جست‌وجوی استاد و پژوهشگر

• Production Engineering
• Industrial Engineering
• Quality Management
• +۳ مورد دیگر

Milan Erić is a Professor and Chair of Production Engineering at the Faculty of Engineering, University of Kragujevac, Serbia. He is affiliated with the Department for Production Engineering and has held this academic rank since September 28, 2017. His research focuses on production engineering, Industry 4.0, quality management, and the application of machine learning and computer vision in manufacturing processes. He contributes to advancing smart manufacturing systems, defect detection, and real-time nonconformity management through software solutions like the JavaScript MEAN stack. Dr. Erić's work intersects automation, IoT, and digital transformation in both industrial and healthcare contexts. He explores trends such as Quality 4.0 to Quality 5.0 transitions and ecological systems for contactless vehicle cleaning. His research often emphasizes small and medium enterprises (SMEs), addressing their challenges in adopting modern technologies for quality improvement and operational efficiency. Notable areas include: Machine vision-based quality control systems Optimization of production scheduling and material processing Integration of virtual/augmented reality for workplace safety training Development of portable welding machinery and nanocomposite analysis tools His publications span over two decades, reflecting contributions to tribology, CAD/CAM systems, and process reengineering. He advocates for digital factory models and the use of big data in public enterprises for effective digitization.

• Industrial Engineering
• Manufacturing Systems
• Occupational Safety and Health
• +۵ مورد دیگر

Professor Ivan Mačužić is a faculty member at the University of Kragujevac's Faculty of Engineering, specifically within the Department for Production Engineering. His expertise centers on Industrial Engineering, with a focus on Industry 4.0 integration, occupational safety, and human-robot collaboration. He leads research initiatives in manufacturing automation, neuroergonomics, and smart technologies for workplace safety. His research interests include advancing Industry 4.0 applications, optimizing production systems, and leveraging IoT and AI for safety improvements. Notable projects involve robotic stations for food processing, modular lab setups for neuroergonomics experiments, and exoskeletons for manual labor safety. Professor Mačužić emphasizes practical solutions for SMEs, such as IoT-based warehouse management systems and risk assessment tools. His work bridges theoretical frameworks with real-world implementation, addressing challenges in safety culture, process optimization, and human factors in industrial environments. Publications highlight trends in Industry 4.0 safety frameworks (Safety 4.0), cognitive load analysis in collaborative robotics, and deep learning applications for workplace hazard detection. He actively contributes to improving occupational health through innovative technologies and adaptive systems.

• Production Engineering
• Sustainability and Recycling
• Artificial Intelligence Applications
• +۳ مورد دیگر

Aleksandar Đorđević is an Associate Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac. His research focuses on advanced manufacturing technologies, sustainability in production systems, and applications of artificial intelligence in engineering processes. He holds a vocation as Docent and is affiliated with the Faculty's Production Engineering department. Key research interests include Industry 4.0 implementation, recycling optimization, fuzzy logic-based decision models, and supply chain sustainability. His work integrates computational methods like neural networks and genetic algorithms to solve complex engineering challenges. Recent publications highlight trends in real-time quality control systems, energy-efficient recycling processes, and multi-objective optimization frameworks. He has contributed to both theoretical advancements and practical applications in production engineering, with a focus on bridging traditional manufacturing with modern data-driven techniques. No scientific awards are explicitly listed in the provided materials. His advising and grant activities remain unspecified. He is affiliated with the Faculty of Engineering’s laboratories and teams focused on production systems and materials engineering.

Sandra Gajevićمشاهده پروفایل

دانشیار

• Materials Science
• Tribology
• Mechanical Engineering
• +۴ مورد دیگر

Sandra Gajević is an Associate Professor at the Department of Mechanical Constructions and Mechanization, Faculty of Engineering, University of Kragujevac. Her research focuses on machine structures and mechanization, with a strong emphasis on materials science, tribology, and optimization techniques. She has contributed significantly to the study of composite materials, particularly in understanding their mechanical and tribological behaviors under various conditions. Her work spans topics such as powder metallurgy processes, gear system optimization using methods like Taguchi and TOPSIS, and the development of biodegradable biomedical alloys. Recent studies include investigations into hypereutectic aluminum composites, magnesium-based nanocomposites, and the application of nanocomposites in industrial lubricants. Dr. Gajević's publications highlight interdisciplinary approaches combining experimental analysis with computational methods (e.g., artificial neural networks) to optimize material performance. She has also explored the influence of material selection and lubricant properties on gear efficiency, contributing to advancements in automotive and aerospace engineering.

Miladin Stefanovićمشاهده پروفایل

استاد

• Production Engineering
• Industrial Engineering
• Industry 4.0/5.0
• +۷ مورد دیگر

Miladin Stefanović is a Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac. His academic role includes research and teaching in production engineering, industrial systems, and advanced manufacturing technologies. He leads initiatives in Industry 4.0/5.0 integration, quality management systems, and smart manufacturing solutions. His research focuses on applying digital technologies like machine learning, computer vision, and IoT for optimizing industrial processes. Notable projects include robotic systems for food processing, OPC UA integration in automation, and cloud-based quality management frameworks. He emphasizes the transition from Quality 4.0 to 5.0, emphasizing human-centric manufacturing advancements. Stefanović has contributed to over 50 peer-reviewed publications since 2014, with recent work addressing real-time defect detection, smart quality control applications, and organizational resilience post-pandemic. His work bridges theoretical advancements with practical implementations in SMEs and public sector organizations. He has been actively involved in educational reforms, developing didactic tools for Industry 4.0 training and prototyping microprocessor-based learning systems. His lab focuses on edge computing solutions for manufacturing efficiency and sustainable resource allocation strategies.

• Production Engineering
• Tribology
• Materials Science
• +۵ مورد دیگر

Vladimir Kočović is an Associate Professor of Production Engineering at the Faculty of Engineering, University of Kragujevac. His research focuses on advanced manufacturing processes, tribology, materials science, and optimization of machining techniques. He holds a position in the Department of Production Engineering and has contributed to numerous interdisciplinary studies. His work spans experimental and computational methods, including tool wear analysis, material testing, and automation in manufacturing. He has developed specialized devices for measuring kinetic friction coefficients and optimizing cutting processes. Notable projects include studies on micro-cutting processes, 3D model reconstruction, and the application of AI in defect classification. Despite his prolific research output, no scientific awards are explicitly mentioned. He collaborates on projects involving tribological investigations, reverse engineering, and additive manufacturing. His academic activities include teaching and advising on mechanical engineering and industrial processes, though student names are not listed in available texts.

• Applied Informatics in Engineering
• Biomedical Engineering
• Machine Learning
• +۳ مورد دیگر

Tijana Geroski is an Assistant Professor at the Faculty of Engineering, University of Kragujevac, Serbia, affiliated with the Department of Applied Mechanics and Automatic Control. Her work integrates applied informatics in engineering with biomedical applications, focusing on machine learning, medical imaging, and computational modeling. She contributes to interdisciplinary research through platforms like SGABU, designed to bridge education and research in multiscale modeling. Her research spans topics such as predictive modeling for cardiovascular diseases, AI-driven diagnostic systems (e.g., lung and spine imaging analysis), and simulation tools for personalized medicine. Notable projects include developing FPGA-based expert systems for disc hernia diagnosis and optimizing drug delivery via computational fluid dynamics. She also explores the intersection of big data, materials science, and epidemiological modeling, particularly in the context of the SARS-CoV-2 pandemic. Her articles emphasize interdisciplinary collaboration, coupling experimental data with numerical simulations. Recent work highlights advancements in transfer learning for medical imaging, physics-driven deep learning for thermal modeling, and FPGA implementations of Bayesian diagnostic systems. These contributions underscore her commitment to advancing healthcare through computational and AI-based solutions. She collaborates actively with institutes like SARTIK (Steinbeis Advanced Risk Technologies Institute) to enhance biomaterial risk assessment and in-silico clinical trials. Her teaching and research roles reflect a dedication to both academic innovation and practical biomedical engineering applications.

Миодраг Д. Спасићمشاهده پروفایل

دانشیار

• Control Systems
• Model Predictive Control
• Orthogonal Functions
• +۴ مورد دیگر

Миодраг Д. Спасић is an Associate Professor at the Department of Automatics, Faculty of Electronic Engineering, University of Niš, appointed in 2021. His academic journey includes completing his undergraduate studies at the same institution in 2010, followed by earning his PhD from the Norwegian University of Science and Technology in Trondheim in 2019. Dr. Spasić's research focuses on advanced control systems, particularly in the areas of model predictive control, orthogonal functions, neural networks, and nonlinear systems. His work demonstrates a strong emphasis on practical implementations for electromechanical systems, particularly DC motor control and magnetic levitation systems. He has developed innovative approaches combining orthogonal polynomial networks with traditional control methodologies to address challenges in robustness and real-time implementation. His publication record shows consistent productivity with 13 papers in journals with impact factors. Analysis of his recent publications reveals a clear research trajectory focused on enhancing control system performance through orthogonal function-based approaches, with increasing sophistication in handling nonlinearities and uncertainties in complex systems. His work bridges theoretical control concepts with practical engineering applications. Dr. Spasić is actively involved in research projects, currently participating in 2 national and 1 international projects. His collaborative work with colleagues at the University of Niš demonstrates strong institutional research connections within the Department of Automatics.

Miroljub T. Pesicمشاهده پروفایل

استادیار

• Metrology
• Measurement Technology
• Frequency Stability
• +۳ مورد دیگر

Miroljub T. Pesic is an Assistant Professor at the Faculty of Electronics, University of Niš, specializing in Metrology and Measurement Technology. He holds a Master's degree (2003) and a Bachelor's degree (1988) from the same institution. Education: Bachelor of Electrical Engineering and Computer Science, 1988 Master's in Metrology and Measurement Technology, 2003 His research focuses on precision measurement systems, frequency stability analysis, TV signal processing, and satellite-based signal dissemination. He has contributed to advancements in crane positioning encoders, synchronization pulse separation in video signals, and calibration of precision oscillators using TV systems. He currently participates in 1 national research project and has published extensively in journals like Machine Dynamics Problems and Facta Universitatis . His work bridges theoretical metrology with practical applications in telecommunications and industrial automation.

• Computer Science
• Geographic Information Systems (GIS)
• 3D Terrain Visualization
• +۳ مورد دیگر

Dejan D. Rancic is a Professor at the Faculty of Electronics , University of Niš, Department of Electrical Engineering and Computer Science. His academic career spans over two decades, with promotions to Assistant Professor in 2005 and Full Professor in 2015. He earned his PhD (2004), Master's (1997), and BSc (1993) degrees from the same department. Current projects: 3 National, 1 International Reviewer for WSEAS journal series Rančić’s research focuses on Geographic Information Systems (GIS), 3D terrain visualization, and algorithm optimization for large-scale spatial data processing. His work bridges computer science with geospatial engineering, emphasizing parallelism and web-based frameworks. His publications highlight trends in GIS integration (mobile/web), terrain rendering algorithms, and advanced signal processing for meteorological applications. Key subfields include raster map creation, adaptive rendering, and spatial coherency techniques. Contact: Email: dejan.rancic@elfak.ni.ac.rs Address: Aleksandra Medvedeva 4, 18104 Niš Tel: +381 (18) 529-105

Ivan M. Petkovicمشاهده پروفایل

استاد

• Computer Science
• Web Technologies
• Numerical Methods
• +۳ مورد دیگر

Professor Ivan M. Petkovic holds the position of Full Professor at the Department of Computing and Informatics, Faculty of Electronics in Niš, University of Niš. He earned his PhD in 2012 from the same institution in Electrical Engineering and Computer Science, following a Master’s (2006) and Bachelor’s (2001) degree in the same field. His academic career includes election to assistant trainee and full professorship in 2022. Education PhD in Electrical Engineering and Computer Science, Faculty of Electronics, University of Niš (2012) Master’s in Electrical Engineering and Computer Science, Faculty of Electronics, University of Niš (2006) Bachelor’s in Electrical Engineering and Computer Science, Faculty of Electronics, University of Niš (2001) Research Interests Professor Petkovic’s research focuses on computational mathematics, numerical methods, and software engineering. His work bridges theoretical advancements with practical applications, including web security, e-science platforms, and mathematical software development. Notable contributions include web-based laboratories, error-bound algorithms for polynomial zeros, and tools for root-finding methods. Publications & Activities His publications span journals and conferences, emphasizing interdisciplinary applications of computational techniques. Current participation includes 1 national and 1 international project, reflecting active engagement in collaborative research. Awards & Grants No specific awards or grants are listed in the provided materials. His projects and publications highlight sustained academic contributions. Labs & Teams While specific lab affiliations are not detailed, his work suggests involvement in computational and software engineering teams at the Faculty of Electronics.

• Geographic Information Systems (GIS)
• Transportation Systems
• Mobile Computing
• +۳ مورد دیگر

Bratislav B. Predić is a Full Professor at the Faculty of Electronics in Niš, University of Niš, Department of Computing and Informatics. He began his academic career as an Assistant Trainee in 2004 and was elected to his current rank in 2024. He graduated in 2003 from the same faculty (Department of Electrical Engineering and Computer Science), and holds a master's and doctorate in related fields. His research focuses on mobile geographic information systems (GIS), transportation systems, data analysis, and algorithm optimization for real-world applications. Key research interests include context-aware mobile GIS frameworks, automatic vehicle location systems (AVL), and large terrain rendering algorithms. He has authored/co-authored multiple papers in journals and conferences such as WSEAS Transactions on Computers, AGILE Conference, and IASTED International Conferences. His work spans transportation optimization, meteorological visualization, and embedded GIS systems. Currently, he participates in 2 national and 1 international scientific projects. His laboratory and collaboration work involves developing practical solutions for urban mobility, field work automation, and cloud-based geospatial systems. Contact: bratislav.predic@elfak.ni.ac.rs

• Computer Science
• Electrical Engineering
• Computer Architecture
• +۳ مورد دیگر

Oliver M. Vojinović serves as an Assistant Professor in the Department of Electrical Engineering and Computing at the Faculty of Electronic Engineering, University of Niš. Appointed to his current academic rank in 2017 after serving as an assistant trainee since 2001, he maintains active roles in teaching and research within Serbia's academic framework. His educational foundation includes a Bachelor's degree (2000) and Master's degree (2008), both in Electrical Engineering and Computer Science from the Faculty of Electronic Engineering. These qualifications established his technical expertise in computing systems and electrical engineering disciplines. Dr. Vojinović's research spans Computer Science, Electrical Engineering, and Education Technology, with concentrated efforts in Computer Architecture simulation tools and optimized Signal Processing implementations. His work bridges theoretical computing concepts with practical engineering applications, particularly through development of educational simulation environments like SimArch for computer architecture instruction. Analysis of his publication history reveals consistent contributions to folded FIR filter architectures and computer science education methodologies. The trajectory shows evolving focus from hardware implementation (2002-2004) toward pedagogical applications of computing (2005-2007), demonstrating interdisciplinary integration of engineering principles with educational innovation. Currently engaged in one national and one international research project, he contributes to academic advancement through project-based learning initiatives and TEMPUS mobility programs. His institutional involvement includes participation in faculty quality assurance frameworks and continuous education programs at the University of Niš.

Dragan H. Stojanovicمشاهده پروفایل

استاد

• Artificial Intelligence
• Edge Computing
• Smart City Systems
• +۳ مورد دیگر

Dr. Dragan H. Stojanovic serves as a Professor at the Faculty of Electronic Engineering, University of Niš, specializing in computer science since his appointment in 2015. His academic journey spans over three decades at the same institution, where he earned all his degrees and now leads research in cutting-edge computational fields. His educational background includes: PhD in Electrical Engineering and Computing (2004, University of Niš) MSc in Electrical Engineering and Computing (1998, University of Niš) BSc in Electrical Engineering and Computing (1993, University of Niš) Stojanovic's research centers on Artificial Intelligence and Edge Computing , with significant contributions to Smart City infrastructures, parallel processing algorithms, and neural network applications. His work bridges theoretical computer science with practical implementations in urban systems, demonstrated through collaborations on 1 national and 2 international research projects . Recent publications (2022-2025) reveal a strategic pivot toward resource-constrained AI deployment across edge-fog architectures, while earlier work (2014-2020) established foundations in geospatial data parallelization and social media analytics. His publication portfolio shows evolving expertise: 2014-2019: Focus on parallel computing (MPI/CUDA) for geospatial and trajectory data 2020-2022: Integration of IoT and social networks into Smart City business processes 2023-2025: Advanced Edge AI optimization for real-time object detection and prediction systems Stojanovic actively contributes to academic knowledge transfer through project leadership and has published 16 journal articles in impact-factor journals. His current research trajectory emphasizes sustainable computing paradigms for urban environments, with emerging work on competency-focused AI education frameworks.

Slavko Mentusمشاهده پروفایل

استاد

• Electrocatalysis
• Battery Technology
• Weather Modification
• +۲ مورد دیگر

Dr. Slavko Mentus is a full Professor at the Faculty of Physical Chemistry, University of Belgrade, and a full member of the Serbian Academy of Sciences and Arts (SASA). His academic career spans fundamental research in electrochemistry, battery technology, and weather modification. His research interests focus on electrocatalysis (particularly hydrogen/oxygen evolution reactions), eco-friendly battery systems (aqueous electrolyte alkali-ion batteries), and weather control technologies . He pioneered silver iodide-reduced anti-hail formulations and leads national projects on lithium-ion batteries and fuel cells since 2011. His work emphasizes environmentally sustainable energy solutions, including sodium-ion cathodes and biomass-derived supercapacitors. Analysis of his 15 most recent publications (2022-2024) reveals a strong trend toward next-generation energy storage with emphasis on sodium-ion systems, bifunctional electrocatalysts for fuel cells, and sustainable material design. Key subfields include aqueous electrolyte stability, transition metal oxide engineering, and computational modeling of single-atom catalysts. Mentus actively participates in international scientific discourse, organizing events like the COIN2022 Symposium in Belgrade. His work bridges fundamental physicochemical principles with practical applications in climate-resilient technologies and clean energy infrastructure.