Дину Драган is a Professor at the Department of Applied Computer Science, Faculty of Technical Sciences, University of Novi Sad. His academic journey includes a BSc (2003), MSc (2008), and PhD (2013) in Computer Science and Informatics, with a focus on medical imaging, data compression, and multimedia systems. He has been affiliated with the university since 2004, progressing from Assistant Lecturer to Associate Professor (2014). Research interests include compression techniques in healthcare systems, PACS implementation, and multimedia technologies. He has contributed to international journals like Computer Science and Information Systems as an editor and reviewer, and his work on JPEG2000 compression in DICOM standards has been impactful. He was awarded the FESTO Young Research Scholarships (2008) for research presented at the DAAMA International Symposium. Teaching responsibilities include courses on Human-Computer Interaction, Multimedia Systems, Data Compression, and Programming Languages. He actively participates in academic conferences and editorial boards, emphasizing interdisciplinary collaboration in technical and medical informatics.
Vladimir Kraguljac is an Assistant Professor at the Faculty of Hotel Management and Tourism in Vrnjačka Banja, part of the University of Kragujevac, Serbia. He teaches Business Informatics and Information and Communication Technologies in the context of hotel and tourism education. His academic affiliation is deeply rooted in applied informatics within the tourism and hospitality sector. His research interests focus on the integration of Information Technology in education, particularly in e-learning , distance learning software , and the use of touchscreen devices in teaching. He explores how digital tools enhance pedagogical outcomes in business informatics, especially for tourism and hospitality management students. The trend in his scholarly work reflects a strong emphasis on educational technology , ICT in tourism education , and digital assessment methods . His publications span topics such as web security, academic integrity, and internet-enhanced language instruction, showing a multidisciplinary approach to modern educational challenges. Professional Affiliations: Institute of Electrical and Electronics Engineers (IEEE) Project Involvement: TEMPUS Project: 'Modernization and Harmonization of Tourism Study Programmes in Serbia – MHTSPS' Project: 'Improving English Language Teaching in the Health Tourism Study Program in Primary Academic Studies' He advises on curriculum development and digital integration in higher education, particularly in tourism studies. His work contributes to modernizing academic programs through international collaboration and technology adoption. He is actively involved in academic service and has contributed to multiple conference proceedings and thematic publications. He is affiliated with research teams focused on educational innovation and digital transformation in tourism. His lab or research environment appears to be collaborative, involving co-authors from technical and educational backgrounds, and is oriented toward practical implementation in higher education settings.
Mario V. Zlatovic is a Full Professor at the Faculty of Chemistry, University of Belgrade , specializing in Natural Products Chemistry, Computational Chemistry, and Medical Chemistry. He has held various academic roles since 1988 and currently teaches courses on Chemical Bonding, Molecular Modeling, and Organic Chemistry. Born: 7 April 1963, Šibenik, Croatia Languages: Serbian (native), English, Russian, Croatian Research Focus: His work explores non-covalent interactions in proteins and small molecules, particularly in superoxide dismutases and anion-π systems . He designs antimicrobial and antimalarial agents, emphasizing structure-based drug design and 3D-QSAR analysis . Scientific Contributions: Over 15 years, his publications span materials science (DFT calculations), enzyme inhibition (α-glucosidase), and marine bioconjugates. He combines computational methods with experimental validation in drug discovery. Fulbright Fellow (2009-2010) at National Cancer Institute, USA Supervisor of HemNet (2020-present) Member of Faculty Council and Examination Recognition Commission Teaching: Offers courses on Molecular Modeling, Chemical Informatics, and Project Management. His educational work includes a 2015 publication on homology modeling pedagogy.
Dejan Lukić serves as Full Professor and Vice-Dean for Investments and Cooperation with Industry at the Faculty of Technical Sciences, University of Novi Sad. He has held progressively senior academic positions since joining the institution in 2000, including Director of the Department of Production Engineering (2021-2024) and Assistant Director (2018-2021). His academic journey began with undergraduate studies in Mechanical Engineering at the same faculty, followed by master's (2007) and doctoral degrees (2012) in specialized production engineering fields. His educational background includes: Bachelor's degree in Mechanical Engineering, Faculty of Technical Sciences (1999) Master's thesis: 'Development of a system for automated design of technological processes for manufacturing plastic injection molds' (2007) Doctoral dissertation: 'Development of a general model of technological preparation of production' (2012) Professor Lukić's research focuses on process planning, production optimization, and techno-economic analysis in manufacturing systems. His work bridges theoretical frameworks with practical industrial applications, particularly in virtual design, CAPP systems integration, and optimization of manufacturing processes. He has made significant contributions to the application of digital technologies in production engineering, including STEP-NC implementation, fuzzy logic for quality control, and collaborative process planning systems. His publication record demonstrates consistent advancement in manufacturing process optimization, with recent work emphasizing multi-criteria decision making, thin-walled structure machining, and digital integration of manufacturing systems. The research trajectory shows evolution from foundational work in traditional process planning toward contemporary applications involving artificial intelligence, collaborative systems, and Industry 4.0 technologies. Professor Lukić has been actively involved in academic service, participating in numerous evaluation committees, professional competitions, and serving as representative of Serbia in the Assembly of the Institute for Materials Testing. His industrial engagement includes consulting on CE/3A product marking, technical system maintenance, and implementation of application software solutions. As an educator and mentor, he has supervised more than 45 undergraduate and master's theses, completed one doctoral dissertation supervision, and currently guides three doctoral candidates. He teaches a comprehensive curriculum spanning process planning, production optimization, logistics, and technological preparation of production across all academic levels. His leadership extends to heading the Master of Professional Studies in Production Engineering program and serving on program committees for multiple scientific conferences and journals in mechanical engineering. Professor Lukić also maintains active industry collaboration through solving professional problems related to product development, manufacturing systems maintenance, and specialized training programs.
Dr. Željko Jovanović is an Assistant Professor at the Department of Computer and Software Engineering , Faculty of Technical Sciences in Čačak , University of Kragujevac , Serbia. He holds a PhD in Electrical Engineering and Computing (2020) from the University of Niš, with a focus on Application of IT in improving the quality of patient transport , and a Diploma Engineer in Computer Science (2008) from the University of Kragujevac. Current roles: Head of Department (2023–present), Coordinator of Undergraduate Studies (2021–present) Teaching areas: Programming basics, Object-oriented programming, Software engineering, Medical informatics (PhD studies) His research focuses on Computer Engineering and Software Engineering , with applications in Medical Informatics , Intelligent Transportation Systems , IoT , and Smart Cities . He has contributed to 15+ publications in journals and conferences, including IEEE Transactions on Intelligent Transportation Systems , Electronics , and Transactions in GIS , emphasizing artificial neural networks , data mining , and comfort assessment in healthcare and transportation contexts. Projects include the national TR32043 initiative on low-power computing systems and the international NeReLa project for remote labs. He has developed technical solutions for thermal comfort monitoring , smart suspension control , and IoT-based systems , and serves on academic committees for software engineering and computer science education.
Nikola Stanić serves as a Teaching Assistant at the Department of Information Technologies, Faculty of Technical Sciences, University of Kragujevac, where he has held academic positions since February 2021. His institutional affiliation includes active teaching duties across multiple technical disciplines at this Serbian research-intensive faculty. His academic credentials feature: Master of Academic Studies in Information Technology (2022, avg. grade 10.0) from University of Kragujevac with thesis on "Software Quality Management Using the Example of an Application for the Police Department" Bachelor of Academic Studies in Information Technology (2021, avg. grade 9.50) from same institution with thesis on "Example of Developing a Digital Game Using Unreal Engine Software" Technical secondary education in Computer Electrical Engineering from "Kolubara" School in Lazarevac Stanić's research focuses on the intersection of computer vision and practical software engineering, with significant contributions to medical diagnostics through YOLO-based detection systems for skin cancer and kidney stones. His work extends to public safety applications via real-time fire/smoke identification algorithms and explores Kotlin multiplatform development frameworks. Early career research included statistical modeling for demographic forecasting in regional healthcare planning, demonstrating methodological versatility across computer science subfields. His publication trajectory reveals concentrated expertise in deep learning applications (75% of recent work), particularly object detection systems adapted for medical and safety-critical domains. The remaining publications address software engineering challenges in cross-platform development and statistical prediction models, indicating a research program bridging theoretical computer science with societal applications in healthcare and public safety. While no scientific awards are documented, Stanić actively contributes to academic instruction through exercises in Programming Languages, Advanced Object-Oriented Programming, Software Testing, Mobile Application Development, and Databases. His teaching portfolio extends to programming instruction for children (ages 6-18) at Logiscool Srbija and online Serbian language tutoring, though no research grants or graduate student supervision are indicated. He operates within the Computer Science Laboratory infrastructure at the Faculty of Technical Sciences in Čačak, which supports his computational research through specialized equipment and collaborative environments for vision-based algorithm development and software engineering projects.
Aleksandar Milenkovic is an Assistant Professor at the Faculty of Electronics in Niš, University of Niš, specializing in Computing and Informatics. He holds a PhD in Electrical and Computer Engineering (2022) and a BSc in Computer Science (2009), both from the same institution. His research focuses on medical information systems integration, chronic disease tracking, pandemic response strategies, and software engineering practices in healthcare. Education: PhD in Electrical and Computer Engineering, Faculty of Electronics, University of Niš (2022) Bachelor's in Computer Science, Faculty of Electronics, University of Niš (2009) Research interests span medical information systems, chronic disease management, pandemic-adaptive technologies, and cross-platform software development. Notable projects include the MEDIS.NET system and collaborative work on distributed medical data repositories. His recent publications emphasize data synchronization in healthcare systems, resource-aware software updates, and telemedicine expansion during crises. Advising and Grants: Collaborates with senior researchers like Dragan Janković and Petar Rajković on national/international projects. Active in developing software solutions for Serbian public healthcare challenges. Labs/Teams: Involved in the MEDIS.NET project and interdisciplinary teams addressing healthcare system interoperability and pandemic response technologies.
Suzana R. Stojkovic is a Full Professor at the University of Niš, Faculty of Electronics in Niš, Department of Computing and Informatics. She holds a Doctorate from the same faculty (1996) and graduated in Electrical Engineering and Computer Science in 1990. Her academic career includes being elected as an Assistant Professor in 2005 and Full Professor in 2022. Her research focuses on spectral analysis of multi-valued functions, decision diagram optimization, and algorithmic methods in electronics. Notable contributions include the UDDP package and advancements in ternary logic systems through spectral translation techniques. Recent publications (2005-2007) emphasize decision diagram reduction, spectral methods, and stack filter analysis. She has contributed to 6 indexed journal/conference papers, with 1 in impact factor journals. No awards or advising roles explicitly stated in available data.
Natasha Z. Veljkovic is an Assistant Professor at the Faculty of Electronics, University of Nis, in the Department of Computer Engineering and Informatics, elected to this position in 2020 within the field of Computing and Informatics after serving as an assistant at the same institution since 2010. Her academic foundation includes: Graduation from the Faculty of Electronics in Niš (Department of Computer Engineering and Informatics) in 2009 Master's degree (institution implied as University of Nis) Doctorate (institution implied as University of Nis) Her research centers on digital governance innovation, specializing in how Web 2.0 frameworks and sensor technologies transform public administration through open data initiatives, environmental monitoring systems, and citizen engagement platforms. Her work critically examines transparency mechanisms and democratic participation in Balkan governmental contexts, particularly Serbia. Analysis of her 2011-2014 publications reveals consistent thematic progression from foundational open data catalogues toward integrated sensor-web applications and cross-national Web 2.0 adoption studies, demonstrating methodological evolution from theoretical frameworks to practical implementations in environmental and power systems monitoring. Scientific Recognition: No formal awards documented in source materials She actively participates in one national research project with no international collaborations noted. While her academic role implies student supervision, no specific advisees are listed in available records. Her impact factor journal publication count stands at one, reflecting selective high-impact contributions within her specialized domain. No dedicated laboratory or research team affiliations are specified in the provided documentation.
Mirjana Mikalacki is a Full Professor in the Department of Mathematics and Informatics at the Faculty of Sciences, University of Novi Sad. She has held academic positions since 2009, advancing from Teaching Assistant to her current rank. Her research focuses on positional games on graphs, discrete random structures, graph algorithms, and combinatorial optimization. She has organized multiple workshops, including the Novi Sad Workshop on Foundations of Computer Science (NSFOCS) series. Education: Ph.D. (2014) and B.Sc. (2007) in Computer Science from the University of Novi Sad. She has also attained advanced English language certifications (CPE, CAE, FCE) and holds proficiency in German and other Slavic languages. Her publications (15+ articles) span journals like Discrete Mathematics and Electronic Journal of Combinatorics , focusing on positional game strategies, graph algorithms, and combinatorial optimization. Recent work includes analysis of optimal paths in graphs and game dynamics in multi-stage and Walker-Breaker scenarios. No scientific awards explicitly mentioned. Her teaching includes courses in programming and informatics. She advises no listed students but collaborates on research projects involving graph theory and algorithmic game theory.
Srđan Trifunović is an Assistant Professor at the Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad. His research focuses on fluid-structure interaction, thermoelasticity, and nonlinear partial differential equations, with applications in mechanical and applied mathematics. He holds a Ph.D. and is affiliated with the Functional Analysis, Geometry and Topology research group. Education: Doctorate in Mathematics (Ph.D.) His research interests include the theoretical analysis of contact problems in fluid-structure systems, thermomechanical coupling in elastic materials, and the development of weak solution methodologies for complex multiphysics systems. Recent work explores time-periodic solutions in viscoelastic beam interactions and heat exchange dynamics in coupled fluid-plate systems. His articles (2020–2025) address fluid-structure interaction across compressible/incompressible fluids and thermoelastic plates/beams, emphasizing existence proofs, regularity, and asymptotic behavior. He has also contributed to damping analysis in wave equations and contact mechanics. No scientific awards or grants are explicitly listed in the provided data. He advises no students in the given texts. His consultations are conducted via email.
Andreja Stojić is an active academic researcher at Singidunum University in Belgrade, Serbia, specializing in atmospheric pollution modeling and environmental health. Her work integrates advanced machine learning techniques with traditional environmental science methodologies to address urban air quality challenges. Born January 3, 1976 in Jagodina, Serbia Doctoral studies (2007-2015) in Theoretical Physics/Atomic and Molecular Physics at University of Belgrade Bachelor studies (1998-2007) in Applied Physics and Informatics at University of Belgrade Her primary research focuses on atmospheric pollution dynamics, particularly PM2.5-bound polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and their health implications. She pioneers explainable artificial intelligence approaches for predicting pollutant behavior, including innovative applications of XGBoost, SHAP, and hybrid metaheuristics. Her work bridges environmental chemistry, computational modeling, and public health risk assessment. Analysis of her 15 most recent publications reveals a strong trend toward explainable AI frameworks for environmental systems, with increasing emphasis on PM2.5-bound pollutants, indoor-outdoor pollution transfer mechanisms, and VOC fate prediction. Her research consistently targets urban environments, particularly Belgrade, with growing international collaboration evident in Mediterranean marine pollution studies. While no specific scientific awards are documented in the provided materials, her extensive publication record in high-impact journals demonstrates significant scholarly contribution to environmental science. Dr. Stojić leads collaborative research projects involving multi-institutional teams across Serbia and international partners, focusing on atmospheric modeling and pollution source apportionment. Her work frequently employs receptor modeling techniques and advanced multivariate statistical methods for environmental data analysis. Her research infrastructure includes access to PTR-MS measurement systems and computational resources for developing AI-driven environmental models, with applications spanning urban air quality management to marine ecosystem contamination studies.
Aleksandar Đorđević is affiliated with Singidunum University, where he contributes to research in digital marketing, machine learning, and cybersecurity. His work spans academic publications in journals like Journal of Industrial Intelligence and Sustainable Cities and Society , as well as conference proceedings from events such as Sinteza and ICIST. He co-authored the textbook Digitalni marketing (2021) and has been actively involved in pandemic-related research, including predictive modeling for COVID-19 cases using hybrid algorithms. His research also explores Bitcoin price prediction via LSTM networks and fraud detection in digital advertising. Key areas of focus include cybersecurity applications of neural networks, optimization algorithms in healthcare, and entrepreneurship opportunities in emerging markets like the GCC region. Đorđević has collaborated on interdisciplinary projects involving data analysis, artificial intelligence, and sociological studies of pandemic impacts.
Jelena Gavrilović is an Assistant Professor at Singidunum University's Faculty of Informatics and Computing, specializing in Computer Science with a focus on cybersecurity, educational technology, and biometric systems. She holds a Doctoral degree in Advanced Protection Systems from Singidunum University (2022), preceded by a Master's in Contemporary Information Technologies (2011) and a Bachelor's in Programming and Design (2007). Education Background: High School: Srednja Tehnička PTT škola, Beograd (2002) Bachelor: Fakultet za informatiku i računarstvo, Programming and Design (2007) Master: Fakultet za informatiku i računarstvo, Contemporary Information Technologies (2011) PhD: Singidunum University, Advanced Protection Systems (2022) Research interests include cybersecurity frameworks, adaptive learning systems, and robust biometric authentication mechanisms. Her work combines technical innovation with pedagogical applications, such as integrating dynamic mathematics software into distance education platforms. Recent projects focus on drone forensics and multi-modal biometric systems for enhanced security. Notable contributions include studies on noise uncertainty in predictive systems (2015), comparative analysis of activity-based costing models in automotive industries (2011), and development of free mathematics education tools (2012). Her publications span academic journals like Journal of Mechatronics and conference proceedings such as Sinteza and ICETRAN. She actively contributes to Singidunum University's distance learning initiatives, emphasizing interoperability between educational software and modern e-learning architectures. Current projects explore hybrid optimization algorithms for healthcare applications and AI-driven path planning for mobile robots.
Bratislav B. Predic is a Full Professor in the Department of Computer Science at the Faculty of Electronic Engineering, University of Niš, elected to this rank in 2024 after serving since 2004 as an Assistant Trainee. His academic career spans two decades at the same institution within Serbia's premier technical university. He completed his Diploma, Master's, and PhD degrees in Electrical Engineering and Computing at the Electronic Faculty in Niš in 2003, establishing his foundational expertise in computational systems. Professor Predic's research focuses on the intersection of mobile computing and geospatial technologies, with significant contributions to context-aware GIS frameworks and transportation informatics. His work bridges theoretical computer science with practical field applications, particularly in real-time location systems and spatial data analysis for urban environments. Key innovations include motion prediction algorithms for public transit and optimized visualization techniques for mobile mapping. Analysis of his 2006-2007 publications reveals a concentrated research thrust in mobile GIS applications, characterized by three dominant themes: real-time vehicle tracking systems for public transportation, context-aware adaptation of geospatial services for mobile devices, and computational optimizations for terrain rendering and raster map visualization. These works demonstrate consistent methodological rigor in addressing latency and bandwidth constraints inherent in mobile geospatial computing. He currently leads 2 national and 1 international research projects, indicating active funding support for his work in transportation informatics and mobile computing. While no formal advisees are documented in the source material, his publications suggest collaborative supervision within multi-institutional research teams focused on geospatial technology deployment.
