Andrea Vedaldi is Professor of Computer Vision and Machine Learning at the University of Oxford, where he co-leads the internationally renowned Visual Geometry Group. Concurrently, he serves as Research Scientist and Technical Lead at Meta, focusing on 3D computer vision and generative AI research. His research spans fundamental and applied aspects of computer vision and machine learning, with specializations in 3D reconstruction and generative models. He has made influential contributions recognized through major awards and leadership roles, including chairing the European Conference on Computer Vision. Awards & Honors: Royal Society Faraday Discovery Fellowship IEEE Thomas Huang Memorial Prize IEEE Mark Everingham Prize Two Best Paper Awards (CVPR) ACM Test of Time Award FREng (Fellow of Royal Academy of Engineering) ELLIS Fellow
Goran Oreški is an Associate Professor and Head of the Laboratory at the Faculty of Informatics in Pula (University Jurja Dobrile, Croatia), where he has been employed since 2019. He teaches courses on databases, object-oriented programming, data warehousing, and artificial intelligence at both undergraduate and graduate levels. Education: Ph.D. in Informatics (2016), Faculty of Organization and Informatics Industry Experience: 9 years as software architect and programmer in banking sector Research Focus: Artificial Intelligence systems, classical machine learning algorithms, and deep learning architectures. His work bridges theoretical advancements with practical applications in autonomous vehicles, traffic monitoring, and financial risk assessment. Recent Publication Trends: 2023-2025 works emphasize generative AI for synthetic credit data, traffic object segmentation with monocular cameras, and context-aware detection models (YOLO*C). Earlier works focus on genetic algorithms and ensemble learning for imbalanced datasets. Awards: Google RFP Award for autonomous vehicle research Highly Cited Paper (Web of Science, top 1%) Best Paper at CECIIS conference Leadership: Director of FIPU Laboratory since 2022, leading projects like ai.Shuttle (autonomous mini-bus) and CenAI (industry collaboration with Cenosco).
Prof. Dr. Igor S. Pandžić is a Full Professor at the Department of Telecommunications , Faculty of Electrical Engineering and Computing (FER) , University of Zagreb . He is also affiliated with the Center of Excellence for Computer Vision , actively contributing to research in computer graphics, virtual humans, and interactive systems. Education: While specific degrees are not listed in the provided text, his title "prof. dr. sc." (Croatian for Full Professor with a Doctor of Science degree) indicates he has completed doctoral studies and achieved the highest academic rank. Research Interests: Virtual Humans & Avatars: Creation, animation, and behavioral modeling of lifelike virtual characters for interactive applications. Facial Animation & Biometrics: Real-time speech-driven facial animation, facial expression recognition, age/gender estimation, and biometric data filtering. 3D Graphics & Virtual Environments: Real-time rendering, networked collaborative virtual environments (e.g., VLNET), and 3D visualization on mobile/web platforms. Human-Computer Interaction: Multimodal interfaces combining speech, gesture, and facial cues for embodied conversational agents (ECAs). Computer Vision: Face alignment, landmark detection, pattern recognition with decision trees, and efficient algorithms for mobile deployment. Research Trends from Publications: His recent work (2022-2023) emphasizes efficiency in computer vision (e.g., fast face alignment, memory-efficient models), unsupervised learning for biometric data quality improvement, and real-time applications on mobile devices. Earlier foundational work spans MPEG-4 facial animation standards, networked virtual environments, and virtual human frameworks. Scientific Awards: No specific awards are mentioned in the provided text. Advising & Grants: While individual students are not named, his extensive publication record and leadership in research centers imply active supervision of PhD and Master's students. Grant details are not specified. Labs & Teams: He leads or heavily contributes to the Center of Excellence for Computer Vision at FER, fostering interdisciplinary collaboration in visual computing and AI.
Lucija Blašković serves as Assistant Professor at the Department of Information Science and Mathematics within the Faculty of Agriculture, University of Zagreb. She has maintained continuous affiliation with the university since 2003, progressing from Assistant to Postdoctoral Researcher (2015) and currently holding her assistant professorship since 2017. Her office is located in the 5th Pavilion, 3rd floor, room 65, with consultations held Wednesdays 11am-1pm. Her academic credentials include: PhD in Information and Communication Sciences from Faculty of Humanities and Social Sciences, University of Zagreb Master of Economics (mag. oecc) in Information Management from Faculty of Economics, University of Zagreb Master of Economics in Marketing from Faculty of Economics, University of Zagreb Dr. Blašković specializes in digital transformation of agricultural systems , with core expertise in E-business implementation , E-learning pedagogy , and information systems quality assurance . Her research bridges computational methodologies with agricultural education, examining data literacy frameworks, influencer marketing efficacy for agricultural products, and machine learning applications in farming systems. Analysis of her 15 most recent publications (2024-2015) reveals three dominant research trajectories: (1) Pandemic-driven digital adaptation in agricultural education and consumer behavior, (2) Computational methods (K-means, CNNs) for educational and agricultural data analysis, and (3) Strategic implementation of e-learning systems in agricultural higher education. Her work consistently applies technical solutions to domain-specific agricultural challenges. She has secured research leadership through competitive grants: "Mjesto i uloga informatike u razvitku poljodjelskih sustava: primjer Hrvatske" (2017-2019, MZOS-funded) as Project Coordinator "Mogućnosti i oblici primjene optimiziranja proizvodnje na obiteljskim poljoprivrednim gospodarstvima" (2017, University of Zagreb-funded) as Project Coordinator Her teaching portfolio spans communications systems, agricultural information systems, AutoCAD drafting, and e-commerce, reflecting her interdisciplinary approach to agricultural informatics education.
Domagoj Ševerdija is an Assistant Professor at the School of Applied Mathematics and Informatics at Josip Juraj Strossmayer University of Osijek, where he leads the Computer Science and Machine Learning Research Group. He holds a PhD in Electrical Engineering (2013) and a dual BS in Mathematics and Computer Science (2007) from the University of Osijek. His research spans computational linguistics, natural language processing, machine learning, and combinatorial optimization, with applications in bioinformatics, robotics, and energy systems. Recent work focuses on neural language models, domain adaptation techniques, and efficient algorithm design. Publications show strong interdisciplinary trends: computational linguistics (Croatian morphology, sentence embeddings), bioinformatics (cell typing, RNA splicing), and algorithm optimization (terrain guarding, matrix operations). Recent papers emphasize knowledge distillation, domain adaptation, and compressed representations. Awards: Best paper award in AIS - Artificial Intelligence Systems track (MIPRO 2023) Research funding includes: Computer-Assisted Corpus Linguistics (UNIOS, 2019-2020) Croatian Identity Network Framework (Adris Foundation, 2020-2021) Croatian Language in Global Cloud (Adris Foundation, 2019-2020) Leads the Computer Science and Machine Learning Research Group, coordinating projects in NLP, computational geometry, and AI applications.
Karlo Veličan is a Researcher affiliated with the Faculty of Physics at the University of Rijeka. He holds an M.Sc. in Physics (Solid state physics) from the Department of Physics, University of Rijeka (2018). His research focuses on material science, nanotechnology, and photocatalysis, with particular attention to thin films, atomic layer deposition (ALD), and the optimization of photocatalytic efficiency in materials like ZnO and TiO₂. His work explores substrate effects, doping strategies (e.g., copper doping), and surface functionalization to enhance material performance for applications in energy and environmental technologies. Key research trends in his publications include advancing photocatalytic properties through controlled synthesis methods, investigating temperature and light-dependent behaviors in semiconductor materials, and developing optomechanical sensors. These studies bridge fundamental material science with practical applications, emphasizing interdisciplinary approaches between physics, chemistry, and engineering. His technical expertise is supported by his role as a Technical Associate Expert at the Faculty of Physics, where he likely contributes to experimental setups, instrumentation, and collaborative research projects. While no awards or student advisements are explicitly cited, his active publication record suggests involvement in cutting-edge laboratory activities and potential contributions to academic teams within the Faculty's Divisions and Laboratories.
Franko Šikić is a Researcher at the Department of Electronic Systems and Information Processing within the Faculty of Electrical Engineering and Computing (FER) at the University of Zagreb. His work bridges computer vision and practical retail applications, focusing on real-world problem solving through deep learning methodologies. His research concentrates on computer vision systems for retail environments and human-computer interaction, particularly in out-of-stock detection, price tag recognition, and gaze estimation. Key interests include applying convolutional neural networks to shelf monitoring challenges and developing attention-based architectures for unconstrained gaze prediction. Recent publications demonstrate a clear progression toward sophisticated retail analytics solutions, with increasing emphasis on multi-task learning for shelf image analysis. His 2025 gaze estimation work introduces novel cross-attention mechanisms, while retail publications consistently address practical constraints like variable lighting and occlusion in supermarket settings.
Zoran Kalafatić, an Associate Professor at the Faculty of Electrical Engineering and Computing, is actively involved in the Image Processing Group. His research spans multiple domains within image analysis and computational methods. Primary affiliations: Image Processing Group Academic rank: Associate Professor Research Focus: Dr. Kalafatić's work centers on advanced image processing techniques, including: Color constancy and visual perception Crater detection in astronomical imagery Application of Hough Transform methods Medical imaging databases (OCT image database) Pattern recognition in astronomical cross-matching Development of DRiDB image dataset Contact: Located in office D-343, reachable via +385 1 6129 998 or zoran.kalafatic@fer.hr .
Kristina Mastanjević serves as an Associate Professor of Biotechnology at the University of Osijek's Faculty of Food Technology, Croatia. Her academic profile centers on food safety research within Biotechnical sciences, with student consultations held Mondays 9-11 AM in office 57/18 at Franje Kuhača 18, Osijek. She maintains active research engagement through publications in high-impact journals while teaching core food science disciplines. Her research program critically examines hazardous compounds in traditional Croatian food systems, specializing in polycyclic aromatic hydrocarbons (PAHs) in smoked meats (Slavonska slanina, Buđola) and malt, alongside mycotoxin contamination in brewing by-products. She pioneers analytical methodologies including GC-MS coupling with sensory analysis and computer vision systems for beer quality assessment. Additional focus areas encompass malting technology for alternative grains, brewing waste valorization, and temperature-dependent sensory properties of craft beer under Mediterranean conditions. Analysis of her 2020-2023 publications reveals consistent investigation of regional food safety challenges, particularly PAH formation mechanisms during traditional smoking processes and mycotoxin transfer through malting/brewing. Her work bridges analytical chemistry with practical food engineering solutions, addressing regulatory compliance gaps for contaminants in artisanal production while developing objective quality assessment tools through digital imaging. No scientific awards or honors were documented in the provided materials. The available information does not specify graduate student advisement activities, research grant acquisitions, laboratory facilities, or collaborative research teams associated with Dr. Mastanjević's work.
Dr. Ante Bilić Prcić serves as Associate Professor and Dean at the Faculty of Education and Rehabilitation Sciences , University of Zagreb. He teaches courses in the Department of Visual Impairments , including Family and Rehabilitation , Electronic Aids in Rehabilitation , and Psychosocial Implications of Visual Impairment . His research focuses on rehabilitation methodologies, assistive technology applications, and social skills development in individuals with visual impairments. Core Research Areas : Visual Impairment Rehabilitation, Assistive Technology, Psychosocial Interventions Teaching Expertise : Braille literacy, ICT accessibility, independent mobility training Recent publications analyze Braille literacy program effectiveness , social skill disparities in visually impaired adolescents, and ICT applications for safe navigation. His work addresses pandemic-specific challenges in disability support and art therapy accessibility. Key Collaborations : Laboratory for Psycholinguistic Research, Centre for Lifelong Learning Students : Supervises clinical exercises and graduation theses in visual impairment rehabilitation
Jadranko Matuško is a Full Professor at the Department of Electric Machines, Drives and Automation, Faculty of Electrical Engineering and Computing (FER), University of Zagreb. His research focuses on control systems, mechatronics, and predictive control, with applications in electric drives, robotics, and vehicle dynamics. Research Areas: Control systems, mechatronics, predictive control, electric drives, automation, robotics, nonlinear control, state estimation, embedded systems, and neural networks in control applications. Scientific Contributions: His work spans projects like field-oriented control of brushless DC motors, global vision systems for UAVs, inverted pendulum laboratory designs, and model predictive control algorithms for grid-tied power converters. Notable applications include self-stabilizing urban vehicles via gyroscopic effects and tire/road friction estimation for automotive control systems. Teaching & Projects: He has developed laboratory setups (e.g., ball and plate systems), human-machine interfaces, and control invariant frameworks. His publications emphasize dynamic reconfiguration, sensorless control, and Kalman filter-based state estimation. Awards & Honors: No specific scientific awards mentioned in the provided texts. Collaborations & Tools: Utilizes MATLAB, FPGA, Arduino/PcDuino, and Tensor Product Transformation for control design. Engaged in projects related to microgrid control, smart water metering, and cyber-physical production systems.
Mateja Marić is an Assistant Professor in the field of psychology at the Faculty of Law, University of Osijek, Croatia, since November 2024. She is affiliated with the Department of Labor Law and Social Sciences and Social Work, contributing to both undergraduate and graduate programs in social work. Her academic journey includes doctoral and master’s training in psychology, with extensive interdisciplinary engagement across philosophy, law, and cognitive science. PhD in Psychology, University of Rijeka (2022) MA in Psychology, University of Osijek (2014) Pedagogical-Psychological and Didactic-Methodological Training First level of behavioral-cognitive therapy (HUBIKOT) Her research focuses on the intersection of psychology, cognitive neuroscience, and social work. Key interests include neurodynamic modeling of visual perception, top-down cognitive influences, and qualitative methodologies in social work. She employs computational tools like MATLAB, JASP, Jamovi, and SPSS in her research. The recent publications of Mateja Marić reveal a strong trend in computational and cognitive neuroscience, particularly in modeling perceptual processes using neurodynamic frameworks. Her work bridges theoretical psychology with neural implementation, emphasizing feedback mechanisms, perceptual organization, and the interplay between vision and memory. These studies frequently appear in high-impact journals such as Neural Networks and Consciousness and Cognition , indicating a rigorous, interdisciplinary approach. Mateja Marić is actively involved in the academic community: Member of the Association for Psychological Science (APS) Member of the Society for the Teaching of Psychology (STP) Member of the Croatian Psychological Chamber She has participated in three major research projects funded by the Croatian Science Foundation and the University of Rijeka, led by Prof. Dražen Domijan, and is currently an external associate on a neurocognitive modeling project (uniri-iskusni-drustv-23-124). She has delivered 18 presentations at national and international conferences and has contributed to science outreach through lectures for educators and psychologists. She teaches core courses such as Research Methodology in Social Work, Communication in Social Work, and Interview as an Assessment Method. Mateja Marić has been an external associate at the Department of Cultural Studies, Department of Psychology (Faculty of Philosophy), and the Social Work Study Program at the Faculty of Law, University of Osijek, from 2015 to 2024, before her current appointment as Assistant Professor.
Tomislav Sedlar is an associate professor at the Faculty of Forestry and Wood Technology, University of Zagreb, located at pavilion IV, room 142. He holds a PhD and has served in academic roles since 2009, progressing from assistant to his current rank. His work focuses on wood technology, material science, and non-destructive testing of wood properties. He teaches courses in special wood products and communicates in Croatian and English, with consultations available Tuesdays 10-11 AM. Professional Experience: 2024–current: Associate Professor 2019–2024: Assistant Professor 2015–2019: Postdoctorate 2009–current: Faculty of Forestry and Wood Technology, University of Zagreb Research interests include wood mechanical properties, composite reinforcement, defect detection via deep learning, and the application of novel testing methods. His work bridges traditional wood science with modern materials engineering, emphasizing sustainability and structural preservation of historical timber structures. Publications span over 15 years, with recent trends in assessing wood durability through steam treatment, fiber implant efficacy, and non-destructive evaluation techniques. His studies often explore juvenile/mature wood transitions and environmental impacts on material properties. No scientific awards are explicitly listed, though his extensive publication record reflects significant contributions. He advises no listed students but collaborates on interdisciplinary projects through the Faculty's institutes, including the Institute of Wood Science and the Institute for Materials Technology. Labs/Teams: Active in multiple university institutes focusing on wood technology, materials science, and forest engineering. His research often involves cross-departmental collaborations on cultural heritage preservation and sustainable forestry practices.
Andrej Novak is an Associate Professor at the Theoretical Physics Department , Faculty of Science, University of Zagreb. He holds a PhD in Mathematical Models of Flow in Porous and Mixed Media (2017) and a Master's in Mathematical Model of Piano String (2011), both from University of Zagreb. Research Interests span: (1) Partial Differential Equations & Mathematical Modeling, (2) Numerical Solutions of PDEs, (3) Data Analysis Algorithms (bioinformatics/medical applications). Current focus includes shock filter equations, medical image processing, and cardiovascular pharmacotherapy modeling. Key Projects include leading the 2024 HRZZ-funded 'From PDEs to Deep Learning: Advancing Medical Image Processing' and contributing to projects like 'Analysis of partial differential equations and shape optimization' (HRZZ, 2023). He has participated in international collaborations including Austrian-funded 'Vanishing Capillarity on Smooth Manifolds' (2019). Teaching responsibilities include courses like Computational Neuroscience, Introduction to Computer Science, and Numerical Mathematics. He advises on C++ programming, AI fundamentals, and mathematical modeling across undergraduate and graduate levels. Publications highlight contributions in journals like Archive for Rational Mechanics and Analysis (2024), Applied Soft Computing (2025), and Canadian Journal of Cardiology (2025), focusing on interdisciplinary applications of PDEs, machine learning in healthcare, and image processing techniques.
Katarina Martinko, PhD, is a Postdoctoral Student in the Division for Phytomedicine at the Department of Plant Pathology, Faculty of Agriculture, University of Zagreb. With active involvement since 2016, her work focuses on fungal diagnostics, biocontrol agents, and antimicrobial compound applications. Current affiliation: Faculty of Agriculture, University of Zagreb Teaching: Osnove biljne patologije , Štetni organizmi energetskih kultura Consultation hours: Fridays 12-14 Research Focus: Mycology, plant pathology, and ecological farming applications. Key areas include: Fungal taxonomy and diagnostic methods Antifungal activity of natural and synthetic compounds Biopolymer-based delivery systems for plant protection Essential oils as biopesticides Entomopathogenic fungi for plant disease control Publication Trends (2025-2023): Recent work emphasizes boric acid derivatives for pathogen control, Trichoderma-based biocontrol, and nanotechnology applications in crop protection. Over 60% of her publications focus on fungal inhibition mechanisms and sustainable alternatives to conventional pesticides. Collaborations: Engaged in interdisciplinary projects combining microbiology, materials science, and agricultural engineering.
