جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Optimization Algorithms
• +۴ مورد دیگر

Nebojša Bačanin Džakula is an academic affiliated with Singidunum University's Faculty of Mathematics, specializing in Computer Science. He earned his PhD in 2015 with a thesis on improving swarm intelligence metaheuristics for global optimization. His research focuses on AI-driven solutions for cybersecurity, energy forecasting, and optimization algorithms. He has authored/co-authored books on cloud computing and web programming. His work bridges metaheuristics with machine learning, addressing challenges in IoT security, renewable energy prediction, and healthcare diagnostics. He actively contributes to conferences like Sinteza and IEEE events, emphasizing practical applications of AI and optimization in real-world scenarios. Education: Completed doctoral studies at the Faculty of Mathematics (2009–2015). Extensive industry certifications include Microsoft, CompTIA, and Oracle credentials, enhancing his technical expertise. Research Interests: Develops hybrid models combining metaheuristics (e.g., PSO, GA) with deep learning for tasks like intrusion detection, price forecasting, and medical diagnostics. Specializes in optimizing neural networks and feature selection using advanced algorithms. His work often addresses societal challenges in sustainability, cybersecurity, and healthcare. Recent Publications: Focus on AI-driven solutions for IoT security, renewable energy prediction, and medical diagnostics (e.g., Parkinson’s detection via LSTM networks). His articles appear in prestigious journals like Engineering Applications of Artificial Intelligence and Applied Soft Computing.

• Mathematics Education
• Interactive Multimedia in Teaching
• Educational Technology
• +۵ مورد دیگر

Marina Milovanović is a Professor at the University of Singidunum, Faculty of Informatics and Computing, Department of Mathematics. She holds dual doctoral degrees from the Faculty of Science, University of Kragujevac (Department of Mathematics, 2014) and Faculty of Entrepreneurial Business, Union University (2008), along with Master's and Bachelor's degrees from the Faculty of Mathematics, University of Belgrade (2000-2005 and 1995-2000 respectively). Faculty of Science, University of Kragujevac, Department of Mathematics (PhD, 2014) Faculty of Entrepreneurial Business, Union University (PhD, 2008) Faculty of Mathematics, University of Belgrade (Master's, 2000-2005) Faculty of Mathematics, University of Belgrade (Bachelor's, 1995-2000) Svetozar Marković High School, science and mathematics major (1991-1995) Professor Milovanović specializes in Mathematics Education and Educational Technology, with particular expertise in interactive multimedia applications for teaching mathematics. Her research consistently bridges theoretical mathematics with practical educational technology solutions, evolving from traditional multimedia approaches to incorporating cutting-edge AI and machine learning techniques. She has authored multiple books including 'Interactive multimedia in mathematics teaching' (2015) and collections of solved mathematics problems for entrance exams. Her recent publication record through 2025 demonstrates active engagement in interdisciplinary research, particularly at the intersection of educational technology, artificial intelligence, and practical applications in fields ranging from software engineering to medical diagnostics. Her work shows a clear trajectory from foundational educational technology research toward more sophisticated AI-enhanced learning systems. Professor Milovanović has made significant contributions to semantic web applications in education, particularly through Moodle LMS enhancements, and has explored SCADA applications in industrial contexts. Her collaborative research spans multiple countries and institutions, reflecting an international scholarly network. She has extensive experience developing computer tools for engineering education and has published on diverse topics including petroleum industry processes, environmental management, and financial mathematics. Her work demonstrates consistent application of computational approaches to solve domain-specific problems across multiple disciplines.

Miloš Rackovićمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Databases
• +۴ مورد دیگر

Miloš Racković serves as a full Professor in the Department of Mathematics and Informatics at the University of Novi Sad, Serbia. He maintains active academic engagement through the Laboratory for the development of information systems, with his office located in the Information technologies and systems office (DMI&DF) on the second floor, room 49. Contact is available via telephone (485)-2868 or email rackovic@dmi.uns.ac.rs, and his personal website (http://www.is.pmf.uns.ac.rs/rackovicm/) provides additional resources. His research spans foundational and applied computer science, with seminal contributions in fuzzy database systems including PFSQL query language development and prioritized fuzzy logic for relational databases and XML. He has pioneered deep learning methodologies through innovative classification techniques using negative and missing features in convolutional neural networks. Additional expertise includes high-performance computing implementations of Lattice Boltzmann methods using OpenCL, robotics (symbolic modeling and trajectory planning), and blockchain applications for Industry 4.0 production processes. His sports analytics work applies neural networks to basketball player and referee movement analysis. Analysis of his 2012-2025 publications reveals a strategic evolution toward interdisciplinary applications, particularly in industrial transformation (blockchain-enabled traceability) and sports analytics. His work consistently bridges theoretical computer science with practical implementations, demonstrating increasing focus on real-world problem solving while maintaining strong foundations in database theory and computational methods. Professor Racković leads the Laboratory for the development of information systems, which focuses on advancing information system methodologies through formal modeling extensions (including Petri net innovations) and practical implementations for uncertainty management. The laboratory's work spans from foundational research in fuzzy logic systems to applied projects in high-performance computing and blockchain integration, fostering innovation in information technology development.

• Control Systems
• Machine Learning
• Robotics
• +۶ مورد دیگر

Marko Tanasković is a researcher at Singidunum University's Faculty of Informatics and Computing, specializing in control systems, robotics, and electrical engineering. He holds a PhD from ETH Zurich (2015) in Information Technology and Electrical Engineering, following degrees from University of Belgrade (BEng, 2009) and ETH Zurich (MEng, 2011). His research focuses on adaptive control systems, machine learning applications in engineering, and sensorless motor control. Key contributions include: Development of predictive algorithms for traffic systems and industrial automation Innovations in rotor orientation determination for PMSM motors Integration of AI in fraud detection and building climate control Recent work includes a 2024 study on wearable health monitoring devices and a 2022 paper on drone forensics. He has authored/co-authored over 15 peer-reviewed articles and holds patents in motor control technologies. Current affiliations include Singidunum University's Department of Electrical Engineering and Collaboration with ETH Zurich alumni networks. Active in international conferences such as Sinteza and IEEE events.

Aleksandar Jevremovićمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Cybersecurity
• Internet of Things (IoT)
• +۶ مورد دیگر

Aleksandar Jevremović is a Full Professor at the Faculty of Informatics and Computing, Singidunum University (Belgrade, Serbia), and holds multiple academic and professional roles. He is the Serbian representative at the UNESCO IFIP Technical Committee on Human-Computer Interaction since 2018. He has served as Vice-Dean of his faculty (2015–2018) and held visiting professorships at institutions like Ss. Cyril and Methodius University (North Macedonia) and Tallinn University (Estonia). His research focuses on cybersecurity, IoT, AI, and e-learning innovation. Education and Affiliations: External Researcher at the Mathematical Institute of the Serbian Academy of Sciences and Arts Visiting Scholar at Cyprus Interaction Lab (Cyprus University of Technology) Alumni/Postdoc Researcher at Tallinn University's HCI Group Member of IEEE and the Informatics Association of Serbia Research Interests: Jevremović’s work spans cybersecurity (e.g., intrusion detection, secure IoT protocols), human-computer interaction (HCI), AI-driven education tools, and neurotechnological applications like EEG-based assessment systems. He emphasizes practical solutions for digital safety, such as children’s online protection and cryptographic key generation from biometric data. Grants and Projects: Member of the External Advisory Committee for the EU-funded ONTOCHAIN project (2022–2023) Mentor for training schools like AAPELE Training School and NET4Age-Friendly initiatives Trainer in IoT, cybersecurity, and health promotion programs across Europe Labs and Teams: He collaborates with interdisciplinary teams on projects like CASPER (Children Agents for Secure and Privacy Enhanced Reaction) and led the development of WIDE, a collaborative web development education platform.

• Mechanical Engineering
• Machine Design
• Tribology
• +۴ مورد دیگر

Miloš Matejić serves as an Associate Professor at the University of Kragujevac's Faculty of Engineering Sciences, within the Department of Mechanical Constructions and Mechanization. His academic position involves active research and teaching in mechanical systems design. Research interests center on advanced mechanical engineering topics including: Cycloid drive efficiency optimization and stress analysis Tribological testing methodologies and material interactions Computational modeling of gear systems using FEM Parametric design automation for mechanical components Composite materials performance in dynamic applications Recent publications demonstrate strong focus on experimental validation of cycloid reducers, novel tribometers, and material optimization. No awards, student advisories, or grant activities are documented in available sources. Institutional collaboration occurs through the Faculty of Engineering Sciences' laboratories and research centers.

• Environmental Physics
• Atmospheric Science
• Air Pollution Monitoring
• +۳ مورد دیگر

Mirjana Perišić is an Associate Professor at Singidunum University and a Senior Research Associate at the Institute of Physics, University of Belgrade. She holds a PhD in Experimental Physics (2016) from the University of Belgrade. Her expertise spans environmental physics and chemistry, with a focus on atmospheric science, air pollution monitoring, and AI-driven environmental data analysis. She has contributed to projects like Horizon 2020 and COST Actions, addressing air quality, climate change, and environmental health. Her research employs statistical modeling, machine learning, and receptor modeling techniques. Education: High School in Čačak (Natural Sciences), BSc in General Physics (University of Belgrade, 1998–2007), PhD in Atomic Physics (University of Belgrade, 2007–2016). Research Interests: Her work emphasizes AI applications in environmental fate analysis, particulate matter (PM) dynamics, polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). She explores the impact of environmental settings on indoor/outdoor pollution and leverages explainable machine learning (e.g., XGBoost, SHAP) for predictive modeling. Publications: Over 10 peer-reviewed articles since 2014, focusing on air pollution sources, climate change implications, and AI-based frameworks for environmental monitoring. Recent work addresses toluene behavior, PAHs distribution, and post-pandemic pollution trends. Awards: None explicitly mentioned in the text. Advising/Grants: No advising students listed. Grants and policy contributions include air quality management plans and collaborative projects with international partners. Labs/Teams: Active in the Institute of Physics, University of Belgrade, and interdisciplinary teams at Singidunum University focusing on environmental data science.

• Separation Methods
• Liquid Chromatography
• Chemometrics
• +۳ مورد دیگر

Jelena Dj. Trifkovic serves as Full Professor in the Department of Analytical Chemistry at the Faculty of Chemistry, University of Belgrade, where she was promoted from Assistant Trainee (2003) through Associate Professor (2019) to her current position (2024). She concurrently holds leadership roles as Vice-Dean for Teaching and Secretary of the Serbian Chemical Society since 2020. Her academic foundation includes undergraduate (1995-2001), Master's (2003-2006), and Doctoral studies (2011-2013) in Chemical Sciences, all completed at the University of Belgrade's Faculty of Chemistry. Trifkovic's research centers on chromatographic separation techniques and chemometrics for food authenticity verification, particularly focusing on bee products like honey and propolis. Her methodology integrates advanced analytical instrumentation with multivariate data analysis to establish quality control protocols and detect adulteration, significantly contributing to food safety standards in the Balkan region. Analysis of her publication record reveals consistent innovation in HPTLC image analysis and multi-technique approaches (GC, LC, electrochemical methods) for natural product authentication. Her work demonstrates increasing international collaboration, with recent publications emphasizing standardized protocols for regulatory compliance and health benefit validation of food components. She actively secures competitive research funding, including Horizon Europe's PFAStwin project (2022-2025) and UNDP-funded valorization initiatives (2023-2024), alongside leadership in bilateral projects on bee product authentication with Croatian and Slovenian institutions. Trifkovic maintains strong laboratory networks through her affiliation with Slovenia's National Chemical Institute Food Chemistry Laboratory and coordinates multiple university committees focused on curriculum development and quality assurance in chemical education.

Đorđević Markoمشاهده پروفایل

دانشیار

• Computational Biology
• Systems Biology
• Infectious Diseases
• +۷ مورد دیگر

Marko Djordjevic is an Associate Professor at the Faculty of Biology, University of Belgrade. His research spans computational biology of infectious diseases, bacterial immune systems (CRISPR/Cas and restriction-modification systems), and quantitative understanding of infection progression with applications to SARS-CoV-2 and computational physics of quark-gluon plasma. Diploma in Physics, Faculty of Physics, University of Belgrade, Serbia. PhD in Biophysics and Bioinformatics, Department of Physics, Columbia University, USA. Postdoctoral training at the Mathematical Biosciences Institute, Ohio State University, USA. Djordjevic's research focuses on nonlinear regulatory dynamics of bacterial immune systems, their role in horizontal gene transfer, and modeling infection progression under social mitigation measures. His secondary interest in computational physics examines quark-gluon plasma dynamics via high-p⊥ observables and tomography. His recent publications address CRISPR/Cas regulation, restriction-modification systems, and SARS-CoV-2 transmissibility drivers. Grants from the Serbian Ministry of Science, Science Fund of Serbia, EU Marie Curie IRG, and Swiss National Science Foundation support his work.

Danijela Tadićمشاهده پروفایل

استاد

• Production Engineering
• Industrial Engineering
• Decision-Making Models
• +۵ مورد دیگر

Danijela Tadić is a Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac, Serbia. Her primary research focuses on decision-making models under uncertainty, manufacturing process optimization, failure mode analysis, and sustainable recycling technologies in the automotive and industrial sectors. She holds a leadership role in the Faculty of Engineering, contributing to academic governance and curriculum development. Her scientific work integrates fuzzy logic systems, multi-criteria decision-making (MCDM), and optimization algorithms to address complex engineering challenges. Notable areas include risk management in supply chains, quality improvement in manufacturing processes, and environmental impact assessment of recycling equipment. She has collaborated on projects evaluating organizational resilience, strategic failure management, and resource planning in SMEs. Prof. Tadić’s publications emphasize practical industrial applications, such as PFMEA integration with fuzzy decision tools, cloud platform selection frameworks, and electric vehicle evaluation models. Her work bridges theoretical advancements in fuzzy set theory with real-world manufacturing and environmental sustainability problems. She actively participates in academic and professional networks, contributing to conferences and journals in production engineering and industrial systems. Her expertise spans project lifecycle management, lean manufacturing, and the evaluation of recycling technologies for end-of-life vehicles (ELVs).

• Information Systems
• Industrial Management
• Environmental Engineering
• +۵ مورد دیگر

Prof. Dr. Miloš Ž Papić is a Full Professor at the Faculty of Technical Sciences Čačak , University of Kragujevac, Serbia. He serves as a City Councilor in Čačak for Education, Science, and Culture, spearheading initiatives like the Čačak Culture Strategy (2023-2027) and launching the Čačak Culture Portal . Education: BSc, MSc, and PhD in Industrial/Engineering Management from University of Kragujevac institutions Research Interests: Information Systems, Environmental Management, Entrepreneurial Education, and Multi-Criteria Decision Making (MCDM) His research spans interdisciplinary applications of IT in education, tourism, and environmental protection, with recent work on: Digital dialogue systems in classrooms Soil contamination analysis using MCDM Cheating behavior in academic settings Beer tourism market analysis AI in educational outcomes prediction Scientific Contributions include over 90 publications, with 15 recent articles focusing on IT integration in tourism (2023-2024), municipal waste management (2024), and educational technologies (2022). Notable collaborations involve partnerships with Dušan Garabinović on tourism analytics and Marija Blagojević on environmental modeling.

Dragan Tasićمشاهده پروفایل

استاد

• Power Transmission
• Power System Components
• Power Cable Technology
• +۶ مورد دیگر

Prof. Dr Dragan Tasić is a distinguished Professor at the Power Engineering Department of the Faculty of Electronic Engineering, University of Niš, Serbia. With decades of academic and research experience, he has established himself as a leading expert in power transmission, power system components, and electrical cable technology. His work spans theoretical research, practical applications, and educational contributions to the field of electrical engineering. Dr. Tasić's research interests focus on power transmission systems, electrical cable technology, relay protection, power system analysis, and grounding systems. His work particularly emphasizes thermal aspects of power cables, electrical energy losses in distribution networks, and innovative solutions for improving cable performance. He has pioneered research on thermal management of underground cables, including the use of hydronic asphalt pavements and cool pavements to eliminate hot spots and increase cable ampacity. His publication record demonstrates consistent productivity with numerous books, journal articles, and conference papers spanning over three decades. Recent research (2019-2023) shows continued innovation in areas such as thermal aging management of underground cables, photovoltaic system integration, and optimization of distribution networks with energy storage. His work frequently employs advanced computational methods including Finite Element Method (FEM) and hybrid optimization algorithms. Dr. Tasić has led and participated in numerous significant research projects funded by Serbian government agencies, focusing on energy efficiency, power system optimization, and technological improvements in electrical distribution networks. His work has practical applications in the Serbian power industry and contributes to international knowledge in electrical engineering. As an educator, Dr. Tasić has contributed to curriculum development and has authored multiple textbooks that are widely used in electrical engineering education in Serbia. His teaching focuses on core power engineering subjects including power transmission, electrical networks, and power cable technology.

• Manufacturing Engineering
• Electrical Discharge Machining
• Surface Roughness Optimization
• +۷ مورد دیگر

Anđelko Aleksić is an Assistant Professor at the Chair of Machining, Faculty of Technical Sciences, University of Novi Sad. His work focuses on advanced machining processes and Industry 4.0 integration. Current Position: Assistant Professor (2025–Present) Previous Positions: Assistant Professor (2019–2025), Teaching Associate (2018–2019) Research interests span Electrical Discharge Machining (EDM) , surface roughness optimization, tool wear analysis, and Industry 4.0 applications. His work incorporates fuzzy logic , genetic algorithms , and other optimization techniques for machining processes. Recent publications analyze powder-mixed EDM for titanium alloys and ceramics, plasma arc cutting quality , and Industry 4.0 advancements . Themes include defect layer reduction, energy-efficient machining, and adaptive control systems. He contributes to the Chair of Machining department through research and teaching activities, emphasizing modern manufacturing technologies.

Nikola B. Dankovicمشاهده پروفایل

استادیار

• Systems Management
• Dynamical Systems Modeling
• Signal Processing
• +۳ مورد دیگر

Nikola B. Dankovic is an Assistant Professor at the Faculty of Electronics in Niš, part of the University of Niš, within the Department of Automation. He earned his PhD in Systems Management from the same faculty in 2018, following a Master's degree from the Faculty of Electronics' Department of Telecommunications in 2009. His academic career began with an appointment as an Assistant Professor in 2013, reaffirmed in 2020. Research interests include dynamical systems modeling, orthogonal filter design, control systems, and thermodynamic applications. He has contributed to fields like DPCM system analysis, nonlinear MIMO control, and cascade filter optimization. His work frequently integrates mathematical techniques such as Monte Carlo methods and bilinear transformations. Publications span journals like International Journal of Electronics , Acta Polytechnica Hungarica , and Filomat , focusing on theoretical and applied aspects of signal processing and systems engineering. He collaborates on national and international research projects, though no specific awards are noted. Contact information includes his email nikola.dankovic@elfak.ni.ac.rs and institutional address in Niš.

• Computer Networks
• Telecommunications
• Machine Learning
• +۴ مورد دیگر

Živko Bojović is affiliated with Singidunum University, holding a doctoral degree in Telecommunications and Signal Processing from the University of Novi Sad. His career includes roles as an engineer and manager in telecommunications companies like Telekom Srbija and PTT Serbia. He has extensive experience in academic publishing, with monographs on network technologies and textbooks on software-defined networking (SDN) and IoT applications. His research focuses on cybersecurity, machine learning applications in healthcare, smart government systems, and network virtualization. Education: PhD in Telecommunications (2011), Postgraduate studies in Telecommunications (2000-2001), Bachelor’s in Electronics with Telecommunications (1986-1992). He also completed high school in Peć with a mathematical focus. Research Interests: He explores advanced networking technologies including SDN, 5G/6G networks, IoT security, and educational technology innovations. His work bridges theoretical advancements with practical implementations in healthcare diagnostics and public sector digitization. Recent studies include applying machine learning to predict thrombosis and thyroid cancer metastasis, reflecting his interdisciplinary approach. His articles collectively highlight trends in smart systems (e.g., government services, energy grids) and network security, with frequent contributions to journals like Computer Applications in Engineering Education and Journal of Network and Systems Management . The Wiley Top Cited Article award (2020-2021) recognizes his impactful work on rapid transition to distance learning during crises. Prof. Bojović holds IEEE membership and sits on editorial boards for journals like Inventi Impact: Software Engineering . He actively participates in EU Horizon projects focusing on 6G privacy and smart city analytics.