جستجوی استاد راهنمای دانشگاهی

Saša Adamovićمشاهده پروفایل

استاد

• Cryptography
• Biometric Security
• Internet of Things (IoT) Security
• +۳ مورد دیگر

Prof. Dr. Saša Adamović is a faculty member at Singidunum University in Belgrade, Serbia, affiliated with the Faculty of Informatics and Computer Science . His academic career spans over 15 years with a focus on Cryptography, Biometrics, and IoT Security . Born October 15, 1985, in Drvar, Bosnia and Herzegovina PhD in Advanced Security Systems (2013), Master’s in Contemporary Information Technologies (2008), and Bachelor’s in Business Informatics (all from Singidunum University) His research interests include: Biometric Cryptography Blockchain for IoT Security Catalan Number Applications in Cryptography Machine Learning in Security Systems Virtualization and Energy Efficiency Steganography and Forensics Recent publications highlight trends in: IoT Healthcare Security (2022) Biometric Authentication (2021) Combinatorial Cryptography (2021) Machine Learning for Diabetes Prediction (2021) Distance Learning Security (2023) He served as one of five Serbian representatives in the Open World program (USA) for expert exchange in technology development.

Marko T. Milojkovicمشاهده پروفایل

استاد

• Control Systems
• Signal Processing
• Neural Networks
• +۴ مورد دیگر

Marko T. Milojkovic is a full professor at the Faculty of Electronics, University of Nis, leading the Department of Automation since 2022. He holds a PhD in Systems Management (2012), Master's in Automation (2008), and a Bachelor's in Computer Engineering & Informatics (2003), all from the same institution. His research focuses on adaptive control systems, neural networks, and dynamical systems modeling, with 27 papers in impact-factor journals. He currently heads the Laboratory for Modeling, Simulation and Systems Management and participates in 2 national and 2 international projects. Education: PhD: Systems Management (2012) MSc: Automation (2008) BSc: Computer Engineering & Informatics (2003) Research interests include neuro-fuzzy systems, MIMO system optimization, and endocrine neural networks applied to adaptive control. His publications demonstrate expertise in quasi-orthogonal filters, sliding mode control, and time-series forecasting. No scientific awards are explicitly mentioned, but his extensive project participation highlights active collaboration in control systems and automation. Prof. Milojkovic's work bridges theoretical modeling and practical applications, with recent emphasis on intelligent control systems and nonlinear dynamics. His laboratory facilitates interdisciplinary projects addressing complex system management challenges.

• 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.

• Environmental Science
• Sustainable Development
• Ecological Conservation
• +۳ مورد دیگر

Vuk Gajić is an Assistant Professor at the Faculty of Applied Ecology, Singidunum University, where he has held academic roles since 2016. His career progression includes positions as a teaching associate (2016), assistant (2019), and current role (2023). He earned a Ph.D. in Environment and Sustainable Development from Singidunum University (2019–2022), following prior studies in environmental protection and risk management at the same institution. Research interests span environmental science, sustainable development, GIS applications, and radiation technology for waste and food treatment. He has contributed to interdisciplinary studies, including soil contamination analysis in Libya, microbial decontamination via ionizing radiation, and machine learning applications for software defect prediction and agricultural weed detection. His work bridges environmental engineering with technological innovation, emphasizing sustainability and ecological conservation. Publications reflect a focus on environmental monitoring, pollution assessment, and eco-technologies. Key themes include GIS-based environmental databases, forest fire prevention through sensor networks, and agricultural waste reuse. His research often integrates quantitative methods with geospatial tools, addressing both local and global environmental challenges. Teaching responsibilities include courses on geodiversity, sustainable development, and natural hazards. He actively participates in academic conferences, contributing to peer-reviewed journals and presenting at events like Sinteza and SETI. Current projects likely explore emerging technologies in environmental management and sustainable practices.

Luis Barbaمشاهده پروفایل

پژوهشگر ارشد

• Computational Geometry
• Algorithms
• Graph Theory
• +۴ مورد دیگر

Luis Barba is a Research Fellow in the Machine Learning and Optimization group at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, working under Professor Martin Jaggi. He completed his PhD through a cotutelle program between Carleton University, Ottawa and Université Libre de Bruxelles, Brussels, supervised by Professors Stefan Langerman, Jit Bose, Pat Morin and Vida Dujmović. Prior to that, he earned his master's degree at Universidad Nacional Autónoma de México (UNAM) under Professor Jorge Urrutia. Dr. Barba's research spans computational geometry, algorithms, graph theory, and more recently, machine learning and optimization. His work addresses fundamental problems in geometric data structures, Voronoi diagrams, graph coloring, and distributed learning. He has made significant contributions to understanding time-space trade-offs in geometric algorithms and developing efficient methods for problems like geodesic Voronoi diagrams and dynamic graph coloring. Dr. Barba's publication record demonstrates a clear evolution from theoretical computational geometry to practical applications in machine learning. Early in his career, he focused on fundamental geometric problems including linear-time algorithms for geodesic Voronoi diagrams and efficient convex hull computation in polygonal domains with obstacles. More recently, his work has shifted toward machine learning, where he has developed novel optimization techniques for distributed and federated learning settings, including implicit gradient alignment methods and multilayer lookahead approaches. Dr. Barba has published extensively in top-tier conferences and journals including Symposium on Computational Geometry (SoCG), Canadian Conference on Computational Geometry (CCCG), Algorithmica, and Discrete and Computational Geometry. His collaborative work demonstrates strong connections across the computational geometry and algorithms communities, with frequent co-authorship with leading researchers in these fields. Throughout his career, Dr. Barba has maintained a consistent focus on algorithmic efficiency and computational complexity, whether addressing theoretical geometric problems or practical machine learning challenges. His work exemplifies how deep theoretical insights can inform practical computational approaches across different domains of computer science.

Vladimir M. Ciricمشاهده پروفایل

استاد

• Computer Networks
• Network Security
• Parallel Computing
• +۳ مورد دیگر

Dr. Vladimir M. Ciric is a Full Professor at the Faculty of Electronics, University of Niš, leading the Department of Computer Science. He directs the Laboratory for Advanced Security Systems and specializes in network security, distributed systems, and high-performance computing. His research spans intrusion detection systems, cloud computing cost modeling, and parallel algorithm design. Notable contributions include Hadoop-based network intrusion detection techniques and tiered programming pedagogy. He received the Cisco Excellence Award (2015) for network technology education. Dr. Ciric teaches courses on network design, cloud computing, and security while maintaining research collaborations in cybersecurity and distributed architectures. His recent work focuses on extreme class imbalance in intrusion datasets and sparse matrix optimizations.

• Sensor Technologies
• Innovation Management
• Entrepreneurship Ecosystems
• +۳ مورد دیگر

Tamara Papić is an Assistant Professor at Singidunum University in Belgrade, specializing in Innovation Management and Entrepreneurship. She holds a Ph.D. in Sensor Technologies from Jožef Stefan International Postgraduate School (Slovenia) and a Master's in Quality Management from Fakultet organizacionih nauka. Her research focuses on sensor technologies, dyslexia detection through eye-tracking, and the application of AI in education and marketing. Key academic contributions include developing sensor-based systems for analyzing reading patterns in children with dyslexia, leveraging machine learning models like VGG16 and autoencoders. She co-founded BabyFM, a startup creating smart thermoregulation devices for infants using sensors and mobile apps. Her work has been supported by grants from Innovation Forum Cambridge, Star Tech, and Serbia’s Innovation Fund. Professionally, she produced RTV Serbia’s entrepreneurial series 'My Hero' and 'Golden Idea,' and organized national startup competitions. She chairs strategic conferences like Smart City SEE and Belgrade Strategic Dialogue, promoting innovation ecosystems. Her cross-disciplinary projects bridge engineering, education, and business strategy.

Olga Ristićمشاهده پروفایل

دانشیار

• Software Testing
• Information Technologies
• Modeling and Simulation
• +۵ مورد دیگر

Olga Ristić is an Associate Professor at the Department of Information Technologies, Faculty of Technical Sciences Čačak, University of Kragujevac, Serbia. Her office is located at Svetog Save 65, Čačak (Office No. 237), and she can be contacted via phone (+381 32 302-714) or email. She holds a Diploma in Technics and Informatics (1997), a Master's in Technical Sciences (2006), and a PhD in Information Technologies and Systems (2016), all from the University of Kragujevac. Her research focuses on: Software testing methodologies and quality assurance Modeling and simulation of complex systems Optimization algorithms for industrial applications Educational technology and IT pedagogy Mobile applications and information systems reliability Her recent publications emphasize interdisciplinary approaches, with strong trends in machine learning applications for cybersecurity, optimization in Industry 4.0 systems, educational technology innovations, and sustainable energy management. She frequently employs simulation techniques and algorithm development across diverse domains. She has led or contributed to eight Ministry of Science-funded projects: Curriculum development for IT education programs Software quality assurance frameworks Industrial system reliability modeling Food supply chain optimization Deregulated energy distribution systems At the Faculty of Technical Sciences, she coordinates courses across all academic levels, including Data Structures, Software Testing, Mobile Applications, and Quality of Software. She also conducts professional development seminars on database design and ISTQB certification.

Marko Šaracمشاهده پروفایل

استاد

• Cybersecurity
• Artificial Intelligence
• Blockchain Technology
• +۷ مورد دیگر

Marko Šarac is a Professor at Singidunum University in the Faculty of Informatics and Computer Science . He holds a Master's degree in Contemporary Information Technologies (2008) and a PhD in Advanced Protection Systems (2013) from the same institution. His research spans Cybersecurity, Artificial Intelligence, Blockchain, Internet of Things (IoT), Machine Learning, and Data Privacy . Education: Master: Contemporary Information Technologies, Singidunum University, 2008 PhD: Advanced Protection Systems, Singidunum University, 2013 Research Focus: SSL Traffic Security, Virtual Datacenters, Biometric Cryptography, and IoT Healthcare Systems Developed frameworks for Explainable AI in Metaverse Security , Blockchain-based IoT Security Gateways , and Machine Learning for Medical Diagnostics Notable Publications: 2025: CNN-enhanced attack detection for IoT-based Metaverse 2024: Modified Firefly Algorithm for medical dataset classification 2023: Space weather prediction using metaheuristics Projects: Co-author on 9+ books including Internet Marketing (2020) and Computer Network Security (2014) Contributed to 50+ peer-reviewed journals and conference papers on cybersecurity and AI Grants & Collaborations: Active in IEEE , ZINC , and Sinteza conference series Collaborated with researchers across Europe and Asia on IoT, Blockchain, and Cloud Security Contact: msarac@singidunum.ac.rs

Miloš Mravikمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +۳ مورد دیگر

Miloš Mravik is an academic affiliated with Singidunum University's Faculty of Informatics and Computing, specializing in research involving artificial intelligence, cybersecurity, and data science. He holds a doctoral degree in 'Advanced Protection Systems' from Singidunum University (2020–2023), preceded by a Master’s in 'Contemporary Information Technologies' (2018–2019) and a Bachelor’s in 'Informatics and Computing' (2014–2018). His work emphasizes applying machine learning techniques to real-world challenges like healthcare diagnostics, cybersecurity frameworks, and pandemic-era education systems. Research Interests: AI-driven cybersecurity solutions for IoT and blockchain Machine learning applications in health informatics Optimization of predictive algorithms using metaheuristics E-learning strategies during crises Recent articles focus on explainable AI for metaverse security, sentiment analysis using BERT models, and blockchain node detection via XGBoost. His work bridges theoretical computer science with practical applications in emergency education and pandemic response. No scientific awards listed. Advised no formally registered students. Active in conference organizing and software prototyping, as seen in projects like a scheduling web application and network management systems.

• Artificial Intelligence
• Neural Networks
• Image Processing
• +۳ مورد دیگر

Petar Biševac is a Lecturer at the Faculty of Informatics and Computing within Singidunum University , Belgrade. His academic work focuses on applied artificial intelligence and machine learning. Education : Not explicitly detailed in available texts. Research Interests : Spanning Artificial Intelligence , Neural Networks , Image Processing , and Metaheuristic Optimization , his research emphasizes hybrid AI systems for biomedical signal processing, cryptocurrency forecasting, and image analysis. Publications : Recent works include anomaly detection in ECG/EEG signals, vehicle damage recognition, and Ethereum price forecasting using LSTM and metaheuristic algorithms. Collaborations : Frequently works with researchers like Nebojsa Bacanin, Milan Zivkovic, and Predrag Spalević. Contact : Email pbisevac@singidunum.ac.rs

P. N. Karthikمشاهده پروفایل

استادیار

• Multi-armed bandits
• Federated learning
• Differential privacy
• +۷ مورد دیگر

P. N. Karthik is an Assistant Professor in the Department of Artificial Intelligence at the Indian Institute of Technology (IIT) Hyderabad. He holds a Ph.D. and Master of Science in Engineering from the Indian Institute of Science (IISc), Bengaluru, advised by Prof. Rajesh Sundaresan, and was previously a Research Fellow at the National University of Singapore (NUS) working with Prof. Vincent Y. F. Tan. Research Interests: His primary research areas include multi-armed bandits, federated learning, differential privacy, reinforcement learning, information theory, and statistics. He focuses on sequential decision-making under uncertainty, privacy-aware learning systems, and optimization in distributed environments. Publication Trends: His recent work centers on best arm identification in various bandit settings, including restless, federated, and differentially private frameworks. These studies, published in top venues like IEEE Transactions on Information Theory, AISTATS, ISIT, ICLR, and AAAI, reflect a strong theoretical foundation with practical implications in AI and data science. Scientific Awards: Faculty Teaching Excellence Award 2025, IIT Hyderabad First place, Electronics and Communication Engineering category, 100 seconds competition, INAE Kanpur Chapter Teaching and Mentoring: He teaches courses such as Stochastic Processes and Programming for AI, receiving consistently high instructor ratings (up to 4.95/5.0). He mentors TAs and emphasizes conceptual clarity, active learning, and student engagement. He has collaborated with industry and government bodies like BMTC and Netradyne on transportation research. Academic Service: He serves on technical program committees for ISIT and APWDSIT and has organized events like the 2024 JTG/IEEE ITSoc Summer School. His collaborators include prominent researchers such as Vincent Y. F. Tan, Rajesh Sundaresan, Krishna Jagannathan, and Yeow Meng Chee.

Aneta P. Prijicمشاهده پروفایل

استاد

• Microelectronics
• Energy Harvesting
• Wireless Sensor Networks
• +۷ مورد دیگر

Aneta P. Prijic is a Full Professor at the Faculty of Electronics in Niš, University of Niš, Serbia, affiliated with the Department of Microelectronics and Microsystems. She completed her academic training at the same institution, earning her PhD in 2007 in Microelectronics and Microsystems. Her research focuses on energy harvesting, microelectronics, and sensor systems. Research Interests: Her work centers on energy harvesting technologies—particularly thermal and photovoltaic—for wireless sensor nodes. She investigates reliability in power semiconductor devices, designs PCB-based sensors, and develops low-power systems for industrial and telemetry applications. Her expertise spans microelectronics, device modeling, and sustainable embedded systems. Publication Trends: Her recent publications emphasize energy efficiency in sensor networks, with a strong focus on thermoelectric and photovoltaic harvesting under low-power conditions. She also contributes to semiconductor reliability (e.g., NBTI analysis) and educational innovations in PCB design. Her work appears in IEEE, Elsevier, and MDPI journals, reflecting interdisciplinary contributions in electronics and engineering. Scientific Contributions: Co-author of 4 national patents, 1 international patent, and 13 technical solutions Active member of the Program Committee of the ETRAN Society (Microelectronics and Optoelectronics section) Participant in 3 national and international research projects Advising and Grants: While specific students are not listed, her collaborative publications suggest mentorship of junior researchers. She is actively involved in funded research projects focusing on energy harvesting and microelectronic systems, contributing to technological innovation and education. Labs and Teams: She is affiliated with research groups at the Faculty of Electronics in Niš focused on microelectronics, energy systems, and sensor technologies. Her work is integrated into national and international collaborations, particularly in the development of reliable, low-power electronic systems.

Stefan Ćirkovićمشاهده پروفایل

مدرس

• Cybersecurity
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Stefan Ćirković is a Teaching Associate in the Department of Information Technologies at the Faculty of Technical Sciences in Čačak, University of Kragujevac. His office is located at Saint Sava 65, 32102 Čačak, Serbia. He is currently pursuing doctoral studies in Information Technology (2023–present) at the same institution. Education: Doctoral Academic Studies – Information Technology, University of Kragujevac (2023–present) Master of Academic Studies – Information Technology, University of Kragujevac (2022–2023) Basic Academic Studies – Information Technology, University of Kragujevac (2018–2022) Specialized Program – Cybersecurity, University of Kragujevac (2024) Research Focus: Ćirković specializes in applied artificial intelligence with significant work in cybersecurity, medical imaging, and network systems. His research demonstrates strong emphasis on practical AI implementations including real-time object detection (YOLO algorithm), anomaly detection in networks, federated learning for healthcare applications, and cybersecurity techniques using large language models. His work frequently intersects with medical informatics, particularly in diagnostic applications. Publication Trends: Recent publications (2024–2025) show predominant focus on AI/ML applications across multiple domains. Cybersecurity remains a core theme with novel approaches to web application security and network anomaly detection. Medical applications feature prominently, especially in diagnostic imaging (kidney stones, skin cancer) and hemodialysis optimization. Methodologically, there's consistent exploration of deep learning architectures and real-time systems. Laboratory Affiliations: Associated with the Computer Science Laboratory at the Faculty of Technical Sciences in Čačak. Utilizes institutional resources including the Moodle e-learning platform and Microsoft 365/Teams infrastructure for academic activities.

• Production Technologies
• Mechanical Engineering
• Computer-Aided Design (CAD)
• +۳ مورد دیگر

Dr. Anđelija Mitrović is an Assistant Professor at the Department of Mechatronics, Faculty of Technical Sciences in Čačak, University of Kragujevac. She holds a PhD in Technical Sciences (Mechanical Engineering) from 2016 and Master of Science in Information Technology from 2010. Her academic career spans multiple institutions including College of Technical Vocational Studies Čačak (2006-2011) and Faculty of Technical Sciences Čačak (2020-present). BSc in Hydropower Engineering, Mechanical Engineering Faculty Belgrade (1996) Profesor in Engineering and Informatics, Technology Faculty Čačak (2006) MSc in Information Technology, Technology Faculty Čačak (2010) PhD in Technical Sciences, Faculty of Technical Sciences Novi Sad (2016) Her research focuses on Production Technologies with emphasis on metal cutting thermal analysis, CAD/CAM systems, and educational technology innovations. Key research trends include: Thermal modeling in conventional and unconventional machining 3D virtual environment applications for engineering education Finite element analysis of milling processes Software-based cutting parameter optimization Integration of immersive learning platforms Publications demonstrate expertise in Thermal Analysis , Manufacturing Simulation , and Virtual Learning Environments . While no formal awards are listed, her work appears in reputable journals and international conference proceedings.