جستجوی استاد راهنمای دانشگاهی

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.

Davor Slugaمشاهده پروفایل

استادیار

• High-Performance Computing
• Approximate Computing
• Parallel and Distributed Systems
• +۴ مورد دیگر

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).

Branko Šterمشاهده پروفایل

استاد

• Computer Systems
• Parallel Processing
• Adaptive Systems
• +۳ مورد دیگر

Branko Šter serves as Professor at the Faculty of Computer and Information Science, University of Ljubljana, teaching Computer Systems Architecture , Computer Systems , and System Software while leading the Laboratory for Adaptive Systems and Parallel Processing. His research focuses on Computer Systems , Parallel Processing , and Adaptive Systems , with emphasis on technological synergy and soft computing methodologies. Current work centers on the ARRS research programme P2-0241 Synergy of the technological systems and processes (2020-2026), extending his continuous involvement since 2009 through overlapping project phases. Professor Šter directs laboratory research in adaptive computing systems with practical applications in embedded technologies, evidenced by projects like PKP 5 Accelerator for virtual machine for embedded systems (2019). His international collaboration includes the EuNetAir COST Action on air-pollution control systems (2012-2016), demonstrating cross-disciplinary technological integration.

Uroš Lotričمشاهده پروفایل

دانشیار

• 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.

Peter Peerمشاهده پروفایل

استاد

• Computer Vision
• Biometrics
• Deep Learning
• +۴ مورد دیگر

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.