جست‌وجوی استاد و پژوهشگر

Nenad Miticمشاهده پروفایل

استاد

• Data Mining
• Database Systems
• Machine Learning
• +۳ مورد دیگر

Nenad Mitic is a regular Professor at the Department of Computer Science and Informatics , Faculty of Mathematics , University of Belgrade. He teaches courses in data mining, relational databases, and data exploration for Industry 4.0 and bioinformatics. His work includes Introduction to Computer Organization (2013), Fundamentals of Computer Systems (2003), and Fundamentals of Programming - Collection of Problems (2000, co-authored). Courses : R270 (Relational Databases), R275 (Data Exploration 2), R374 (Data Research B), R274 (Data Exploration 1), 9018 (Data Exploration for Industry 4.0 Students) Textbooks : Introduction to Computer Organization (2013), Fundamentals of Computer Systems (2003), Fundamentals of Programming (2000, co-authored) Research interests focus on data mining, database systems, and computational methods. His courses emphasize practical applications in data classification, clustering, anomaly detection, and SQL optimization.

Mladen Nikolićمشاهده پروفایل

دانشیار

• Machine Learning
• Automated Reasoning
• Earthquake Damage Assessment
• +۲ مورد دیگر

Mladen Nikolić is an Associate Professor at the Faculty of Mathematics, University of Belgrade, specializing in machine learning and automated reasoning. He actively contributes to the Machine Learning and Applications Group (MLA@MATF) and the Automated Reasoning GrOup (ARGO) . His research spans earthquake damage assessment , deep learning object tracking , LLM integration with tabular data , and astronomical data analysis . Recent work focuses on the RELAR Project for rapid earthquake loss assessment, CNN architectures for structural damage classification, and novel approaches to incorporating large language model priors into machine learning systems. His publications demonstrate strong interdisciplinary applications connecting computer science with seismology, transportation engineering, and astrophysics. Developed frameworks for earthquake loss assessment and recovery Advanced deep learning filters for non-linear motion tracking Integrated LLMs with tabular data processing systems Contributed to LSST astronomical data challenges Nikolić maintains active research collaborations through MLA@MATF and ARGO groups, with publications spanning machine learning theory, automated reasoning systems, and practical applications across multiple scientific domains. His work shows increasing focus on real-world deployment of AI systems for disaster response and scientific data analysis.

Milan G. Đorđevićمشاهده پروفایل

استادیار

• Theoretical Computing
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Milan G. Đorđević serves as an Assistant Professor at the Faculty of Mathematics and Computer Sciences, Alfa BK University, where he has taught core computer science courses for over a decade including Programming 1, Object-Oriented Programming, Data Structures and Algorithms, Operating Systems, and Computer Architecture. He completed his doctoral studies in 2012 at the University of Primorska, Faculty of Mathematics and Information Technology, Department of Computing and Informatics, supported by a scholarship from Slovenia awarded for his exceptional academic performance during higher education in Belgrade. His research focuses on interdisciplinary applications of computing theory: Artificial Intelligence and Machine Learning systems development Combinatorial Optimization with Nature-Inspired Algorithms Computational modeling of Misinformation Spread in Social Networks Dr. Đorđević has authored over 30 international publications and received recognition through: Microsoft Imagine Cup award for mentoring award-winning student projects Slovenian Doctoral Scholarship for academic excellence As an academic advisor, he has guided numerous bachelor's and master's theses to international competition success. He maintains active professional engagement through long-standing memberships in IEEE, IET, and ACM, contributing to global computer science discourse while addressing contemporary societal challenges through computational research.

• Computer Systems
• Data Protection
• Applied Mathematics in Computer Science
• +۴ مورد دیگر

Mladen Janjić is a Lecturer at the Department of Information Technologies, Faculty of Technical Sciences Čačak, University of Kragujevac. He holds a BSc (2005) and MSc (2010) in Electrical Engineering from the same institution, with an MSc thesis focusing on mathematical models of synchronous generators. His research interests span Computer Systems, Data Protection, Applied Mathematics in Computer Science, and E-Learning methodologies. He has published extensively in international journals and conferences, contributing to fields like educational analytics, cloud-based CRM systems, and multi-criteria decision-making. Teaching roles include serving as a Teaching Assistant (2013-2019) and Lecturer (2021-present) for courses such as Web Technologies, Electronic Business, Data Security, and Programming. He has also led projects on IT requalification (e.g., Java and JavaScript training programs) and educational process improvements funded by the Serbian Ministry of Education. Janjić is a recognized photographer with over 70 exhibitions under FIAP and FSS patronage, earning distinctions like F1 (FSS) and AFIAP (FIAP). His academic awards include medals from prestigious photographic salons and contributions to technical education through editorial roles in journals like Serbian Journal of Electrical Engineering .

Vladimir Milovanovićمشاهده پروفایل

دانشیار

• Electrical Engineering
• Computer Science
• Signal Processing
• +۷ مورد دیگر

Dr. Vladimir Milovanović is an Associate Professor at the Faculty of Engineering, University of Kragujevac, Serbia, holding a position as Chair of the Department of Electrical Engineering and Computer Sciences. His academic career is anchored in interdisciplinary research at the intersection of electrical engineering, computer science, and biomedical applications. His research focuses on hardware design, radar sensor systems, biomedical signal processing, and machine learning applications. Notable areas include CMOS circuit design, FPGA-based implementations, and parameterizable hardware generators for signal processing tasks. He also explores medical imaging analysis using deep learning techniques for conditions like disc hernia diagnosis. Recent work emphasizes radar technology (FMCW transceivers, signal processing architectures), embedded systems (FPGA development, IP core utilization), and high-performance streaming data algorithms. His publications span over two decades, demonstrating expertise in analog/digital circuit design, comparative classifier analysis in biomedical contexts, and hardware-software co-design methodologies. Dr. Milovanović collaborates with industry on energy-efficient MIMO arrays and semiconductor gas sensors. His contributions include open-source HDL models for digital signal processors and comparator circuits optimized for low-power and high-speed applications.

• Energy Efficiency
• Renewable Energy Technologies
• Environmental Sustainability
• +۳ مورد دیگر

Nebojša Jurišević is a **Scientific Associate** at the **Faculty of Engineering**, University of Kragujevac, Serbia. He is affiliated with the **Department of Energy and Process Engineering**, focusing on energy efficiency, renewable energy systems, and environmental sustainability. His research spans interdisciplinary domains including energy management in public buildings, waste-to-energy technologies, and smart infrastructure solutions. His work integrates advanced methodologies such as machine learning and AI tools (e.g., Large Language Models) to optimize energy systems and assess environmental impacts. Notable projects include analyzing energy performance in kindergartens, sports facilities, and solar greenhouses, as well as evaluating policies for electric vehicle adoption and air quality initiatives in Serbia. He has contributed to studies on wastewater heat recovery, sewage sludge utilization, and citizen science-based air quality monitoring. His research often emphasizes real-world applications, such as improving energy efficiency in public sector buildings and supporting circular economy frameworks. While no formal awards are listed, his prolific publication record reflects sustained contributions to technical and technological sciences, with a focus on bridging theoretical and applied engineering challenges. Nebojša collaborates on projects involving energy auditing, solar collector design (e.g., flat-plate solar collectors with selective absorbers), and policy analysis for sustainable urban development. His work underscores the importance of interdisciplinary approaches to address contemporary environmental and energy challenges.

• Biomedical Engineering
• Production Engineering
• Industrial Engineering
• +۳ مورد دیگر

Dr. Goran Devedžić is a Professor at the Department of Production Engineering within the Faculty of Engineering at the University of Kragujevac, Serbia. His academic focus spans Production Engineering and Industrial Engineering, with interdisciplinary contributions in biomedical engineering and medical informatics. He leads research initiatives integrating artificial intelligence, robotics, and simulation technologies into medical diagnostics and manufacturing processes. Research Interests: Biomedical engineering applications in musculoskeletal disorders (e.g., scoliosis, osteoarthritis) Medical imaging and AI-driven diagnostic systems (e.g., CNNs for neurosonography) Advanced manufacturing techniques including reverse engineering and CAD/CAM integration Biomechanical modeling of human movement (gait analysis, joint kinematics) Development of clinical decision-support systems like ScolioMedIS Notable Contributions: His work bridges engineering and healthcare through innovations like AI-based diagnostic algorithms, 3D spinal modeling, and customized orthotic design. Publications emphasize practical applications in smart healthcare technologies and industrial process optimization. Grants & Collaboration: Active in EU-funded initiatives for bioengineering education and cross-border Balkan academic collaboration. Involved in digital manufacturing projects integrating distributed manufacturing processes and knowledge-based systems. Labs/Teams: Leads research groups focused on biomedical informatics, orthopedic engineering, and industrial simulation platforms like IRoSim.

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

Slobodan Mitrović is a Professor in the Department of Production Engineering at the Faculty of Engineering, University of Kragujevac. His academic role emphasizes research and teaching in production systems, materials science, and tribology. Research Interests : His work focuses on advanced manufacturing technologies, including tribological behavior of materials, additive manufacturing processes, and quality management frameworks. Specific areas include friction and wear analysis of metals/polymer composites, 3D printing applications, and Industry 4.0 integration. He also explores educational technologies for STEM training in early childhood education. Key Contributions : He has developed novel methods for measuring kinetic friction under dynamic loads and pioneered research into nanocomposite material characterization. His publications frequently address practical challenges in mechanical engineering, such as optimizing CNC machining parameters and enhancing biomedical alloy performance. Awards : No specific awards are listed in the provided texts, though his extensive publication record indicates significant scholarly contributions. Advising & Grants : While specific grants are not detailed, his research involves collaborations on machine design, tribology instrumentation, and educational tool development. No advisee names are recorded in the current data. Labs & Teams : Affiliated with production engineering laboratories at the Faculty of Engineering, contributing to cross-departmental projects in mechanical systems and materials innovation.

• 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.

Aleksandar Bodićمشاهده پروفایل

پژوهشگر

• Mechanical Engineering
• Structural Analysis
• Numerical Simulations
• +۳ مورد دیگر

Aleksandar Bodić is a Researcher at the Department of Applied Mechanics and Automatic Control, Faculty of Engineering, University of Kragujevac, Serbia. His research focuses on structural analysis, materials science, numerical simulations, and biomedical engineering applications. He holds a position in the Applied Mechanics and Automatic Control department and is affiliated with the university's broader engineering community. His work integrates computational methods like the Finite Element Method (FEM), Smoothed Particle Hydrodynamics (SPH), and Finite Volume Method (FVM) to address challenges in mechanical, civil, and biomedical engineering. Notable areas include piezoelectric nanocomposites, blast-resistant structures, dental material performance, and cardiovascular fluid dynamics. His recent studies emphasize predictive modeling for structural safety, fatigue analysis, and particle dynamics in medical devices. Research interests span advanced materials characterization, structural dynamics under extreme conditions, and computational tools for engineering problem-solving. He collaborates on projects involving interdisciplinary applications, such as improving muzzle brake efficiency for firearms and optimizing drug delivery systems via dry powder inhalers. No academic awards or grants are explicitly mentioned in the provided information. His advisory role and student supervision details are currently unavailable. Affiliated with the Faculty's technical and research infrastructure, his work contributes to the Department for Applied Mechanics and Automatic Control's broader mission in advancing engineering science and technology.

Milan Čabarkapaمشاهده پروفایل

دانشیار

• Telecommunications
• Signal Processing
• RF Engineering
• +۲ مورد دیگر

Milan Čabarkapa is an Associate Professor at the University of Kragujevac's Faculty of Engineering, Department of Electrical Engineering and Computer Science. His research spans telecommunications, signal processing, and RF engineering, with focus on distortion compensation in wireless systems and computational solutions for electromagnetic problems. Čabarkapa develops methods for nonlinear distortion compensation in MIMO transmitters, electromagnetic field modeling, and machine learning applications for signal processing. Recent work explores AI evaluation in linguistics, IoT education tools, and foreign investment analysis frameworks. He contributes to educational initiatives by developing accessible Arduino simulation tools for IoT pedagogy, making hardware experimentation available through online platforms.

Nadica Stojanovićمشاهده پروفایل

دانشیار

• Automotive Engineering
• Internal Combustion Engines
• Thermal Systems
• +۴ مورد دیگر

Nadica Stojanović is an Associate Professor at the Department for Motor Vehicles and Motors, Faculty of Engineering, University of Kragujevac. Their research focuses on automotive engineering, thermal systems, and internal combustion engines, with a particular emphasis on brake systems, aerodynamics, and renewable energy integration. Key areas include improving vehicle safety through thermal management of braking components, optimizing engine performance via numerical simulations, and advancing sustainable energy solutions. Education: No specific educational details provided in the text. Research Interests: Dr. Stojanović’s work spans mechanical engineering innovations in automotive design, including studies on brake wear reduction, disc brake thermal behavior, and aerodynamic stability enhancements. They also explore renewable energy applications such as geothermal systems and wind energy resource assessment. Their computational expertise includes finite element analysis and CFD modeling for optimizing engine and vehicle systems. Articles Trends: Recent publications emphasize interdisciplinary approaches, combining mechanical engineering with computational methods. Key themes include thermal stress analysis in braking systems, dual-fuel engine combustion, wind energy potential evaluation, and AI-driven solutions for automotive and environmental challenges. Awards and Grants: No scientific awards or funded grants explicitly mentioned in the text. Labs and Teams: Affiliated with the Faculty’s mechanical engineering research groups, collaborating on projects involving vehicle safety, energy efficiency, and advanced materials testing.

Slavica Mačužić Saveljićمشاهده پروفایل

استادیار

• Vehicle Dynamics
• Ergonomics
• Vibration Analysis
• +۳ مورد دیگر

Slavica Mačužić Saveljić serves as an Assistant Professor in the Department for Motor Vehicles and Motors at the Faculty of Engineering, University of Kragujevac, Serbia. Her research focuses on the intersection of automotive engineering, human biomechanics, and vibration dynamics, with particular emphasis on driver comfort and safety systems. Contact details include office B-II-1 and phone +381 34 335990. Her primary research domains encompass: Vehicle Dynamics and Vibration Analysis Ergonomics of Driver-Vehicle Interaction Biomechanical Effects of Whole Body Vibration Neural Network Applications in Comfort Prediction Automotive Safety and Accident Reconstruction Pedestrian and Micro-Mobility Ergonomics Analysis of her 15 most recent publications (2020-2024) reveals a consistent research trajectory centered on neural network modeling of vibration transmission pathways and their physiological impacts. Key trends include the development of predictive models for seat-to-head transmissibility, investigation of vestibular system responses to whole body vibration, and ergonomic optimization for diverse vehicle types including electric scooters and agricultural machinery. Her work demonstrates strong interdisciplinary integration of biomechanics, computational modeling, and automotive engineering. No scientific awards or fellowships were documented in the available sources. Information regarding student advising, research grants, or laboratory affiliations remains unspecified in the provided materials.

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.