جست‌وجوی استاد و پژوهشگر

Lazar Dražetaمشاهده پروفایل

استاد

• Human Resource Management
• Artificial Intelligence Applications
• Organizational Development
• +۳ مورد دیگر

Lazar Dražeta is a Professor at Singidunum University , actively contributing to interdisciplinary research across informatics, human resource management, and cultural studies. He holds a PhD in Plant Biology from Massey University (2003) and graduate degrees in Pomology (University of Belgrade, 1996) and Horticulture (University of Belgrade, 1989). As a member of the academic community, he has co-authored works in business analytics, healthcare education, and organizational development. Education PhD in Plant Biology, Massey University (2003) MS in Pomology, University of Belgrade (1996) BS in Horticulture, University of Belgrade (1989) Research Interests span from Artificial Intelligence applications in HR to organizational development in IT sectors , with notable focus on sustainable pharmacy practices and corporate cultural dynamics . His recent publications examine soft skill development, AI integration in recruitment, and digital safety protocols in online environments. Academic Contributions include books like "Regrutovanje i selekcija ljudskih resursa" (2024) and co-authored works on career development (2019). He participates in conferences like Sinteza and FINIZ, exploring topics from metaheuristic algorithms for harassment detection to leadership coaching effectiveness in corporate settings. His collaborative work with institutions such as Ernst & Young Serbia demonstrates attention to organizational identity, while his earlier research on fruit physiology at Massey University reveals a diverse scholarly trajectory bridging natural sciences and social sciences.

• Autonomous Vehicles
• Software Engineering
• Machine Learning
• +۳ مورد دیگر

Pavle Dakic is affiliated with Singidunum University as a researcher in the Faculty of Informatics and Computing . His work spans multiple disciplines including Software Engineering , Machine Learning , and Autonomous Vehicles . Doctoral studies in Electrical Engineering and Computing at Singidunum University (2015-2024) Doctoral studies in Applied Informatics at Slovak Technical University (2020-2024) Master’s in Contemporary Information Technologies at Singidunum University (2014-2015) His research focuses on CI/CD pipelines , automotive software compliance , and cybersecurity in autonomous systems. He has published extensively on topics like intrusion detection in IoT/IIoT and AI-powered call centers . Recent publications include work on AI integration in business , robotic vehicle sustainability , and metaheuristic optimization for intrusion detection . His collaborations span international institutions and researchers.

Marko Rosićمشاهده پروفایل

دانشیار

• Electrical Drives
• Induction Motors
• Torque Ripple Reduction
• +۵ مورد دیگر

Dr. Marko Rosić is an Associate Professor at the Department of Power Engineering, Faculty of Technical Sciences Čačak, University of Kragujevac, Serbia. Born on July 31, 1984, in Priboj, he completed his education in electrical engineering, graduating with top honors in 2008. He joined the faculty in 2008 as a Teaching Associate and progressed to Assistant Professor (2016) and Associate Professor (2021). He teaches courses including Electrical Drives, Control of Electrical Drives, and Computer-Aided Design in Power Engineering. His research focuses on: Torque ripple reduction in induction motor drives Energy efficiency in electric drives Magnetic field modeling and hysteresis analysis Educational technology for engineering instruction Control algorithms for electrical machines His recent publications (2021-2025) demonstrate a consistent focus on improving control algorithms for induction motors, advancing magnetic material modeling, developing fault detection systems for DC motors, and creating innovative educational tools like GeoGebra applications for engineering education. This work bridges theoretical research and practical implementations in industrial power systems. Scientific Awards: Most Successful Student Award (during studies) Most Successful Graduate Student in Electrical Engineering Young Researcher Best Paper Award (ETRAN 2013) He has led or contributed to multiple national and international projects including: TR 33016: 'Research and implementation of energy efficiency programs for electric drives' (national) 543667-TEMPUS: 'Building Network of Remote Labs' (international) 'Development of Computer-aided Design curriculum for digital competencies' (project coordinator) He develops laboratory setups including electromagnetic load emulators, DC motor test benches, and remote experimentation platforms. As a steering committee member of the ETRAN society and editor assistant for the Serbian Journal of Electrical Engineering, he actively contributes to the academic community.

Lidija Fodorمشاهده پروفایل

استادیار

• Optimization
• Big Data Analytics
• Clustering Algorithms
• +۳ مورد دیگر

Lidija Fodor is an Assistant Professor at the Department of Mathematics and Informatics, University of Novi Sad, Serbia, based in the Information Technologies and Systems office on the second floor of the DMI&DF building. Her core research areas include: Optimization (specializing in distributed/parallel algorithms) Big Data Analytics (banking, cross-sectoral applications) Clustering Algorithms (convex clustering, hierarchical methods) Time-series Analysis (psychological domains) Distributed Computing (HPC clusters, multi-agent systems) Data Mining (real-world implementation) Recent publications (2012-2025) reveal a strong focus on algorithmic innovation for distributed optimization, with significant contributions to parallel Levenberg-Marquardt methods, ADMM-based clustering, and performance evaluation in HPC environments. Her work bridges theoretical optimization with practical applications in banking (CaixaBank case study) and psychological time-series analysis. Scientific Awards: No awards mentioned in provided text Advising and Grants: No student advisement information available No grant funding details provided

• Computer Engineering
• Software Engineering
• Artificial Neural Networks
• +۴ مورد دیگر

Dr. Željko Jovanović is an Assistant Professor at the Department of Computer and Software Engineering , Faculty of Technical Sciences in Čačak , University of Kragujevac , Serbia. He holds a PhD in Electrical Engineering and Computing (2020) from the University of Niš, with a focus on Application of IT in improving the quality of patient transport , and a Diploma Engineer in Computer Science (2008) from the University of Kragujevac. Current roles: Head of Department (2023–present), Coordinator of Undergraduate Studies (2021–present) Teaching areas: Programming basics, Object-oriented programming, Software engineering, Medical informatics (PhD studies) His research focuses on Computer Engineering and Software Engineering , with applications in Medical Informatics , Intelligent Transportation Systems , IoT , and Smart Cities . He has contributed to 15+ publications in journals and conferences, including IEEE Transactions on Intelligent Transportation Systems , Electronics , and Transactions in GIS , emphasizing artificial neural networks , data mining , and comfort assessment in healthcare and transportation contexts. Projects include the national TR32043 initiative on low-power computing systems and the international NeReLa project for remote labs. He has developed technical solutions for thermal comfort monitoring , smart suspension control , and IoT-based systems , and serves on academic committees for software engineering and computer science education.

• Engineering Management
• Quality Management
• Decision Making
• +۵ مورد دیگر

Aleksandar Aleksić is an Associate Professor at the Faculty of Engineering Sciences, University of Kragujevac, specializing in Engineering Management within the Department for Production Engineering. His academic position was officially confirmed on June 9, 2021, and he maintains an active research profile through the SciDAR repository. Dr. Aleksić's research interests span Engineering Management, Quality Management, Decision Making, Risk Assessment, Fuzzy Logic, and Machine Learning Applications. His scholarly work demonstrates a strong focus on integrating advanced computational methods with traditional engineering management practices to solve complex industrial problems. He has made significant contributions to fields such as PFMEA 4.0 maturity assessment, organizational resilience, and multi-criteria decision-making under uncertainty. His recent publications (2024-2025) reveal a clear research trajectory emphasizing the application of fuzzy logic, machine learning, and exact solution methods to engineering management challenges. Notably, his work bridges theoretical advancements with practical industrial applications, particularly in manufacturing systems, asset maintenance, and quality performance enhancement. The consistent publication output across multiple high-impact topics demonstrates his active engagement in cutting-edge research. As a faculty member at one of Serbia's leading engineering institutions, Dr. Aleksić contributes to the academic community through his teaching in production engineering and his research that addresses contemporary challenges in engineering management. His work has implications for both academic theory and industrial practice, particularly in the areas of risk management, process optimization, and decision support systems.

Marko Đapanمشاهده پروفایل

دانشیار

• Industrial Engineering
• Manufacturing Systems
• Occupational Safety
• +۷ مورد دیگر

Dr. Marko Đapan is an Associate Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac. His work focuses on advancing manufacturing systems through Industry 4.0/5.0 integration, occupational safety, and human-robot collaboration. He leads research in neuroergonomics, lean manufacturing, and risk assessment, emphasizing practical applications in SMEs and automotive industries. Key research interests include optimizing assembly line performance, mental workload assessment via EEG, and resilient supply chain design. His projects frequently address challenges in workplace safety compliance, process improvement through robotics, and mitigating human factors risks. Notable contributions include frameworks for neuroergonomic evaluations, risk assessment tools for SMEs, and studies on Industry 4.0 adoption. His work bridges technological innovation with human-centric design principles, particularly in high-risk industrial environments. Publications highlight interdisciplinary approaches combining machine learning with engineering practices, such as deep learning for waste sorting and IoT integration for ergonomic safety monitoring. Current trends in his work emphasize sustainable manufacturing practices aligned with occupational health goals. No scientific awards are listed. His advising and grant activities are not detailed in available texts, though his extensive publication record suggests active research collaboration. He is affiliated with the Faculty of Engineering's laboratories focused on neuroergonomics and human-robot interaction experiments.

Marija Savkovićمشاهده پروفایل

پژوهشگر

• Industrial Engineering
• Manufacturing Systems
• Human-Robot Collaboration
• +۵ مورد دیگر

Marija Savković is a Researcher at the Department for Production Engineering, Faculty of Engineering, University of Kragujevac in Serbia. Her scientific field focuses on Industrial engineering and engineering management, with a strong emphasis on neuroergonomics, human-robot collaboration, and Industry 4.0 implementation. She holds a position in the Department for Production Engineering, contributing to advancements in manufacturing systems and workplace safety. Her research interests include optimizing industrial processes through robotics and automation, assessing mental workload in assembly tasks using EEG, and enhancing workplace safety via IoT and AI technologies. She has conducted extensive work on ergonomic assessments in human-robot collaboration environments, emphasizing both physical and cognitive aspects of operator performance. Her recent studies explore frameworks for neuroergonomic evaluation, comparative analyses of agile project management tools, and the integration of Industry 4.0 technologies in SMEs. Key projects involve developing robotic stations for fruit and vegetable processing, predictive demand analysis in automotive industries, and evaluating safety compliance using deep learning object detection. Marija collaborates on modular industrial workstations for neuroergonomics research and has contributed to national radon surveys in Serbia. Her work bridges advanced technologies with practical industrial challenges, aiming to improve operational efficiency and worker well-being in manufacturing sectors.

Jovanka Lukićمشاهده پروفایل

استاد

• Automotive Engineering
• Vehicle Dynamics
• Ergonomics
• +۳ مورد دیگر

Jovanka Lukić is a Professor and Chair of the Department for Motor Vehicles and Engines at the Faculty of Engineering, University of Kragujevac. Her research focuses on automotive engineering, vehicle dynamics, and ergonomics with a strong emphasis on environmental impact and sustainable transportation solutions. She leads studies on brake wear pollution, electric vehicle optimization, and driver comfort under vibration exposure. Her academic contributions span over three decades, addressing technical challenges in vehicle design, energy systems, and human-machine interaction. Key areas include: (1) Development of predictive models for brake wear particle emissions, (2) Optimization of vehicle suspension and transmission systems, (3) Application of AI/ML for comfort assessment, and (4) Sustainable materials in automotive manufacturing. She holds a prominent position within the Department’s Motor Vehicles and Motors unit, overseeing cutting-edge research facilities including specialized dynamometers and vibration testing laboratories. Her work integrates mechanical engineering principles with environmental science to address global transportation challenges.

Dragan Rakićمشاهده پروفایل

دانشیار

• Applied Mechanics
• Structural Analysis
• Finite Element Method
• +۵ مورد دیگر

Dragan Rakić is an Associate Professor at the Department of Applied Mechanics and Automatic Control, Faculty of Engineering, University of Kragujevac, Serbia. His research focuses on structural safety assessment, material modeling, and computational mechanics. He specializes in dam safety analysis, finite element method applications, and tribomechanical systems. His work integrates machine learning and artificial intelligence for predictive modeling in engineering systems. Key research areas include structural integrity assessment, geotechnical modeling of embankment dams, and failure analysis of civil infrastructure. He contributes to national guidelines for dam safety in Serbia and develops user interfaces for constitutive model parameter identification. His projects address resilience of water resource systems under hazardous events, combining system dynamics and neural networks. Academically, he is affiliated with the Department for Applied Mechanics and Automatic Control, collaborating on interdisciplinary projects involving mechanical, civil, and environmental engineering. His publications span dam stability analysis, material behavior modeling, and failure assessment methodologies.

• Control Systems
• Automatic Control
• Signal Processing
• +۳ مورد دیگر

Станиша Перић serves as an Associate Professor in the Department of Automation at the Faculty of Electronic Engineering, University of Niš. His academic appointments and research activities are centered on advanced control systems and signal processing within Serbia's prominent technical institution. His educational foundation includes: BSc in Automation (2009, Faculty of Electronic Engineering, University of Niš) PhD in System Control (2016, Faculty of Electronic Engineering, University of Niš) Perić's research spans Control Systems , Signal Processing , and Automotive Control , with emphasis on sliding mode control, neural network integration, and orthogonal function applications. His work bridges theoretical control engineering with practical automotive implementations, particularly in anti-lock braking systems. Recent publications demonstrate a clear trajectory toward adaptive neural control architectures and real-time system optimization. With 21 impact-factor journal publications, his research output shows consistent focus on digital control algorithms and filter design. Current involvement in 6 active projects (2 national, 4 international) underscores his collaborative research profile. Dr. Perić actively supervises graduate students in control engineering while securing research funding through national and international grants. His laboratory work within the Department of Automation focuses on experimental validation of control algorithms using automotive test benches and real-time simulation environments.

• Computational Electromagnetics
• Antenna Design
• TLM Modeling
• +۱ مورد دیگر

Nebojša S. Dončov is Full Professor at the Department of Telecommunications, Faculty of Electronic Engineering, University of Niš. As Vice-Dean for Science and IEEE Senior Member, he leads research in computational electromagnetics with applications in antenna design and electromagnetic compatibility. His TLM modeling techniques have been validated internationally. Education & Affiliations: PhD in Telecommunications (2002) Corresponding Member of Academy of Engineering Sciences of Serbia IEEE MTT/AP/EMC Society Senior Member Research Focus: Pioneers cylindrical TLM methods for: Conformal antenna analysis EM propagation modeling On-body communication systems Machine learning-assisted EM simulation Publication Trends: Recent IEEE Transactions papers demonstrate advances in neural network applications for antenna optimization and experimental validation of novel simulation techniques. Research consistently bridges theoretical electromagnetics with practical wireless system design. Awards & Projects: Aleksandar Marinčić Award (2017) URSI Young Scientist Award (2002) NATO SPS Project Director: UAV-Based Explosive Detection Royal Society projects on sensor networks Teaching & Service: Authors textbooks on antenna theory and simulation techniques. Chairs IEEE TELSIKS conferences and coordinates Erasmus+ collaborations with European technical universities.

• Telecommunications
• RF Amplifier Design
• Antenna Modeling
• +۳ مورد دیگر

Aleksandar S. Atanasković is a Lecturer at the Faculty of Electronic Engineering within the University of Niš , affiliated with the Department of Telecommunications . His academic career has been dedicated to advancing telecommunications engineering through both theoretical and applied research. PhD in Telecommunications (2015) Master's Degree in Telecommunications (2004) Bachelor's Degree in Electronics and Telecommunications (1997) His research focuses on telecommunications and RF engineering, with a specialization in amplifier linearization techniques, computational modeling of antennas, and deep learning applications for sensors. His work addresses challenges in wireless communication systems, including: Digital injection methods for Doherty amplifiers Even-order nonlinear signal processing Cylindrical TLM method for antenna analysis Soft sensor development using neural networks Near-field measurement calibration Broadband amplifier optimization The trends in his publications reflect expertise in microwave engineering, signal processing, and machine learning integration. His work spans theoretical modeling and experimental validation. No scientific awards or fellowships are explicitly mentioned in the provided text.

• Environmental Chemistry
• Air Pollution
• Toxicology
• +۴ مورد دیگر

Gordana Jovanović is a researcher at Singidunum University with expertise in environmental chemistry and pollution analysis. She holds a PhD in Environmental Chemistry from the University of Belgrade (2012–2015), followed by postdoctoral research at the Institute for Medical Research and Occupational Health in Zagreb (2017–2018). Her research focuses on persistent organic pollutants (POPs), polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs), with applications in air quality, indoor/outdoor environmental fate, and human health risk assessment. She employs advanced methods like machine learning (XGBoost, SHAP) and metaheuristics for predictive modeling of pollutant behavior. Key contributions include studies on PCBs and OCPs in breast milk, fish, and soil-plant-air systems, as well as biomonitoring using mosses and tree leaves. Her work bridges environmental chemistry, toxicology, and AI-driven analytics, addressing global challenges in pollution management and public health.

• Operations Research
• Optimization
• Electric Vehicle Scheduling
• +۳ مورد دیگر

Raka Jovanović is a Researcher at Singidunum University , affiliated with the Faculty of Informatics and Computing . His work bridges theoretical algorithm design with practical applications in transportation, energy systems, and optimization. Bachelor's, Matematički fakultet - Beograd (2002) Postgraduate, Matematički fakultet - Beograd (2007) Doctorate, Matematički fakultet - Beograd (2016) His research focuses on metaheuristics and matheuristics for complex optimization problems, including: Knapsack problems with penalty constraints Electric vehicle charging infrastructure planning Graph-based combinatorial optimization Energy management in extreme climates Integration of machine learning with traditional algorithms Recent publications demonstrate a strong emphasis on Fixed Set Search as a unifying methodology across diverse domains. Journal articles in 2024-2025 explore its application to: Maximum Diversity Problem Multidimensional knapsack Charging station placement Multi-objective optimization Conference papers from 2023-2024 highlight collaboration with international teams on: EV fleet scheduling Desert climate agricultural energy systems Max-Cut and disjoint dominating sets problems Waterway transport prediction models