جست‌وجوی استاد و پژوهشگر

Karlo Veličanمشاهده پروفایل

پژوهشگر

• Material Science
• Nanotechnology
• Photocatalysis
• +۳ مورد دیگر

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.

Kristina Kovačevićمشاهده پروفایل

پژوهشگر

• Machine Learning
• Business Analytics
• Data Mining
• +۳ مورد دیگر

Kristina Kovačević is a researcher and teaching collaborator at the Faculty of Economics, University of Osijek, where she has been employed since February 2020. She is affiliated with the Department of Quantitative Methods and Informatics and contributes to courses such as Statistics and Quantitative Methods for Business Decision-Making. Educated in Business Economics with a focus on Business Informatics Doctoral candidate in Business Economics in a digital environment at the University of Dubrovnik and University of Zagreb since November 2020 Her research interests center on Machine Learning and its applications in energy management, business process optimization, and economic trend prediction. She actively participates in the research project funded by the Croatian Science Foundation, titled "Methodological Framework for Efficient Energy Management Using Smart Data Analytics," which leverages techniques like neural networks, decision trees, and cluster analysis. Her work intersects Quantitative Methods in Business and Intelligent Data Analytics , emphasizing simulation models and business intelligence systems. While no scientific awards are explicitly mentioned in the provided text, her academic profile reflects engagement in both teaching and research, bridging theoretical and applied aspects of business economics through advanced data analysis methodologies.

• Economics
• Macroeconomics
• Business Cycles
• +۳ مورد دیگر

Marija Hruška, PhD is a researcher at the University of Zagreb Faculty of Economics & Business , affiliated with the Statistics Faculty . Her research focuses on macroeconomic dynamics , including economic policy uncertainty , business cycle coherence , and zombie company impacts in Central/Eastern Europe. Her recent work analyzes consumer confidence indicators and unemployment determinants in the EU, combining traditional economic analysis with machine learning applications in policy modeling. Key sub-fields include housing market economics , corporate finance spillovers , and economic sentiment analysis . Her publications span topics from zombie company effects to labor market dynamics . She currently maintains an email contact at mlogarusic@efzg.hr but has paused office hours due to maternity leave.

Krešimir Fertaljمشاهده پروفایل

استاد

• Software Engineering
• Information Systems
• Project Management
• +۶ مورد دیگر

Krešimir Fertalj is a Full Professor at the Department of Applied Computing, Faculty of Electrical Engineering and Computing, University of Zagreb. His work focuses on software development, project management, and data integration architectures. Research areas include ERP systems, agile methodologies, and hybrid wireless networks in maritime environments Developed tools for workflow modeling, business process automation, and mobile application frameworks Contributed to projects like Flora Croatica Database, CROFlora 2.0, and institutional GIS systems Teaching responsibilities cover structured programming techniques (UML), web service development, and software reliability analysis. Contact: Office D-369, Work 01 6129-918, Home 418

• Kinesiology
• Sports Science
• Volleyball
• +۵ مورد دیگر

Mirjana Milić is an Associate Professor at the Faculty of Kinesiology, University of Split. She holds a doctoral degree in Kinesiology from the same institution (2014). Her academic work focuses on sports kinesiology, volleyball, and physical education methodologies. Research Interests: Volleyball, sports research methodology, kinesiological education, anthropometry, motor skills, physical activity Teaching Roles: Lecturer for undergraduate and graduate courses including Systematic Kinesiology, Volleyball Methodology, and Research Methodology Her publications emphasize volleyball player profiling, injury prevention, and the intersection of physical activity with public health and education. She contributes to understanding motor ability development in youth athletes and has explored topics like health literacy among university students.

Mario Stipčevićمشاهده پروفایل

استاد

• Quantum optics
• Quantum information
• Quantum communication
• +۵ مورد دیگر

Mario Stipčević is a senior scientist at the Ruđer Bošković Institute (RBI) in Zagreb, Croatia, where he heads the Photonics and Quantum Optics Laboratory within the Division of Experimental Physics. Holding the Croatian rank of scientific advisor in permanent position —equivalent to full professor—he has led national and international research efforts spanning quantum optics, quantum-information science, and high-energy neutrino physics. Education 2011–2012: Visiting Specialization in Experimental Quantum Information, University of California, Santa Barbara, USA 2010–2011: Fulbright Scholar, Experimental Quantum Information, University of California, Santa Barbara, USA 1994: PhD in Particle Physics, Université de Savoie, Chambéry, France 1991: BSc in Theoretical Nuclear Physics, Faculty of Science, University of Zagreb Research Interests His work focuses on quantum communication , quantum randomness , single-photon detection , quantum key distribution , and quantum holography . Early in his career he contributed to neutrino oscillation experiments (NOMAD, OPERA) and calorimetry R&D for the LHC. Scientific Awards Fulbright Scholarship (2010–2011) Golden Medal ARCA 2005, Zagreb International Autumn Fair Golden Medal, Salon International de Inventions, Geneva 2005 Young Investigator Award, Ministry of Science and Technology, Croatia (1998) Projects & Leadership Since 2014 he has been Head of the Photonics and Quantum Optics Research Unit at the RBI Centre of Excellence for Advanced Materials and Sensing Devices. Earlier projects include the Croatian Ministry of Science grant Experiments in Quantum Communication and Quantum Information (2007–2014) and World-Bank-funded development of a Quantum Random Bit Generator (2004–2005). Laboratory & Teams At RBI he directs the Photonics and Quantum Optics Laboratory , a multi-disciplinary group developing photon-counting detectors, entangled-photon sources, and quantum-network testbeds. The lab participates in European initiatives such as the European Quantum Internet Alliance and the ESSnuSB neutrino super-beam design study .

Ana Marija Filipasمشاهده پروفایل

مدرس

• Econometrics
• Big Data Analytics
• Regression Analysis
• +۳ مورد دیگر

Ana Marija Filipas serves as a Lecturer at the Faculty of Economics and Business (EFRI) of the University of Rijeka, Croatia, where she delivers core quantitative coursework for undergraduate and graduate programs. Her institutional affiliation includes active teaching responsibilities within the Faculty's academic structure, with office hours maintained for student consultation in Chair 62/III. Her research and pedagogical expertise centers on econometric methodology and big data applications in business contexts. She systematically covers probability theory, mathematical statistics, linear regression modeling (including OLS derivation, categorical variables, and diagnostic testing for multicollinearity/heteroscedasticity), and advanced analytics techniques such as supervised/unsupervised learning, decision trees, association rule mining, and text mining. This bridges classical econometric frameworks with contemporary data science tools for economic analysis. Her scientific contributions manifest through curriculum development in quantitative disciplines, particularly the foundational 'Basics of Econometrics' course and the English-taught 'Big Data Analytics' program covering data preprocessing, model deployment, and ensemble methods. While specific research outputs aren't documented in the source material, her instructional focus demonstrates applied expertise in transforming complex statistical concepts into practical business analytics solutions.

Ivana Pajač Živkovićمشاهده پروفایل

دانشیار

• Agricultural Entomology
• Integrated Fruit and Grape Protection
• Taxonomic Identification
• +۶ مورد دیگر

Assoc. Prof. Ivana Pajač Živković is an Associate Professor at the Faculty of Agriculture, University of Zagreb , specializing in Agricultural Entomology at the Division for Phytomedicine. Her research focuses on integrated fruit and grape protection , molecular identification of pests , and invasive arthropod dynamics , with expertise in Cydia pomonella genetics and geometric morphometrics . Education: Doctor of Science (2009-2012), Faculty of Agriculture, University of Zagreb Master Engineer of Phytomedicine (2001-2007), Faculty of Agriculture, University of Zagreb Her publications emphasize technology-driven pest monitoring (e.g., machine learning, hyperspectral imaging) and biological control strategies for invasive species like Halyomorpha halys and Cydalima perspectalis . Recent work explores caffeine-based biopesticides and wing morphometric tracking for population spread analysis. Professional activities include editorial roles at Agriculturae Conspectus Scientificus (2021-) and Entomologia Croatica (2011-2016). She has coordinated projects on pesticide resistance monitoring and invasive species management , funded by Croatian Science Foundation and EU programs.

• Probability Theory
• Mathematical Statistics

Bojan Basrak is a Full Professor at the Department of Mathematics, University of Zagreb, specializing in Probability Theory and Mathematical Statistics. He is affiliated with the Division of Probability Theory and Mathematical Statistics and actively involved in research and teaching. Teaching roles: Lecturer in charge for graduate and doctoral courses including 'Fundamentals of probability theory,' 'Time series,' and 'Probability.' His research focuses on Poisson point processes and hierarchical modeling of character strings, bridging theoretical probability with computational applications. While specific awards are not listed, his active involvement in EU projects like RobSparseRand and QuantiXLie suggests ongoing contributions to interdisciplinary mathematical research.

Franko Šikićمشاهده پروفایل

پژوهشگر

• Computer Vision
• Deep Learning
• Retail Analytics
• +۳ مورد دیگر

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.

Jasmina Pivarمشاهده پروفایل

استادیار

• Business Informatics
• Big Data
• Machine Learning
• +۵ مورد دیگر

Jasmina Pivar is an Assistant Professor in the Department of Informatics at the Faculty of Economics - Zagreb (University of Zagreb). Her research focuses on business informatics, big data, machine learning, and smart cities, with applications in fraud detection, human resource management, and urban planning. Research Interests: She explores intersections of technology and economics, including patent analysis of emerging technologies, cluster-based financial strategies, and digital literacy trends. Her work addresses challenges in smart city development, churn management, and data-driven policy for the EU video game industry. Publications Trends: Over the past decade, her articles highlight big data adoption frameworks, fraud profiling techniques, and generational shifts in digital behavior. She frequently employs machine learning and cluster analysis for predictive modeling. Contact: Reach her at jpivar@efzg.hr or Room A507, Faculty of Economics - Zagreb.

Davor Runjeمشاهده پروفایل

مدرس

• Artificial Intelligence
• Theoretical Computer Science
• Software Engineering
• +۴ مورد دیگر

Davor Runje is a lecturer at Algebra University with extensive industry experience as a software engineer, computer scientist, and serial entrepreneur. He has co-founded multiple technology ventures including AIRT (an AI startup), DRAP (a digital agency acquired by Imago Ogilvy in 2018), and PlayMedia Systems (1997), which became a global leader in AMP MP3 playback technology. His research interests span artificial intelligence, theoretical computer science, parallel and distributed computing, and cryptography. Runje has made significant contributions to programming for multiprocessor/multicore systems, with work that later became the Task Parallel Library in the .NET framework during his time at Microsoft Research. His publication portfolio shows a clear evolution from theoretical computer science and concurrency research (2003-2009) toward machine learning and AI (2019-2025), with particular focus on neural networks, model interpretability, and security aspects of large language models. His recent work demonstrates expertise in constrained monotonic neural networks, attention mechanisms for tabular time-series, and vulnerabilities in large language models. His notable achievements include: Microsoft Research SSCLI and Phoenix 2005 awards Two US patents 20 publications in theoretical computer science and artificial intelligence Chairing the Croatian Independent Software Exporters board (2020-2024) As an active industry leader, Runje has participated in numerous legal and tax reform initiatives aimed at increasing the competitiveness of the Croatian IT sector in global markets, representing approximately one-third of the Croatian IT industry through his leadership role.

• Image Processing
• Computer Vision
• Pattern Recognition
• +۳ مورد دیگر

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 Mastanjevićمشاهده پروفایل

دانشیار

• Food Safety
• Analytical Chemistry
• Brewing Technology
• +۵ مورد دیگر

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.

Vinko Lešićمشاهده پروفایل

دانشیار

• Model Predictive Control
• Smart Grids
• Renewable Energy Systems
• +۵ مورد دیگر

Associate Professor Vinko Lešić is affiliated with the University of Zagreb's Faculty of Electrical Engineering and Computing (FER), specifically within the Department of Control and Computer Engineering. His research focuses on advanced control systems, smart grids, renewable energy integration, IoT applications in agriculture, and optimization algorithms. Notable projects include predictive climate control systems for buildings, precision pest detection using hyperspectral imaging, and energy-efficient street lighting solutions. He has contributed to over 50 peer-reviewed articles and led initiatives like the AgroSPARC project for climate-resilient agriculture. His work bridges theoretical control theory with practical applications in smart cities and sustainable energy systems. Research interests span Model Predictive Control (MPC), distributed energy management, and machine learning integration with industrial automation. He collaborates on EU-funded projects addressing climate change impacts on agriculture and urban infrastructure. Teaching responsibilities include courses on automation fundamentals and process control, emphasizing hands-on IoT and PLC implementations. Current activities include developing zone climate control living labs and resilient energy management systems for buildings and microgrids. Publications highlight innovations such as coalitional MPC for building zones, data-driven thermal modeling, and adaptive battery charging for electric vehicles. He advises projects on renewable energy integration and has pioneered sensor-based systems for crop health monitoring. Though no formal awards are listed, his extensive publication record and industry collaborations reflect his academic and applied contributions.