Find Academic Supervisors

• Information Technology Governance
• Cybersecurity
• Blockchain
• +8 more

Dalibor Radovanović is a researcher at Singidunum University , affiliated with the Faculty of Business Informatics . His work spans cybersecurity, blockchain technologies, and their applications in business and IoT systems. Education: Doctoral Dissertation (2016, Singidunum University) Master's & Basic Studies (Faculty of Business Informatics) Secondary Education: ETŠ Nikola Tesla Research Interests include: Security frameworks for IoT and blockchain integration Smart card and wireless network vulnerabilities E-governance and corporate IT audit methodologies Machine learning applications in cybersecurity Environmental performance optimization in agribusiness Publication Trends reveal a focus on blockchain (2022), cybersecurity (2009-2022), and IT governance (2010-2017). His work bridges theoretical analysis with practical implementations in Serbia's digital economy. Collaborations with scholars like Marko Šarac and Saša Adamović highlight interdisciplinary approaches to securing financial systems, educational institutions, and industrial IoT applications.

• Artificial Intelligence
• Machine Learning
• Optimization Algorithms
• +4 more

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.

• Project Management
• Operations Management
• Retail Logistics
• +3 more

Goran Avlijaš is a researcher affiliated with Singidunum University in Belgrade, specializing in project management, operations research, and retail logistics. He holds a Doctorate in Engineering Management (2011–2016) from Singidunum University, a Master’s in Project Management (2008–2009) from the Faculty of Organizational Sciences, and a Bachelor’s in Management (2003–2007) from the same institution. His research focuses on optimizing project schedules through methods like Earned Value Management and Monte Carlo Simulation, analyzing supply chain efficiency, and exploring gig economy impacts on well-being in Balkan countries. Key research areas include: Project Management Innovation: Developing risk analysis tools (e.g., Event Chain Methodology) and applying earned value metrics to construction projects. Retail Operations: Investigating automated replenishment systems and inventory management challenges in retail environments. Social-Economic Dynamics: Studying gig economy effects on workforce well-being and regulatory impacts on entrepreneurship. His work spans 30+ peer-reviewed articles and conference papers, including contributions to Management , Sustainability , and Frontiers in Psychology . He co-authored textbooks like Project Management and Entrepreneurship for Singidunum University’s curriculum. Active in academic events such as Sinteza and FINIZ conferences, he bridges theoretical research with practical industry applications.

Blerim RexhaView profile

Professor

• Cybersecurity
• Blockchain Technology
• Machine Learning
• +5 more

Prof. Blerim Rexha is a full professor at the University of Prishtina's Faculty of Electrical and Computer Engineering, Kosovo. With a Ph.D. in Computer Engineering from Vienna University of Technology (2004), he has led research in cybersecurity, blockchain, machine learning, and electronic voting systems. His teaching portfolio includes data, computer, and internet security courses. Education : Ph.D. in Computer Engineering (Vienna), Electrical Engineer MSc (Prishtina), specialized certifications in software engineering, biometrics, and .NET programming. His research spans cybersecurity (DDoS mitigation, face authentication attacks), blockchain applications (electronic voting bridges, transaction privacy), and machine learning integration (boosted trees for intrusion detection, LSTM for vulnerability scanning). He has contributed to cloud security through novel encryption methods and AI-driven attack detection. Recent publications focus on energy efficiency in cloud vs on-premises systems, XGBoost/CatBoost/LightGBM comparisons for network security, and blockchain bridges for e-voting. His work has addressed privacy preservation in video data, SMS encryption, and eID card pseudo-profiles. Awards include the 2024 Marin Barleti Prize for academic contributions and Best Paper Awards in election security (2015) and Kosovo website vulnerabilities (2013). Honors : Marin Barleti Prize (2024) Cyber Security Ambassador (2018) ICT Academician of the Year (2016) Best Paper Awards (2015, 2013) As academic advisor to the KosovaCyberTeam , he mentors students like Korab Keqekolla and Abian Morina. His leadership extends to Kosovo's Cyber Security State Training Center curriculum development and jury roles in Albanian ICT Awards .

• Control Systems
• Signal Processing
• Neuro-Fuzzy Systems
• +3 more

Dragan S. Antic is a Professor at the Department of Automation, Faculty of Electronics, University of Niš. He earned his PhD in Automation from the same institution in 1994, following a Master's (1991) and Bachelor's (1987) degree in the same field. His research focuses on control systems, signal processing, and neuro-fuzzy systems, with a strong emphasis on sliding mode control, orthogonal function-based modeling, and adaptive neural networks. He has published 51 papers in journals with impact factors and currently participates in 2 national and 8 international research projects. Key research areas include dynamic system modeling, quasi-orthogonal filters, and finite-time stability analysis of time-delay systems. His work often integrates mathematical techniques with engineering applications, such as anti-lock braking systems and PID control optimization. Contact details include his office at Aleksandra Medvedeva 4, Niš, and the email dragan.antic@elfak.ni.ac.rs. Professional contributions include foundational research in endocrine neural networks and low-pass filter design, with notable publications in journals like Electronics Letters and Journal of the Franklin Institute . His efforts bridge theoretical advancements with practical engineering solutions in automation and control.

• Functional Analysis
• Generalized Functions
• Integral Transforms
• +7 more

Stevan Pilipović is a Full Professor at the Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad. His research spans generalized functions, integral transforms, pseudodifferential operators, and fractional calculus. He holds a PhD in Mathematics from the University of Novi Sad (1979) and has led key academic roles, including editorships in journals like Integral Transforms and Special Functions and Pseudo-Differential Operators and Applications . Education: BSc in Mathematics, University of Novi Sad (1973) MSc in Mathematics, University of Belgrade (1977) PhD in Mathematics, University of Novi Sad (1979) Professional Activities: Leader of the Generalized Product and Integral Transformations seminar Editorial roles in multiple international journals Supervisor of numerous research projects in functional analysis and mathematical physics Research Interests: Pilipović’s work emphasizes microlocal analysis, fractional calculus in viscoelasticity, and stochastic PDEs. Key contributions include monographs on generalized functions and Fourier analysis, with over 400 publications. His research bridges pure mathematics (e.g., ultradistribution theory) and applications in mechanics and signal processing. Grants and Collaborations: Active in international collaborations, including projects on fractional Zener models and stochastic dynamics. His work frequently intersects with engineering and physics, addressing real-world problems in material science and wave propagation.

Zoran J. StankovicView profile

Professor

• Antenna Design and Optimization
• Direction of Arrival (DoA) Estimation
• Artificial Neural Networks in Electromagnetics
• +7 more

Zoran J. Stankovic is a Full Professor at the Faculty of Electronics, University of Niš, Serbia, in the Department of Telecommunications. He has been an integral part of the institution since earning his PhD in 2007, progressing from Assistant to Associate Professor (2020) and Full Professor (2024). He is actively involved in research, education, and academic leadership. Education: PhD in Telecommunications, Faculty of Electronics, University of Niš (2007) Master's in Telecommunications, Faculty of Electronics, University of Niš (2002) Bachelor's in Electronics and Telecommunications, Faculty of Electronics, University of Niš (1994) His research focuses on applying artificial neural networks to solve complex problems in electromagnetics and wireless systems. Key areas include antenna design optimization , direction-of-arrival (DoA) estimation , microwave cavity modeling , and smart textile antennas . His work bridges machine learning with electromagnetic theory, enabling efficient and adaptive RF system design. The analysis of his recent publications reveals a strong trend in using deep and hybrid neural networks for electromagnetic modeling and signal processing. His research emphasizes real-world applications such as wearable antennas, mobile source tracking, and intelligent antenna systems, often published in high-impact IEEE and Wiley journals. Scientific Awards: Commemorative Plaque from the Yugoslav Society for Microwave Techniques and Technologies (2005) for outstanding scientific results in microwave engineering Advising and Grants: While specific students are not listed, he has supervised numerous academic works. He has participated in 17 research projects (13 national, 4 international including DAAD, NATO, COST) and 8 educational development projects (including ERASMUS+, TEMPUS, WUS). These reflect sustained funding and academic collaboration. Labs and Teams: He is the founder and head of the Laboratory for Antennas and Propagation at the Faculty of Electronics, Niš. He is actively involved in organizing and leading the international conferences TELSIKS and ICEST , serving on their program and organizational committees, demonstrating strong leadership in the academic community.

• Mathematics Education
• Interactive Multimedia in Teaching
• Educational Technology
• +5 more

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.

• Microbiology
• Food Microbiology
• Biochemical Engineering
• +5 more

Prof. Dr. Maja Vukašinović-Sekulić is a Full Professor at the Department of Biochemical Engineering and Biotechnology at the Technical-Metallurgical Faculty, University of Belgrade. She was elected to her current professorial position on October 16, 2023. Her office is located in the large TMF building, office 70, and she can be reached at vukasinovic@tmf.bg.ac.rs or by phone at 011/3303845 ext. 845. Professor Vukašinović-Sekulić specializes in Microbiology, Food Microbiology, Biochemical Engineering, and Biotechnology, with a particular focus on antimicrobial research and fermentation technology. Her teaching portfolio includes courses such as Microbiology and Microbiological Food Analytics, Genetics, Industrial Microbiology, Professional Practice, Technology of Fermented Milk Products, and Pharmaceutical Microbiology. Her research interests center around essential oils and their antimicrobial properties, food safety, probiotics, fermentation processes, and pharmaceutical microbiology. She has supervised numerous doctoral, master's, and undergraduate students whose work has explored the antimicrobial effects of essential oils, particularly against pathogens like Candida albicans, Saccharomyces boulardii, and various bacterial strains. Professor Vukašinović-Sekulić's publication record includes significant contributions to carbohydrate polymers research, particularly in nanocomposite hydrogels, as well as important work on lactic acid production from distillery waste, demonstrating her commitment to sustainable bioprocessing and waste valorization. She has mentored an extensive number of students across multiple academic levels, with recent thesis topics focusing on the application of essential oils in treating candidiasis, comparative antifungal activity of essential oils, antibacterial effects against probiotic strains, and the impact of various factors on antimicrobial activity of essential oils.

Miloš RackovićView profile

Professor

• Artificial Intelligence
• Machine Learning
• Databases
• +4 more

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
• +6 more

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.

Ivan Z. MilentijevicView profile

Professor

• Computer Science
• Electrical Engineering
• Digital Signal Processing
• +3 more

Professor Ivan Z. Milentijevic is a full professor at the Faculty of Electronics in Niš, University of Niš, within the Department of Electrical Engineering and Computer Science. He earned his PhD in Computer Science from the same institution in 1998, following a Master's (1994) and undergraduate degree (1989) in the same field. His research focuses on systolic arrays, digital signal processing architectures, and project-based learning methodologies. He has published 8 papers in journals with impact factor and is currently involved in 1 domestic and 1 international research project. Research interests include: Optimal design of systolic arrays for matrix operations FIR filter architectures and error-tolerant systems Reconfigurable hardware and parallel processing Educational technologies in project-based learning His recent work (2002–2008) emphasizes configurable architectures for signal processing and collaborative learning systems. Earlier contributions (1996–1998) focused on systolic array optimization for linear algebra operations. Advising/grants: No explicit student/advisor relationships listed. Current projects involve 1 domestic and 1 international collaboration. Grants and funding details not specified. Labs/teams: Affiliated with the Faculty of Electronics' research groups in computer engineering and signal processing, though specific lab names are not mentioned.

Goran S. RisticView profile

Professor

• Semiconductor Physics
• Radiation Effects on Electronics
• Applied Physics
• +3 more

Goran S. Ristic is a Full Professor at the Faculty of Electronic Engineering, University of Nis, Serbia, since 2004. He holds a PhD in Semiconductor Physics from the same institution (1998), preceded by a master's (1994) and bachelor's degree (1990) in Physics. His research focuses on semiconductor materials, radiation effects on electronic devices, and dosimetry systems. He has published widely in journals like Journal of Applied Physics and IEEE Transactions , with over 69 papers in impact-factor journals. His work includes developing microcontroller-based dosimeter systems and studying defect behaviors in MOSFETs under irradiation and high electric fields. Key research interests include radiation-induced defects in semiconductors, annealing processes, and applications in medical dosimetry. He leads the Applied Physics Laboratory (website: http://www.apl.elfak.rs/ ). Current projects involve 1 national and 1 international collaboration. His contributions span semiconductor device reliability, gas breakdown measurements, and radiation-hardened electronics. Contact details: Email , Phone: +381 (18) 529-329, Address: Aleksandra Medvedeva 4, 18104 Nis, Serbia.

Sandra M. ĐosićView profile

Associate Professor

• Electronics
• Real-Time Systems
• Fault-Tolerant Systems
• +7 more

Sandra M. Đosić is an Associate Professor at the Faculty of Electronics in Niš, University of Niš, Serbia, specializing in Electronics and Embedded Systems. She has been actively contributing to research in real-time systems, fault tolerance, wireless sensor networks, and indoor localization technologies. Research Interests: Her work spans fault-tolerant real-time systems, energy-efficient computing, UWB-based indoor localization, and communication protocols for wireless sensor networks. She explores techniques such as dynamic voltage and frequency scaling (DVFS), tone-based contention resolution, and deflection routing in networks-on-chip to enhance system reliability and efficiency. Publication Trends: Her recent publications (2009–2022) demonstrate a strong focus on improving robustness and performance in embedded and distributed systems. The research integrates signal processing, network optimization, and energy-aware design, primarily applied in industrial and indoor environments. Scientific Awards: No awards are mentioned in the provided text. Advising and Grants: While no specific students are listed, she is currently participating in two national research projects, indicating active involvement in funded research. Her collaborations with researchers such as Igor Stojanovic and Milica Jovanovic suggest a strong team-based research approach. Labs and Research Teams: Although no formal lab or team name is specified, her repeated co-authorship with colleagues from the Faculty of Electronics implies active participation in a research group focused on electronics, communications, and real-time systems.

• Mechanical Engineering
• Energy Engineering
• Process Engineering

Angelina Cvetanovic is a Research Associate in the Department of Energy and Process Engineering at the Faculty of Engineering Sciences, University of Kragujevac, Serbia. She earned her undergraduate and master's degrees from the same institution and has been active in her academic role since her appointment on October 20, 2022. Her research focuses on areas within mechanical engineering, particularly energy and process systems. While specific projects are not detailed, her affiliation with the department suggests engagement in thermal systems, energy efficiency, or industrial processes. She is affiliated with SciDAR, indicating scholarly output in engineering disciplines. No recent publications are listed in the provided text. There is no mention of teaching roles, awards, or student supervision. No scientific awards have been mentioned in the available information. There is no information provided regarding her advisory roles, grants, or participation in research teams. No lab or research team affiliations are specified in the text.