جست‌وجوی استاد و پژوهشگر

• Food Safety
• Meat Technology
• Food Waste Management
• +۴ مورد دیگر

Nataša Kilibarda serves as Professor at Singidunum University's Faculty of Tourism and Hospitality Management in Belgrade, Serbia. Her academic career spans over two decades with specialized expertise in food safety, meat technology, and sustainable food systems. She holds doctoral qualifications in Food Hygiene and Technology from the University of Belgrade's Faculty of Veterinary Medicine. Her research focuses on critical food industry challenges including food waste reduction, pandemic-era food safety protocols, sustainable meat production, and hospitality sector food handling practices. Kilibarda's work bridges academic research with practical industry applications, particularly in Serbian and Balkan contexts. Her recent publications demonstrate growing emphasis on sustainable food systems, biogas production from organic waste, and the intersection of tourism with traditional food quality. Her 15 most recent publications reveal consistent contributions to food safety literature with particular expertise in: Meat technology and quality control Microbiological safety of processed foods Food waste management strategies Pandemic impact on food systems Sustainable resource utilization Kilibarda maintains active collaboration with Serbian food industry stakeholders and contributes to national food safety standards development. Her work appears in prominent regional journals including Meat Technology, Journal of Food and Nutrition Research, and Tehnologija mesa.

• 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.

• 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.

• Chemistry of natural products
• Phytochemistry
• Analytics of organic compounds
• +۳ مورد دیگر

Dr. Snezana S. Trifunovic is a full-time Researcher at the Faculty of Chemistry , University of Belgrade, affiliated with the Department of Organic Chemistry. She holds ORCID 0000-0001-9528-6686 and ResearcherID Q-5612-2016. Education: University of Belgrade PhD in Chemical Sciences (2006), Master's (1997), and BSc (1991) Academic roles: Scientific Advisor since 2018, Senior Research Associate (2012–2018), Research Associate (2007–2013), Assistant (1998), Assistant Trainee (1992) Her research focuses on phytochemistry , natural product analysis , and bioorganic chemistry , with particular interest in secondary metabolite profiling, plant-derived anticancer agents, and chemical characterisation of medicinal species. Recent projects include metabolomics for schizophrenia biomarker discovery (2021–2024) and portable GC-MS/LC-MS methods development for OPCW field testing (2017–2021). Publications emphasize bioactive natural products , polymer chemistry , and plant metabolite bioactivity across two decades of research output. Active in international collaboration with the Organisation for the Prohibition of Chemical Weapons (OPCW), she has contributed to 5 major research projects since 1998, including transgenic plant studies for anticancer compounds and chemoprotective DNA assays. Current work involves metabolomic fingerprinting of neuropsychiatric disorders and development of portable analytical devices.

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.

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.

• Machine Learning
• Computer Vision
• Emotion Recognition
• +۵ مورد دیگر

Marina Marjanovic is a faculty member at Singidunum University in Belgrade, Serbia, affiliated with the Faculty of Informatics and Computing. She maintains an active research profile with numerous publications spanning machine learning, computer vision, and signal processing applications. Her work demonstrates strong interdisciplinary connections between theoretical AI development and practical implementations in healthcare, security, and digital government services. Dr. Marjanovic earned her Doctoral degree in Signals and Systems from Universidad Politecnica de Madrid in 2007, following a Master's degree in the same field from the same institution in 2005. Her foundational education includes basic studies in Telecommunications at the Faculty of Electrical Engineering in Belgrade, and secondary education at the third Belgrade high school with a focus on natural sciences. This strong technical background has enabled her transition from traditional signal processing to contemporary AI research. Her research interests center around machine learning and computer vision, with significant contributions to emotion recognition, sign language processing, and explainable AI. She has demonstrated particular expertise in developing robust AI models that address real-world challenges such as demographic bias in age estimation systems, vulnerability to adversarial attacks in deep learning models, and accurate medical diagnostics through imaging analysis. Her recent work shows increasing focus on healthcare applications, security implications of AI systems, and making AI more transparent and interpretable. Analysis of her publication trajectory reveals a clear evolution from signal processing foundations toward contemporary AI applications. Her recent work (2022-2024) shows strong emphasis on healthcare AI, security applications, and explainability, often combining traditional machine learning approaches with novel optimization techniques. She frequently collaborates with international researchers across multiple institutions, demonstrating the global reach of her work. Dr. Marjanovic has established herself as a productive researcher with consistent publication output across reputable journals and conferences including IEEE transactions, Springer publications, and specialized AI conferences. Her collaborative approach is evident through her extensive co-authorship network spanning multiple Serbian and international institutions. She actively contributes to the academic community through conference organization (including Sinteza conferences) and participation in research projects at Singidunum University's research institutes. Her work bridges theoretical advancements with practical implementations across multiple domains, demonstrating versatility and impact across the AI research landscape.

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

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.

• Electronic Music
• Algorithmic Composition
• Audio Signal Processing
• +۲ مورد دیگر

Zlatko Baracskai is a Bosnian-Hungarian experimental musician, sound programmer, and academic. He currently serves as a Senior Lecturer at the University of West of England in the Faculty of Computer Science and Creative Technologies, while also holding a Visiting Professor position at the Faculty of Music in Belgrade's Music Direction Study Program since 2020. His academic journey includes a sonology degree from the Institute of Sonology in Den Haag and a PhD in contemporary composition from the University of Birmingham (2011). Research interests span Electronic music composition Algorithmic sound processing Experimental audio technologies Neural network applications in music Asymmetrical rhythm development His publications demonstrate technical expertise in audio algorithm design and neural networks for sound manipulation, with conference papers presented at AES, ICMC, and IEEE SpliTech. Notable projects include Coca-Cola Beatbox Pavilion (2012) and De-Fuse Interactive Installation (2005).