: European Becquerel Prize (2022) Zois Award (2008) Gold Plaquette of University of Ljubljana (2017)

Rok ČešnovarView profile

Lecturer

• Embedded Systems
• Signal Processing
• Computational Statistics
• +3 more

Lecturer Rok Češnovar is affiliated with the Laboratory for Adaptive Systems and Parallel Processing (LASPP). His work focuses on computational methods in adaptive systems and parallel processing. Teaches classes in Computer Systems Organisation, Input-Output Systems, and Embedded Systems Active in research projects related to computationally intensive statistical analysis, sensor networks, and RISC-V vector processors Research Focus Rok Češnovar specializes in embedded systems and signal processing , with emphasis on computationally intensive methods and approximate computing . His work bridges theoretical statistics with practical implementation in adaptive systems. Project History He has contributed to projects including: ARRS-funded research on computationally intensive statistical methods (2016-2019) Decomposing cognition in working memory studies (J3-9264, 2018-2021) High-performance RISC-V vector processor computing (BI-HR/23-24-009, 2023-2025)

Jure DemšarView profile

Assistant Professor

• Neuroinformatics
• Collective behaviour
• Natural phenomena modeling
• +5 more

Jure Demšar, PhD , is an Assistant Professor at the Faculty of Computer and Information Science , University of Ljubljana . He conducts interdisciplinary research bridging neuroinformatics, collective behaviour, and game development, while actively collaborating with leading institutions worldwide. Education & Academic Journey: PhD studies supported by the prestigious “Inovativna shema” scholarship for promising doctoral researchers. Research visits: three months at Newcastle University (Game Lab & Institute of Neuroscience), three months at University of Groningen (Prof. Charlotte K. Hemelrijk’s lab), one month at University of Houston (Computer Graphics and Interactive Media Lab). Research Interests: Dr. Demšar’s work converges on four core themes: Neuroinformatics & Neuroimaging: development of scalable platforms for multimodal neuroimaging data processing (Qu|Nex, autohrf, bayes4psy R packages). Collective Behaviour & Modeling: adaptive agent-based simulations of predator–prey interactions and flocking, evolution of composite tactics. Computational Psychiatry: mapping brain–behavior relationships along the psychosis and mood spectra, placebo vs. drug neural signatures. Game Development & Personalization: generating personalized game content, GPU-accelerated Bayesian modeling, and recommender systems. Scientific Awards & Recognition: Faculty Award for Outstanding Pedagogic Work, 2017/2018 Faculty Award for Outstanding Research Achievements, 2017 Inovativna shema scholarship for promising PhD students Collaborations & Funding: Dr. Demšar has established long-standing collaborations with: Washington University in St. Louis (Connectome Coordination Facility) – Human Connectome Project Yale University (Anticevic Lab) – Qu|Nex platform Harvard University (Applied Neuroimaging Statistics Laboratory) Internal University of Ljubljana partners: Faculty of Arts, Faculty of Medicine, Faculty of Sport Laboratory & Team: He leads the Bayesian Statistics Project Laboratory , where he mentors students and drives open-source tool development for Bayesian data analysis and neuroimaging workflows.

Peter PeerView profile

Professor

• Computer Vision
• Biometrics
• Deep Learning
• +4 more

Peter Peer is a Full Professor at the University of Ljubljana's Faculty of Computer and Information Science, where he leads the Computer Vision Laboratory. He serves as Executive Editor for ICT Express , Area Editor for IEEE Access and IET Biometrics , and coordinates dual-degree programs with Kyungpook National University. His administrative roles include membership in the Faculty Board of Directors (2018-present) and Senate (2021-present), and he previously served as Vice-Dean for Economic Affairs (2018-2022). His research spans computer vision and biometrics , with specialization in privacy-enhancing technologies, deep learning applications, and multimodal recognition systems. Key focus areas include: Face/sclera/ear biometric recognition and segmentation Deepfake detection and media forensics Generative models for data privacy Efficient model optimization techniques Publication analysis shows strong emphasis on biometric security (65% of recent works), privacy-preserving AI (25%), and generative modeling (10%), with applications spanning surveillance, forensics, and human-computer interaction. Awards highlight leadership in international biometric competitions and recognition for high-impact publications. Significant scientific honors include: NIST FATE evaluation winner (2025) Top 3 placements in ACM/IEEE biometric competitions (2023-2024) IEEE Transactions top-downloaded articles (2022-2024) European Association for Biometrics awards (2021-2024) He mentors 10+ PhD students working on biometric recognition, privacy preservation, and deep learning applications. Research is supported by national grants including DeepFake DAD (2023-2026) and MIXBAI (2023-2026), focusing on explainable AI and deepfake detection. Leads the Computer Vision Laboratory with international collaborations across Europe and Asia.

Borut RobičView profile

Professor

• Computability Theory
• Algorithms
• Parallel Computing
• +5 more

Borut Robič is a Full Professor and Head of the Theoretical Computer Science Chair at the Faculty of Computer and Information Science, University of Ljubljana . He also serves as Head of the Laboratory for Algorithmics and President of the Faculty's Academic Assembly since 2005. His work spans computability theory, algorithms, and parallel computing, with notable contributions to foundational concepts and educational literature. University: University of Ljubljana School: Faculty of Computer and Information Science Roles: Professor, Head of Theoretical Computer Science Chair, Head of Laboratory for Algorithmics, President of Academic Assembly Robič's research interests focus on computability and complexity theory, algorithm design, and parallel computing frameworks. His publications emphasize historical context, formal methods, and modern computational paradigms like hypercomputing. Publication trends reveal a progression from foundational algorithmic theory (1999) to advanced computability research (2020), with a 2018 work bridging parallel programming and practical implementation. Projects include leadership in ARRS research programmes on parallel systems (2020-2026) and past collaborations on graph optimization and big data initiatives. Laboratory affiliations: Head of the Laboratory for Algorithmics and active member of its research team.

Erik ŠtrumbeljView profile

Researcher

• Probability
• Statistics
• Machine Learning
• +5 more

Erik Štrumbelj is a researcher specializing in probability, statistics, and machine learning. His work focuses on stochastic processes, Monte Carlo methods, Bayesian statistics, and applications in sports analytics (player evaluation, match simulation, statistical forecasting). He has contributed to advancing computationally intensive statistical analysis and has collaborated on interdisciplinary projects involving data mining, high-performance computing, and explainable AI. Key research trends include: Developing game theory-based explanations for machine learning predictions Modeling sports outcomes using Markov processes Analyzing forecasting reliability through betting odds Integrating data mining with medical modeling He has been involved in numerous research projects funded by ARRS and international bilateral agreements, addressing topics like imbalanced data analysis, AI explainability, and hypercomputing applications.

Klen Čopič PuciharView profile

Associate Professor

• Augmented Reality
• Mixed Reality
• Virtual Reality
• +7 more

Dr. Klen Čopič Pucihar serves as Associate Professor at the Faculty of Mathematics, Natural Sciences and Information Technologies (FAMNIT) at the University of Primorska in Koper, Slovenia. He holds multiple leadership roles including Department Chair of Information Sciences and Technologies, Deputy Chair of HICUP Lab, and Study Programme Coordinator for the Doctoral Computer Science program. His research centers on Human-Computer Interaction with particular emphasis on: Augmented, Mixed, and Virtual Reality systems Micro-gesture recognition using radar sensing (e.g., Google Soli) Paper interfaces and augmentation of physical media AR for educational applications, particularly vocabulary learning Addressing the 'dual-view problem' in handheld AR systems Dr. Čopič Pucihar's work is driven by the vision to 'unclog the bottleneck' between humans and digital information. His recent publications (2019-2025) show a strong trajectory from theoretical interaction techniques toward practical educational applications and novel input methods using radar sensing, with consistent output in top venues including CHI, ISS, MobileHCI, and ISMAR. His notable achievements include: Best Paper Award at ACM IUI 2025 Honorable Mentions at ACM EICS 2022 and ACM ISS 2022 Best Poster Award at ISMAR Multiple hackathon victories including at Columbia University As Study Programme Coordinator for Doctoral Computer Science, Dr. Čopič Pucihar mentors graduate students and shapes research directions. His HICUP Lab hosts an international research group focused on making digital interfaces more intuitive and effective for human use through advanced sensing methods and personalized services. HICUP Lab leverages techniques from data mining, machine learning, computer vision, and human perception to develop interfaces that function as extensions of human minds, bodies, and behavior, with the ultimate goal of enabling 'digital augmentation of human abilities to its fullest potential.'