جستجوی استاد راهنمای دانشگاهی

Zaklina Spalevic is a distinguished Professor at Singidunum University, specializing in the intersection of law, technology, and business. With a strong academic background in criminal law and extensive research in cyber law, artificial intelligence applications in legal systems, and tourism law, she has established herself as a leading scholar in digital legal frameworks. Her work spans multiple disciplines, connecting traditional legal principles with emerging technological challenges. Dr. Spalevic earned her doctoral degree in Criminal Law from the University of the Academy of Economics in Novi Sad (2008-2012), following basic studies in General Law at the University of Pristina (1996-2001). Her educational foundation in Science and Mathematics from First Pristina High School (1992-1996) provided the analytical basis for her interdisciplinary approach to legal scholarship. Her research interests focus on the evolving landscape of cyber law, particularly the legal implications of artificial intelligence in judicial systems, electronic governance, and tourism industry regulation. Dr. Spalevic has pioneered work on digital evidence processing, algorithmic justice, and the integration of green law principles into sustainable business practices. Her publications reveal a consistent pattern of addressing emerging legal challenges in the digital age, with increasing emphasis on AI applications across various legal domains. Analysis of her recent publications shows a clear trend toward interdisciplinary research that bridges law, technology, and business. Her work increasingly focuses on practical applications of legal frameworks for emerging technologies, particularly in tourism, agriculture, and judicial systems. The integration of technical solutions with legal regulation represents a distinctive feature of her scholarly contributions. Dr. Spalevic has authored numerous publications including three books: 'Fundamentals of Law with Special Reference to Business and Tourism Law' (2021, 2024 editions) and 'Legal Aspects of Cyberspace' (2018). Her extensive publication record includes over 100 journal articles and conference papers spanning cyber security, electronic governance, intellectual property in digital environments, and legal frameworks for emerging technologies. She actively contributes to academic discourse through conference presentations and collaborative research projects, particularly focusing on the legal implications of artificial intelligence across various sectors. Her work demonstrates a commitment to developing practical legal frameworks that address real-world technological challenges while maintaining foundational legal principles.

• Cyber Law
• Artificial Intelligence and Law
• Business Law
• +۷ مورد دیگر

Dr. Nemanja Stanišić is a Full Professor at Singidunum University's Faculty of Business, with a distinguished academic career spanning over 15 years. He holds a Ph.D. in Corporate Finance from Singidunum University (2010), an MBA in Finance from Lincoln University (2007), and a Bachelor's in Accounting from the University of Belgrade (2005). His expertise focuses on Corporate Finance, Banking, Audit, and Applied Statistical Analysis. His research integrates quantitative methods with economic theory, addressing topics such as audit opinion prediction using AI, tourism destination competitiveness, financial distress dynamics, and air pollution health impacts. He co-authored textbooks including Contemporary Exchange and E-business (2010) and Financial Statement Analysis (2024), and served as Editor-in-Chief of The European Journal of Applied Economics . He teaches courses from Financial Accounting to Advanced Financial Engineering at undergraduate, master's, and Ph.D. levels. The 15 most recent publications highlight his interdisciplinary approach: 7 in Finance/Audit, 5 in Tourism/Hospitality, and 3 in Environmental Health. Key trends include applying machine learning to audit quality (2023), multilevel modeling for hospitality satisfaction (2015-2019), and air pollution mortality analysis (2016). His work appears in high-impact journals like Tourism Management (IF 10.125) and Environmental Health (IF 4.986). He held administrative roles including Rector (2020-2021) and Vice President of Singidunum University. He served as Vice Dean for Student Affairs (2010-2011) and participated in TEMPUS projects for educational reform. He mentors graduate students extensively, advising 100+ bachelor's, 57 master's, and 4 doctoral theses, including international candidates. His visiting professorship at Bangkok's ICO NIDA and teaching in Austria-Singidunum joint programs reflect global engagement. Professional development includes advanced training at Utrecht University (Bayesian Modeling, 2019), Stanford (Mentoring, 2010), and NYU (Valuation, 2012). He reviews for top journals like Annals of Tourism Research and Cornell Hospitality Quarterly , with 1017 Google Scholar citations and 349 Scopus citations. Current research involves the Science Fund of Serbia's TOURCOMSERBIA project evaluating tourism competitiveness models.

• Corporate Finance
• Banking
• Audit
• +۳ مورد دیگر

Svetlana Stanišić is an Associate Professor at Singidunum University's Faculty of Informatics and Computer Science, Department of Applied Artificial Intelligence. She holds a dental degree from the University of Belgrade's Dental Faculty (1998-2004) and a PhD in Physical Chemistry from the University of Belgrade's Faculty of Physical Chemistry (2007-2011). Her interdisciplinary research bridges environmental science, artificial intelligence, and public health. Her research interests focus on environmental science, air pollution modeling, and artificial intelligence applications . She investigates the atmospheric fate of pollutants using advanced machine learning techniques, with particular emphasis on polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and particulate matter. Her work combines environmental chemistry, computational modeling, and public health impact assessment to address urban air quality challenges. Analysis of her recent publications reveals a clear trend toward explainable AI applications in environmental science . She has pioneered the use of SHAP (SHapley Additive exPlanations), XGBoost, and metaheuristic optimization for pollutant fate prediction and source apportionment. Her research spans indoor and outdoor environments, with particular attention to health implications of air pollution exposure in urban settings like Belgrade. Dr. Stanišić leads significant research projects including "crAIRsis" (2024-2026) , which characterizes crisis-caused air pollution alternations using AI frameworks, and "ATLAS" , focusing on artificial intelligence theoretical foundations for spatio-temporal modeling. She has also authored influential books including "Ako je hrana Vaš porok" (2024) and "Ishrana i zdravlje" (2018). Her research group focuses on environmental informatics , developing computational tools to understand pollutant behavior in complex urban environments. The team combines atmospheric chemistry measurements with advanced machine learning techniques to create predictive models with practical applications for urban air quality management and public health protection.

• Environmental Science
• Air Pollution Modeling
• Artificial Intelligence Applications
• +۷ 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.

• Artificial Intelligence
• Machine Learning
• Optimization Algorithms
• +۴ 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.

• Mathematics Education
• Interactive Multimedia in Teaching
• Educational Technology
• +۵ 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.

• Cryptography
• Biometric Security
• Internet of Things (IoT) Security
• +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 Physics
• Atmospheric Science
• Air Pollution Monitoring
• +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.

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

Jelena Gajic is a Professor at the University of Singidunum in Belgrade, Serbia, where she serves in the Faculty of Business within the Department of Marketing. With a comprehensive academic background and extensive publication record, she has established herself as a leading scholar in marketing, advertising, and consumer behavior fields. Doctoral studies at Singidunum University, Belgrade (2008-2011) Master's studies in International Marketing at Faculty of Economics, University of Belgrade (2001-2004) Basic studies in Marketing at Faculty of Economics, University of Belgrade (1992-1997) Cultural and Linguistic studies at XIII Belgrade High School (1988-1992) Professor Gajic's research spans multiple marketing domains with particular emphasis on digital transformation in marketing practices. Her work bridges traditional marketing theories with contemporary digital applications, examining how technologies like AI and neuromarketing are reshaping marketing strategies. She has made significant contributions to understanding social media marketing effectiveness, advertising in digital environments, consumer behavior in tourism contexts, and marketing challenges in higher education institutions. Her research methodology often combines theoretical frameworks with empirical testing, including A/B testing and advanced analytical approaches. Her recent publications demonstrate a clear trajectory toward technology-integrated marketing research. There's a strong emphasis on digital marketing channels, particularly social media platforms like Instagram, and their effectiveness across various contexts including higher education, tourism, and creative industries. Her work increasingly incorporates advanced analytical methods, including AI applications and neuromarketing research, to understand consumer responses. The pandemic's impact on travel behavior and digital communication strategies has also been a significant focus of her recent research, reflecting her ability to address contemporary challenges in marketing. While specific awards aren't documented in the available information, her substantial publication record in reputable journals such as The European Journal of Applied Economics, TEME - Journal of Social Sciences, and others indicates professional recognition within her academic community. Though specific advisees aren't listed in the available information, Professor Gajic's extensive publication record, particularly her work on student perspectives in higher education, suggests active involvement in mentoring and supervising student research. Her leadership in organizing conferences like Sinteza and FINIZ indicates significant contributions to academic community building. Her research on digital marketing, tourism, and consumer behavior has likely been supported by various institutional grants, though specific funding sources aren't detailed in the available information.

• Marketing
• Digital Marketing
• Advertising
• +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.

• Software Testing
• Information Technologies
• Modeling and Simulation
• +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.

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

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

Ivan Miletić is an Associate Professor at the Faculty of Engineering Sciences, University of Kragujevac, specializing in Machine Structures and Mechanization. His academic career at the university includes significant contributions to mechanical engineering research and education within the Department of mechanical structures and mechanization. His research interests span across several key areas in mechanical engineering, with a strong focus on machine design, structural analysis, and materials science. Professor Miletić has made substantial contributions to the understanding of cycloid reducers, gear design, and the mechanical properties of advanced materials. His work bridges theoretical analysis with practical applications in automotive, aerospace, and industrial machinery sectors. Professor Miletić's publication record demonstrates a strong focus on mechanical design optimization and structural analysis. His recent work has particularly emphasized the development and analysis of cycloid reducers, gear systems, and advanced composites. He has also contributed significantly to design automation methodologies and structural optimization techniques, applying advanced computational approaches to solve complex engineering problems across multiple disciplines. His scholarly contributions have practical applications in diverse fields including automotive engineering, aerospace technology, and industrial machinery design. Professor Miletić maintains an active research profile with publications spanning from 2020 to 2025, indicating ongoing scholarly productivity in mechanical engineering disciplines. As an educator, Professor Miletić has been instrumental in developing curriculum and mentoring students in mechanical engineering disciplines. His election to the position of Associate Professor in 2021 reflects his significant contributions to both research and teaching at the Faculty of Engineering Sciences.

• Mechanical Engineering
• Machine Structures
• Mechanization
• +۵ مورد دیگر

Miloš Dobrojević serves as a Professor at Singidunum University's Faculty of Informatics and Computing in Belgrade, Serbia. His academic foundation includes doctoral, postgraduate, and bachelor studies at the University of Belgrade's Faculty of Mechanical Engineering. His research spans Artificial Intelligence , Internet of Things , and Computer Vision with emphasis on practical applications. Key focus areas include metaheuristic optimization of neural networks for tasks like crop yield prediction, medical diagnostics, and cybersecurity. Recent work demonstrates strong industry relevance in precision agriculture, drone detection systems, and sustainable homestead automation. Analysis of his 15 most recent publications reveals a consistent pattern of applying modified metaheuristics to enhance deep learning models across diverse domains. His work bridges theoretical AI advancements with real-world implementations in agriculture, healthcare, and energy systems. Scientific Contributions: Author of 3 textbooks including 'Veb informacioni sistemi' (2024) and 'Veb programiranje' (2021) Published 40+ journal/conference papers between 2003-2025 Active contributor to Springer book chapters on AI applications Dobrojević's work demonstrates strong practical orientation with projects in Serbian renewable energy transition, flood prevention systems, and municipal e-government solutions. His recent collaborations with researchers like N. Bacanin and M. Zivkovic show consistent output in high-impact journals. Current projects focus on generative AI for medical data and computer vision for agricultural optimization. His laboratory work centers on IoT-based monitoring systems for environmental applications, particularly water management in mountainous regions. Ongoing research explores drone detection networks and waste classification systems using advanced computer vision techniques.

• Artificial Intelligence
• Internet of Things
• Computer Vision
• +۴ 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
• Cybersecurity
• Machine Learning
• +۳ مورد دیگر