Miloš Matejić serves as an Associate Professor at the University of Kragujevac's Faculty of Engineering Sciences, within the Department of Mechanical Constructions and Mechanization. His academic position involves active research and teaching in mechanical systems design. Research interests center on advanced mechanical engineering topics including: Cycloid drive efficiency optimization and stress analysis Tribological testing methodologies and material interactions Computational modeling of gear systems using FEM Parametric design automation for mechanical components Composite materials performance in dynamic applications Recent publications demonstrate strong focus on experimental validation of cycloid reducers, novel tribometers, and material optimization. No awards, student advisories, or grant activities are documented in available sources. Institutional collaboration occurs through the Faculty of Engineering Sciences' laboratories and research centers.
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.
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.
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.
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).
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.
Milenko Sekulić is a Full Professor at the Chair of Machining within the Department of Production Engineering, Faculty of Technical Sciences, University of Novi Sad. He has held this position since 2017 and currently serves as Head of the Chair of Machining (since 2018), following previous roles as Associate Professor (2012-2017) and Assistant Professor (2008-2012) at the same institution. His academic foundation includes a Bachelor's degree (1993), Magister degree (1998), and PhD (2007), all in Mechanical Engineering from the Faculty of Technical Sciences. His educational journey focused on cutting force analysis in milling, development of cutting force calculation models, and determination of drilling forces. Professor Sekulić's research centers on advanced manufacturing engineering, specializing in machining process optimization, thermal analysis, and cutting force prediction. His work integrates fuzzy logic, evolutionary algorithms, and response surface methodology to solve complex problems in electrical discharge machining, abrasive water jet systems, and high-pressure jet assisted turning. Key contributions include energy efficiency models for EDM, surface roughness prediction frameworks, and thermal state optimization in creep-feed grinding. Analysis of his 15 most recent publications reveals a strong trend toward sustainable and intelligent manufacturing solutions. His work consistently addresses material-specific challenges (particularly nickel-based alloys), develops predictive models for machining outcomes, and pioneers hybrid techniques like laser-assisted cutting. The research demonstrates increasing sophistication in combining computational intelligence with traditional manufacturing physics. No scientific awards or fellowships are documented in the available information. Professor Sekulić actively mentors students through thesis supervision and teaching, building on his own academic progression within the institution. His leadership as Head of Chair involves guiding research direction and laboratory activities for the machining group. International collaborations with Slovenian institutions (evident in co-authored publications) highlight his cross-border research engagement. He leads the Chair of Machining research team, which maintains specialized laboratories for conventional and non-conventional machining processes including EDM, water jet systems, and high-pressure jet assisted equipment. Current work focuses on AI-driven process optimization and sustainable manufacturing techniques.
Dr. Deјan Veljković is an Assistant Professor at the Department of Mechatronics , Faculty of Technical Sciences Čačak , University of Kragujevac. He has held academic positions at institutions such as the Higher School of Shipping Belgrade (2017–2020) and has been actively involved in research since 1996. His expertise includes experimental research, material characterization, and vibration-based diagnostics. Education: Bachelor's, Master's, and PhD in Applied Mechanics and Automatic Control, Faculty of Mechanical Engineering, University of Kragujevac. Research Interests: Focus on thermoviscoplasticity of metals/composites, hyperelastic materials (rubber, soft tissues), nonlinear optimization in applied mechanics, and adaptive algorithms for vibration analysis. His work addresses critical issues in industrial machinery diagnostics and biomechanical systems. Research Trends in Publications: Contributions span vibration-based condition monitoring, material behavior modeling, and biomedical applications. Notable areas include adaptive order tracking techniques for rotating machinery and hyperelastic modeling of biological tissues. Awards: Twice awarded for academic excellence during undergraduate studies (1996, 2001). Scholarship holder for doctoral research (Ministry of Science and Technology of Serbia, 2006–2007). Advising & Projects: Extensive involvement in national research projects (e.g., thermoviscoplasticity studies, biomechanical software development). No formally listed advisees, but collaborative research with multiple institutions including BIOIRC and Jaroslav Černi Institute. Labs & Teams: Associated with the Faculty of Technical Sciences Čačak laboratories and the BIOIRC Research and Development Center for interdisciplinary projects in engineering and biomechanics.
Miroslav Popović is an academic affiliated with Singidunum University's Faculty of Informatics and Computing . His expertise spans nuclear engineering, materials science, environmental engineering, and medical research. He holds a PhD from the University of California, Berkeley (2013–2017) in Nuclear Engineering, and bachelor's degrees in Physics (2000–2009) and Chemistry (2000–2004) from the University of Belgrade. His research focuses on advanced materials for nuclear applications , environmental sustainability , and medical technologies . Key projects include corrosion studies in liquid metals (e.g., Pb-Bi eutectic), AI-driven waste classification systems, and clinical trials for scoliosis treatments. He has authored/co-authored over 30 peer-reviewed articles and a textbook Prirodni hazard (2024). Recent work highlights: Convolutional neural networks for waste management (2025) Randomized controlled trial for Schroth Method in adolescent scoliosis (2025) Hydrometallurgical recovery of metals from tailings (2024) Structural analysis of tungsten under helium ion irradiation (2022) He collaborates with institutions like UC Berkeley and the Serbian Academy of Sciences. No awards or grants are explicitly listed, though his prolific publication record indicates active research funding.
Vladimir Zlokolica is a researcher affiliated with Singidunum University, holding a PhD in Telecommunications and Information Processing from Ghent University (2006) and a Master's degree from the same institution (2005). He obtained his Bachelor's degree in Electrical Engineering from Novi Sad (2001). His research focuses on Medical Imaging , Computer Vision , and Automotive Perception Systems , particularly in advanced image processing techniques for 3D medical imaging and motor vehicle environmental modeling. His work includes segmentation algorithms for cardiovascular diagnostics and innovative methods for automotive image generation and enhancement. Publications from 2017-2020 demonstrate expertise in 3D image analysis , medical applications , and automotive vision systems . Notable contributions include techniques for left atrial appendage segmentation, vessel delineation, and quality metrics for 3D visual content. Despite no explicit scientific awards mentioned, his collaborations with institutions like Ghent University and Singidunum University highlight his academic engagement.
Emilija N. Zivanovic is an Associate Professor at the Faculty of Electronic Engineering, University of Nis, specializing in Applied Physics. She holds a PhD (2014), Master's (2004), and Bachelor's (1999) degrees in Applied Physics from the same institution. Her research focuses on plasma physics, electrical breakdown phenomena, and gas discharge dynamics. She has authored/co-authored 11 impact-factor papers on topics like xenon-filled tube dosimetry, nitrogen afterglow processes, and combined gas-vacuum breakdown mechanisms. Professional Activities: Member of IEEE and the Serbian Society of Physicists (Plasma and Ionized Gas Physics Department). Currently involved in 2 national research projects. Publications accessible at npao.ni.ac.rs . Research Interests: Statistical analysis of electrical breakdown parameters, memory effect mechanisms in gases, radiation dosimetry applications, and ionization processes in low-pressure environments. Her work bridges plasma physics with engineering applications through experimental and theoretical studies. Key Contributions: Pioneered studies on xenon-filled tube dosimetry for low-dose gamma radiation, established methodologies for analyzing nitrogen memory effects, and developed models for combined gas-vacuum breakdown mechanisms in various gas environments.
Prof. Dr Karlo Raić is a full Professor at the Department of Metallurgical Engineering , Faculty of Technology and Metallurgy , University of Belgrade . His academic career spans over three decades with a focus on metallurgical and materials engineering . Teaching: Surface Engineering, Iron and Steel Metallurgy, Welding Physics, Transport Phenomena Research: Metal-ceramic interfaces, dental biomaterials, composite materials, CFD analysis Publications: 20+ journal articles (Metallurgical and Materials Engineering, Metals, Surface Engineering) Research Trends : Recent work emphasizes dental metallic materials and metal-ceramic joining with active filler metals. He investigates additive manufacturing of dental alloys, wetting phenomena at liquid metal/ceramic interfaces, and CFD modeling of metallurgical processes. Project Leadership : • Thermal Barrier Coatings (2002-2005) • Nanostructured Materials Synthesis (2006-2010) • Metal Matrix Composites (2011-2015) International Collaboration : DAAD fellowship (Germany), Max Planck Institute (Germany), Washington State University (USA), Montanuniversität Leoben (Austria).
Gordana Jovanović is a researcher at Singidunum University with expertise in environmental chemistry and pollution analysis. She holds a PhD in Environmental Chemistry from the University of Belgrade (2012–2015), followed by postdoctoral research at the Institute for Medical Research and Occupational Health in Zagreb (2017–2018). Her research focuses on persistent organic pollutants (POPs), polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs), with applications in air quality, indoor/outdoor environmental fate, and human health risk assessment. She employs advanced methods like machine learning (XGBoost, SHAP) and metaheuristics for predictive modeling of pollutant behavior. Key contributions include studies on PCBs and OCPs in breast milk, fish, and soil-plant-air systems, as well as biomonitoring using mosses and tree leaves. Her work bridges environmental chemistry, toxicology, and AI-driven analytics, addressing global challenges in pollution management and public health.
Nebojša S. Doncov is a Full Professor at the Faculty of Electronics, University of Niš, Serbia, where he is affiliated with the Department of Telecommunications. He has been a leading academic and researcher in computational electromagnetics and antenna systems since earning his PhD in 2002 from the same institution. His research interests include: Computational Electromagnetics, particularly the Cylindrical TLM Method Antenna Design and Optimization using AI and Neural Networks Wearable and Smart Textile Antennas Direction of Arrival (DoA) Estimation Electromagnetic Compatibility and High-Frequency Modeling Biomedical and UAV-based GPR Applications His recent publications show a strong trend toward integrating artificial intelligence with electromagnetic modeling, especially in wearable and conformal antenna systems. He has published extensively in top IEEE and Wiley journals, with a focus on numerical methods and practical antenna applications for wireless and biomedical systems. His scientific awards include: URSI Young Scientist Award (2002) Aleksandar Marinčić Award (2017) Best Diploma Thesis Award (1995) Early Graduation Charter (1995) He has led or participated in numerous national and international research projects, including NATO Science for Peace, Royal Society International Exchange, and multiple COST Actions. He has advised students through research collaborations and co-authored works, though no formal list is provided. He has also contributed to academic education through textbooks and problem collections. He is actively involved in research labs and teams, including the Serbian research teams in SmartBridges, Predictive Design of Wearable Antennas, and Advanced UAV-Based GPR Imaging. He collaborates with institutions such as WIPL-D, University of Nottingham, and Technical University of Munich.
Dr. Dragan Rodić is an Associate Professor at the Faculty of Technical Sciences , University of Novi Sad, affiliated with the Department of Production Engineering and the Chair of Machining . His career spans roles from Research Associate to Assistant Professor, culminating in his current position since 2025. He serves as Secretary of the Chair since 2020. Dr. Rodić’s research focuses on advanced machining processes , particularly electrical discharge machining (EDM) of nonconductive materials. He employs fuzzy logic and ANFIS systems for modeling tool wear, cutting forces, and thermal behavior. His work addresses energy efficiency in machining, sustainable production, and optimization of abrasive water jet cutting. His publications (2013–2022) reveal a consistent emphasis on thermal analysis , surface roughness prediction , and intelligent optimization in manufacturing. Key subfields include EDM of ceramics, jet-assisted turning, and inverse heat transfer modeling. Dr. Rodić contributes to international journals like Neural Computing and Applications and Journal of Cleaner Production , with collaborations across departments. His work bridges theoretical models and practical industrial applications in manufacturing engineering.
