جست‌وجوی استاد و پژوهشگر

Hrvoje Novakمشاهده پروفایل

پژوهشگر

• Control Systems
• Machine Learning
• Energy Management
• +۶ مورد دیگر

Hrvoje Novak is a Leading Researcher at the Department of Control and Computer Engineering, University of Zagreb Faculty of Electrical Engineering and Computing. His work focuses on interdisciplinary research spanning energy systems optimization, precision agriculture, and advanced control methodologies. He has contributed to innovative solutions in predictive control for building energy management, railway traction systems, and water treatment infrastructure. His research integrates machine learning, IoT, and remote sensing technologies to address challenges in smart grids, crop health monitoring, and insect pest management. Key research areas include: Predictive control strategies for energy-efficient systems Machine learning applications in agricultural pest detection Data-driven modeling of urban traffic and infrastructure IoT-based plant development modeling systems Optimization of railway traction and energy storage systems His publications emphasize practical implementations such as hierarchical building energy management, flight mill analysis for invasive species, and grey-box modeling of water treatment plants. Novak collaborates across academic and industrial sectors to advance sustainable technologies.

Ana Pap Vorkapićمشاهده پروفایل

استاد

• Nonprofit Marketing
• Political Marketing
• Consumer Behavior
• +۵ مورد دیگر

Ana Pap Vorkapić, PhD, is a Professor at the Department of Marketing, Faculty of Economics and Business in Osijek, University of Osijek. Her academic journey includes postdoctoral studies in Management (defended 2019) and has been a faculty member since 2014. She transitioned to her current rank of Professor after serving as an Assistant Professor since 2020. Her research focuses on non-profit marketing (particularly political and social aspects), consumer behavior, voter behavior, and generational studies with a focus on Generation Z. Notable areas include: Nonprofit marketing strategies impacting prosocial behavior Political marketing to reduce civic apathy Generational differences in pandemic-era consumer behavior Employee turnover prediction using machine learning Teaching responsibilities include undergraduate and graduate courses such as Market Analysis, B2B Marketing, Web Analytics, and Political Marketing. She actively contributes to academic governance as an editorial board member for an international journal and CROMAR member. Her work integrates digital marketing trends with organizational behavior insights. Key professional activities include organizing international symposia, publishing over 30 peer-reviewed articles since 2015, and collaborating on projects like neural networks for energy consumption prediction. Her research bridges marketing theory with practical applications in political strategy, sustainability, and cultural institutions.

Zvonko Čapkoمشاهده پروفایل

استاد

• Information Systems
• Digital Transformation
• Artificial Intelligence in Business
• +۵ مورد دیگر

Zvonko Čapko is a Full Professor at the Faculty of Economics and Business, University of Rijeka, specializing in information systems and digital business technologies. His academic profile demonstrates extensive expertise across undergraduate, graduate, and doctoral programs where he teaches critical courses in database management, digital transformation, and artificial intelligence applications in business contexts. His research interests center on the intersection of information technology and business management, with particular focus on: Digital transformation processes and disruptive business models Application of AI and machine learning in business decision-making Electronic business systems and security frameworks Modern communication channels in digital business environments ICT project management methodologies Professor Čapko's teaching portfolio reveals significant contributions to curriculum development in emerging digital business fields, particularly in areas like blockchain applications, IoT integration, and cloud computing strategies. His course structures emphasize practical implementation of theoretical concepts through tools like WordPress, Canva, and data analytics platforms. His professional activities demonstrate strong engagement with contemporary business technology challenges, including: Digital economy frameworks and information society evolution Strategic implementation of primary digital technologies (cloud computing, big data) Secondary digital technology applications (AI, robotics, AR/VR) Ethical considerations in AI business implementation While specific research publications aren't detailed in the available information, his course content indicates active involvement in cutting-edge business technology research areas, particularly in digital business model innovation and ICT project management methodologies.

Anamarija Zronمشاهده پروفایل

استادیار

• Information Systems
• Artificial Intelligence
• Business Intelligence
• +۳ مورد دیگر

Anamarija Zron is an Assistant Professor at the Faculty of Economics (EFRI) of the University of Rijeka. She teaches courses on Information and Communication Technologies in Economics and Business, and Artificial Intelligence in Business. Her research focuses on AI applications in business, data analysis, and negotiation strategies with a cultural perspective. Her teaching includes modules on computational modeling with Excel, VBA programming, and the ethical implications of AI in business. Courses also cover virtual/augmented reality applications and digital transformation trends. Recent research explores innovative leadership's impact on employee innovation, business intelligence tools for smart city rankings, and cross-cultural negotiation frameworks.

Vilko Smrečkiمشاهده پروفایل

پژوهشگر

• NMR Spectroscopy
• Biochemistry
• Molecular Spectroscopy
• +۴ مورد دیگر

Vilko Smrečki is a Senior Researcher and Assistant Director at the NMR Centre of Ruđer Bošković Institute in Zagreb, Croatia. He holds a Ph.D. in Chemistry from the University of Zagreb (1998) and has maintained continuous academic engagement through teaching and research collaborations with the University of Zagreb and University of Split. His research spans NMR spectroscopy applications in biochemistry, material science, and quantum chemical modeling. Key interests include structural analysis of bioactive molecules, DNA/RNA secondary structures, zeolite nanomaterials, and machine learning applications in NMR data interpretation. His work demonstrates strong interdisciplinary collaboration across chemistry, physics, and computational science. Analysis of his 15 most recent publications reveals a consistent focus on advancing NMR methodologies for complex systems, with increasing integration of computational approaches since 2015. His research bridges fundamental NMR physics with practical applications in petroleum analysis, glycobiology, and nanomaterial characterization. Ruđer Bošković Institute Award for best scientific papers (2020) Smrečki has mentored numerous graduate students across chemistry programs at the University of Zagreb and supervised multiple doctoral theses. His current leadership of the Horizon Europe R-NMR project demonstrates ongoing grant acquisition success. The NMR Centre under his direction maintains active collaborations with international research groups and provides essential infrastructure for structural analysis across multiple scientific disciplines.

• Cybersecurity
• Artificial Intelligence in Education
• Information Systems Security
• +۳ مورد دیگر

Dr. Bernard Vukelić is a Professor of Professional Studies at Veleučilište u Zagrebu (Collegium Carolinum), specializing in cybersecurity, AI applications in education, and information systems security. He holds a Doctorate in Sociology (Dr. Sc.) and focuses on topics like digital transformation, phishing detection, and lifelong learning strategies. His research bridges theoretical frameworks with practical applications in office automation, web application security, and AI-driven solutions for educational assessment. Education: PhD in Sociology (Dr. Sc.) His research interests include: Cybersecurity measures for critical infrastructure AI ethics and implementation in higher education Automated office processes using ChatGPT Phishing attack recognition and mitigation Content management system vulnerabilities Indoor positioning system analysis Recent Research Trends: His work from 2024 emphasizes AI's role in office automation and cybersecurity resilience, while 2023 papers address AI-driven examination proctoring and phishing detection methodologies. Earlier studies explored backend web frameworks and biometric algorithms. He teaches courses like Tools for Digitalization of Business and Security of Information Systems , reflecting his practical focus on industry-relevant technical skills.

Tomislav Sedlarمشاهده پروفایل

دانشیار

• Wood Technology
• Non-destructive Testing
• Mechanical Properties of Wood
• +۴ مورد دیگر

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.

• Applied Mathematics
• Partial Differential Equations
• Numerical Mathematics
• +۴ مورد دیگر

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.

• Econometrics
• Causal Inference
• Time Series Analysis
• +۳ مورد دیگر

Rok Spruk, PhD, is an Assistant Professor at the Faculty of Economics, University of Ljubljana. His academic work focuses on advanced econometric methods and causal inference, with a particular emphasis on time series analysis, dynamic panel data modeling, and policy evaluation techniques such as difference-in-differences and synthetic control estimators. Causal inference frameworks (matching, instrumental variables, regression discontinuity) Time series econometrics (ARIMAX, GARCH, VAR models) Dynamic panel data methods (Arellano-Bond, Blundell-Bond, LSDVc) Big-data analytics and kernel-regularized least squares Policy evaluation with synthetic control estimators

• Fluid Dynamics
• Mathematical Biology
• Partial Differential Equations
• +۳ مورد دیگر

Boris Muha is a Professor in the Department of Mathematics at the University of Zagreb's Faculty of Science. His research focuses on fluid-structure interaction, mathematical modeling in biomechanics, and numerical analysis of partial differential equations. He has contributed extensively to the analysis of complex systems involving fluid dynamics, poroelasticity, and nonlinear structural mechanics. Key research areas include the mathematical analysis of fluid-structure interaction problems, computational methods for porous media, and the development of reduced-order models using deep learning. Recent work emphasizes rigorous derivation of reduced models, validation of solvers for fluid-poroelastic systems, and optimal design of bioartificial organ scaffolds. His publications from 2024–2025 highlight advancements in global weak solutions for fluid-structure systems, nonlinear geometric coupling, and applications to biomedical engineering. Notably, he explores self-propulsion mechanisms in viscous fluids and stability analysis of coupled systems. Awards and grants are not explicitly listed in the provided text. His advising and collaborations span interdisciplinary projects in computational fluid dynamics and mathematical biology, with active participation in international research networks.

Mario Bukalمشاهده پروفایل

استادیار

• Partial Differential Equations (PDEs)
• Fluid Dynamics
• Nonlinear Systems
• +۳ مورد دیگر

Dr. Mario Bukal is an Assistant Professor at the University of Zagreb’s Faculty of Electrical Engineering and Computing, Department of Applied Mathematics. He specializes in Partial Differential Equations (PDEs), particularly evolution equations and systems, with current involvement in the Croatian Science Foundation-funded project Mathematical Analysis of Multi-Physics Problems Involving Thin and Composite Structures and Fluids (MAMPITCoStruFl) . His research focuses on fluid-structure interaction, nonlinear systems, and mathematical modeling. He has taught courses in Mathematics, Probability & Statistics, and Stochastic Processes at both undergraduate and PhD levels, including roles at Vienna University of Technology. Education & Positions: Holds a PhD and has taught at multiple institutions, including TU Wien. Research Interests: Nonlinear PDEs, fluid dynamics, quantum mechanics, and applied mathematical analysis. His recent publications emphasize rigorous derivation of reduced models for complex systems, entropy analysis in quantum diffusion, and numerical schemes for fourth/sixth-order equations. Bukal actively contributes to seminars and conferences on nonlinear analysis and differential equations.

Tomislav Medićمشاهده پروفایل

مدرس

• Information Systems
• Business Informatics
• Artificial Intelligence in Finance
• +۳ مورد دیگر

Tomislav Medić, MA, is a Lecturer at the Department of Informatics, Faculty of Economics and Business, University of Zagreb. His academic work focuses on information systems, educational technology, and financial machine learning. Faculty: Faculty of Economics and Business (University of Zagreb) Department: Informatics Office: Room A501, Trg J.F. Kennedyja 6, Zagreb Consultations: Monday 12-1PM (in-person or via Google Meet) His research explores technology utilization in education , stock market prediction using AI models , and business informatics applications . Recent publications analyze bibliometric trends in educational technology and comparative machine learning approaches for financial forecasting. Web presence: www.efzg.unizg.hr/tmedic | Contact: tmedic@net.efzg.hr

Romeo Šajinaمشاهده پروفایل

مدرس

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

Romeo Šajina is a Lecturer at the Faculty of Informatics in Pula, Croatia, affiliated with the University of Pula . His work focuses on computer science, machine learning, and applied informatics, with publications in areas such as neural networks, time series forecasting, and image processing. University: University of Pula School: Faculty of Informatics His research spans disciplines like Artificial Intelligence , Data Science , and Imaging Technology , emphasizing practical applications in time series modeling and computer vision. Recent publications highlight advancements in deep learning architectures and hybrid data analysis techniques. Articles demonstrate expertise in Neural Networks , Predictive Analytics , and Computer Vision , often published in IEEE and Journal of Imaging . Collaborations with researchers like Marina Ivašić-Kos and Nikola Tanković appear in multiple works. No scientific awards or student advisement details are documented in the provided materials. Further inquiries may be directed via email at romeo.sajina@unipu.hr .

Nikola Bilandžijaمشاهده پروفایل

دانشیار

• Agricultural biomass
• Energy crops
• Energy in agriculture
• +۴ مورد دیگر

Nikola Bilandžija is an Associate Professor at the University of Zagreb Faculty of Agriculture, specializing in mechanization and autonomous systems in agriculture. His research focuses on agricultural biomass, energy crops, and engineering solutions for sustainable agroecosystems. He actively contributes to projects addressing climate change mitigation, circular bioeconomy, and bioenergy optimization. University of Zagreb Faculty of Agriculture (2009–present) Projects funded by NATO, Croatian Science Foundation, Horizon 2020, and World Bank Research themes: biomass energy potential, ash fertilization, soil health, and machine learning applications His publications analyze the energy properties and productivity of Miscanthus x giganteus, Virginia Mallow, and cereal residues under varying environmental and technological conditions. Recent work explores ash fertilization impacts, soil respiration dynamics, and waste biomass valorization for bioproducts. He serves as Topic Editor for Energies and Editor-in-Chief for international symposium proceedings, advancing discourse on agricultural engineering and bioenergy systems.

Sven Lončarićمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Medical Imaging
• +۵ مورد دیگر

Academician Professor Sven Lončarić serves as a Full Professor in the Department of Electronic Systems and Information Processing at the Faculty of Electrical Engineering and Computing, University of Zagreb. With his office located in room D-119 and contactable via phone at 6129-891, he maintains an active presence in both teaching and research activities within the institution. His work bridges theoretical computer science with practical applications across multiple domains. Professor Lončarić's research spans computer vision, image processing, and deep learning with significant contributions to medical imaging, particularly in retinal analysis using optical coherence tomography. His work in color constancy and illumination estimation has advanced techniques for handling multi-illuminant scenes, while his research in ultrasound image analysis has practical applications in non-destructive testing. He also explores computer security aspects of machine learning models, particularly in backdoor detection and removal. His recent publications demonstrate a strong trend toward applying deep learning techniques to solve complex problems in medical imaging, retail automation, and industrial applications. The concentration of work in retinal imaging and color constancy shows his commitment to advancing computer vision fundamentals while simultaneously addressing practical challenges in healthcare and industry. His research increasingly incorporates anomaly detection methods and robust security practices for machine learning systems. Professor Lončarić actively contributes to the academic community through organizing events like the Croatian Computer Vision Workshop and the First Croatian Symposium on Artificial Intelligence, providing platforms for knowledge exchange in his fields of expertise. His work on astronomical data processing demonstrates the versatility of his methodological approaches across diverse scientific domains. Within the Department of Electronic Systems and Information Processing, he participates in the Center of Excellence for Computer Vision, contributing to the institution's research profile in artificial intelligence and computer vision. His work on medical imaging applications connects the faculty with healthcare institutions, facilitating interdisciplinary collaborations that translate technical advances into medical practice.