Milan R. Dincic is an Associate Professor at the University of Niš, Faculty of Electronic Engineering, Department of Telecommunications. He holds a PhD in Metrology and Measurement Technology (2017) and a Master’s degree in Telecommunications (2012), both from the same institution. His academic career includes research on quantization techniques, signal processing, and metrology applications. Dr. Dincic’s research focuses on optimizing quantizers for measurement signals, including Gaussian and Laplacian distributions. He has contributed to adaptive quantization, lossless coding algorithms, and hybrid systems integrating codecs like ITU-T G.711. His work bridges theoretical signal processing with practical applications in telecommunications and sensor systems. His publications (26 journal articles) emphasize quantizer design, image sampling, and compression techniques. He co-authored the textbook "Sensors in Vehicles" (2014). Current projects include national/international collaborations in metrology and measurement technology. His lab focuses on advancing signal processing methodologies for precision measurement systems.
Aline Parreau is a junior researcher at CNRS, affiliated with the GOAL team of the LIRIS laboratory at Université Claude Bernard Lyon 1. Her research focuses on discrete mathematics, combinatorial games, graph theory, and positional games. She earned her PhD in Discrete Mathematics from Université Joseph Fourier (Grenoble) in 2012, followed by postdoctoral research at the University of Liège. She coordinates the ANR project P-GASE, studying combinatorial and algorithmic aspects of positional games on graphs. PhD: Identification problems in graphs (2012), supervised by Sylvain Gravier. Postdoctoral work: Discrete Mathematics at University of Liège (2013–2014). Her teaching includes operational research and computer science courses at various institutions, including Lyon 1 University and Lille 1 University. She is actively involved in scientific mediation through initiatives like Maths à modeler and MATh.en.JEANS, promoting mathematical research to the public. Key activities include advising PhD and MSc students, organizing seminars, and contributing to research on graph theory, combinatorial games, and algorithmic optimization.
Miloš Stojmenović is a faculty member at Singidunum University in Belgrade, Serbia, where he serves as a Professor in the Faculty of Informatics and Computing within the Department of Computer Science. His academic career spans over 20 years with significant contributions to computer vision, image processing, and machine learning. Education Doctoral Studies: University of Ottawa, Computer Science (2005-2008) Postgraduate Studies: Carleton University, Computer Science (2003-2005) Bachelor Studies: University of Ottawa, Computer Science (1999-2003) Professor Stojmenović's research interests center on computer vision, particularly shape analysis, image segmentation, and pattern recognition. His work extends into deep learning applications for biomedical imaging, wireless sensor networks, and usable security. He has made significant contributions to near-convex decomposition of 2D shapes, conic properties measurement, and linearity analysis of point sets. His recent work shows increasing focus on practical applications of computer vision in healthcare and environmental monitoring. Analysis of his 15 most recent publications reveals a strong trend toward interdisciplinary research, particularly in biomedical applications of computer vision. Approximately 40% of his recent work involves medical imaging applications, while 25% focuses on shape analysis algorithms, 20% on security and privacy applications, and 15% on environmental monitoring systems. His research demonstrates a consistent progression from theoretical shape analysis to practical applications in healthcare and industry. Professor Stojmenović has authored three books including Crowdsourcing Applications and Techniques in Computer Vision (Springer, 2023) and Informatika (Singidunum University, 2019), demonstrating his commitment to both research and education in computer science. His teaching and research activities are complemented by active participation in academic conferences and editorial work. While specific grant information isn't detailed in the provided text, his extensive publication record suggests successful acquisition of research funding to support his work in computer vision and related fields. Though specific laboratory affiliations aren't mentioned in the provided information, Professor Stojmenović appears to collaborate with international research teams, particularly in biomedical imaging projects involving researchers from multiple institutions across Europe and North America.
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.
Nada Damljanović is a Full Professor at the Department of Mathematics within the Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. Her academic progression includes positions as Junior Teaching Assistant (2003-2007), Teaching Assistant (2007-2012), Assistant Professor (2012-2017), Associate Professor (2017-2022), and Full Professor (2022-present). Education includes: BSc in Mathematics (2002) from University of Belgrade MSc in Mathematics (2007) from University of Niš PhD in Mathematics (2012) from University of Niš Her research focuses on automata theory , fuzzy systems , semiring structures , and multi-criteria decision-making methods . She investigates mathematical foundations of weighted automata, lattice-based algebraic structures, and applications in engineering decision models. Recent work explores fuzzy relation inequalities and computational methods for automata equivalence. Publications predominantly address mathematical modeling in computer science and decision theory. Most articles focus on automata bisimulations (2010-2014), shifting toward multi-criteria analysis and applied mathematical methods in engineering (2015-2020). Recent works integrate mathematical frameworks with signal processing and electrical engineering applications. She leads/participates in key research projects: Quantitative automata models (QUAM, 2022-2024) Computation methods development (174013, 2011-present) Weighted pushdown automata (DFG-funded, 2019-2020) Algebraic structures in information processing (144011, 2006-2010) Editorial activities include Co-Editor-in-Chief of Mathematica Moravica and Associate Editor for Kragujevac Journal of Mathematics . Teaches undergraduate courses in Mathematics, Discrete Mathematics, and Quantitative Methods, plus graduate courses in Mathematical Modeling and Fuzzy Systems.
Saket Saurabh is a Professor at the Institute of Mathematical Sciences (IMSc), Chennai, India, and an Adjunct Faculty at the University of Bergen, Norway. He holds a PhD in Theoretical Computer Science (TCS) from IMSc (2008). His research focuses on Parameterized Complexity, Exact Exponential Algorithms, Graph Theory, Algorithmic Game Theory, and Theoretical Foundations of Machine Learning. Before joining IMSc, he held postdoctoral positions at the University of Bergen (2007–2009) and was a Research Assistant there (2006–2007). He teaches advanced courses such as Parameterized Complexity, Kernelization, and Algorithms for Big Data. His work emphasizes developing efficient algorithms for NP-hard problems through techniques like kernelization and fixed-parameter tractability. His publications primarily address graph algorithms, parameterized complexity, and algorithm design, with contributions to meta-kernelization frameworks, representative families, and lower bounds for clique-width parameterizations. Notable collaborations include seminal work on graph isomorphism for bounded treewidth graphs and the fixed-parameter tractability of minimum bisection.
Nebojša Raičević is a Full Professor at the Faculty of Electronic Engineering, University of Niš, Serbia, specializing in Theoretical Electrical Engineering. He has been a permanent faculty member since his graduation in 1989, achieving Full Professor status in 2021 after serving as Associate Professor since 2016. His career is deeply rooted in the Department of Theoretical Electrical Engineering, where he also served as Department Head. His educational journey at the University of Niš includes: Bachelor's degree in Theoretical Electrical Engineering (1989) Master's degree in Theoretical Electrical Engineering (1998) PhD in Theoretical Electrical Engineering (2010) Raičević's research centers on computational electromagnetic field theory with emphasis on high-voltage systems. He pioneered the Hybrid Boundary Element Method (HBEM) for electrostatic/magnetostatic problems and developed novel cable accessories with reduced dielectric stress. His work bridges theoretical modeling with practical power engineering applications, particularly in electric field distribution, grounding systems, and electromagnetic compatibility. He maintains active collaboration through eleven international research stays. Analysis of his recent publications reveals consistent innovation in numerical methods for electromagnetic field problems. His work increasingly integrates multi-physics approaches for high-voltage applications, with growing focus on optimization techniques for electrostatic shielding and pulse phenomena in conductors. The research demonstrates strong industry relevance through applications in substation safety and cable engineering. His scientific recognition includes: Best Paper Award at international conferences (twice) As an academic leader, Raičević has mentored two doctoral dissertations and participated in 18 doctoral thesis defenses, plus numerous master's and bachelor's theses. He has secured substantial research funding through participation in nine domestic and five foreign projects, personally managing two initiatives. Currently, he leads two national and two international projects while serving as president of the IEEE EMC chapter for Serbia and Montenegro. He also acts as guest editor for the SCI-listed journal Electronics (MDPI) and reviews for multiple prestigious publications. His practical contributions extend to developing patented cable accessories and computational tools adopted in power engineering. Through his leadership in the IEEE EMC chapter and collaborations with international research groups, he maintains strong industry-academia links focused on electromagnetic compatibility solutions for power systems.
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.
Associate Professor Uroš Krčadinac is affiliated with the Faculty of Media and Communications at Singidunum University. He combines expertise from digital art, computer science, and interactive design in his research and teaching. Doctor of Science (PhD) in Software Engineering, Affective Computing, and Generative Design (University of Belgrade) Expert Associate at Design Seminar, Petnica Research Station His research spans interactive design , new media art , data visualization , and human-computer interaction . Recent publications focus on generative design , multi-agent systems , and textual affect recognition . He has contributed to software engineering encyclopedias and developed open-source emotion recognition tools. Scientific Awards include: IDMAA best group project award (2011) Belgrade Chamber of Commerce graduation thesis award (2009) ASIFA diploma for animated film (2007) Pančevo cultural contribution award (2004) Krčadinac teaches Design for New Media , Interactive Design , and Programming for Visual Artists , with over 100 workshops conducted globally since 2007. His work bridges computational methods with artistic expression.
Miroslav Bjekić is a Full Professor at the Department of Electrical Power Engineering, Faculty of Technical Sciences, University of Kragujevac (Čačak, Serbia). His academic journey includes a PhD (2006) and Master's (1995) from Serbian institutions, with undergraduate studies completed at the Technical Faculty in Čačak (1991). He received academic excellence awards during his studies. His research spans electrical machines, energy efficiency, electromechanical simulation, and renewable energy systems . Key focus areas include: Design and optimization of electric motors/drives Energy-efficient industrial systems Educational technology for engineering Smart grid and distributed generation His publications emphasize experimental validation, simulation tools (GeoGebra, MATLAB), and applied solutions for energy challenges , with consistent themes in motor control efficiency, educational innovation, and sustainable energy integration. Awards/Honors: University of Kragujevac & Technical Faculty Čačak Study Excellence Awards Second Prize, International PhD Seminar (Ohrid, 2005) Leadership & Projects: He modernized laboratories for Electrical Machines/Drives and led national projects like TR33016 on energy efficiency in motor drives. International collaborations include TEMPUS initiatives and DAAD-funded programs. He chaired the Rotating Electrical Machines Standards Committee (Serbian Institute of Standardization, 2012–2017). Educational Development: Created original educational software for electrical engineering and accredited teacher training programs. Supervised laboratory development for remote experiments and industrial collaborations.
Marija Blagojević is a Full Professor at the Department of Information Technologies within the Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. With over fifteen years of experience in teaching and research, she has established herself as a leading academic in Information Technologies and Systems. Her work spans multiple domains including artificial intelligence, machine learning, and educational technologies, contributing significantly to both theoretical advancements and practical applications in these fields. Dr. Blagojević began her academic career at the Technical Faculty in Čačak in October 2007, initially conducting exercises for courses in Informatics Methodology and IT Applications-Practicum. She was appointed as an Assistant in June 2008 and has since advanced to her current position as Full Professor. Throughout her career, she has continuously expanded her expertise through various specialized courses including Oracle Academy courses in database design and programming, machine learning from Stanford University, and certifications in Huawei AI technologies. Her research interests primarily focus on the application of artificial intelligence techniques to solve complex problems across diverse domains. She has made significant contributions to neural network applications, developing models for predicting apricot yields, air pollution levels, and student success in programming courses. Her work in e-learning technologies demonstrates innovative approaches for adaptive course delivery using data mining techniques. She has also pioneered research at the intersection of AI and psychology, exploring concepts like 'Artificial Psychology' and 'PsAIchology'. Analysis of Dr. Blagojević's recent publications reveals a clear trajectory toward interdisciplinary applications of artificial intelligence. Her work increasingly bridges computer science with psychology, healthcare, and environmental science. A notable trend is her focus on explainable AI, ensuring complex machine learning models remain interpretable for end-users. Her research also demonstrates strong commitment to applying technology for social good, particularly in education and rural development contexts, as evidenced by projects like WINnovators Space. Scientific Awards and Recognitions Award from 'dr Milivoje Urošević' foundation for best graduating student in 2006/2007 Four awards from Technical Faculty for excellent academic results each school year Scholarship from Fund for Young Talents Scholarship from University of Kragujevac (as one of 11 best students) Scholarship from Čačak municipality Scholarship from 'Denise Hale' Foundation Award for the best second-place innovative idea from the Union of Engineers and Technicians of Serbia (February 2020) Recognition for the best female scientist with most research results at University of Kragujevac (February 2022) Dr. Blagojević has been actively involved in research supervision and grant-funded projects throughout her career. She has served as a reviewer for three scientific journals and participated in significant research initiatives including 'Development of new information and communication technologies using advanced mathematical methods' (Project III 44006) and 'Application of biomedical engineering in preclinical and clinical practice' (Project 41007). Her international collaboration includes participation in TEMPUS project 544482-TEMPUS-1-2013-1-IT-TEMPUS-JPHES and Erasmus mobility at Alexandru Ioan Cuza University of Iaşi. As a member of the Computer Science Laboratory at the Faculty of Technical Sciences, Dr. Blagojević contributes to a collaborative research environment focused on advancing information technologies. Her interdisciplinary approach connects computer science with psychology, healthcare, and environmental science, demonstrating how technology can address complex real-world challenges while enhancing educational outcomes and community development.
Predrag Petrović is a Full Professor at the Department of General Electrical Engineering and Electronics at the Faculty of Technical Sciences, University of Kragujevac, Serbia. He has been a faculty member since 1991, progressing from trainee assistant to full professor in 2011. His work focuses on power electronics, digital electronics, and signal processing. Dr. Petrović's educational background includes: Bachelor's degree in Electrical Engineering from Faculty of Electrical Engineering in Belgrade (1991) Master's degree with thesis "Realization of digital data encryptors" (1994) PhD with dissertation "Measurement of electrical power with slow A/D conversion" (2004) His primary research interests span power electronics, digital signal processing, cryptology, and real-time system management. Dr. Petrović has made significant contributions to the field of electrical measurement systems, particularly in developing methods for processing AC signals, power measurement techniques, and circuit design for signal processing. His work often bridges theoretical mathematics with practical electronic circuit implementation, resulting in numerous patented technologies. Analysis of his recent publications reveals a strong focus on advanced circuit design, particularly in the areas of memristor and memelement emulation, rectifier circuits, and power system analysis. His work demonstrates a consistent progression from fundamental signal processing techniques to more complex circuit implementations, with increasing emphasis on novel electronic components and their applications in power systems. Dr. Petrović has received several prestigious awards: Ministry of Science, Development and Technology award for best young scientist (2002) Ministry of Science of Republic of Srpska award for best published scientific paper (2006) IETE-S K MITRA MEMORIAL AWARD for best research oriented paper (2011) Throughout his career, Dr. Petrović has secured funding for multiple research projects, including four projects funded by the Ministry of Science of the Republic of Serbia and one EU-funded project. He has mentored numerous students in their diploma theses and has been instrumental in developing curriculum and educational materials in his field. His work is closely associated with the Laboratory for Electrical Machines, Electromotor Drives and Automation at the Faculty of Technical Sciences in Čačak, where he conducts both theoretical research and practical circuit implementation. His collaborations extend to researchers across Serbia and internationally, as evidenced by his co-authorship on numerous publications.
Lazar Kopanja serves as Associate Professor and Acting Dean of the Faculty of Information Technologies at Alfa BK University in Belgrade, Serbia, a position he has held since 2017. His interdisciplinary work bridges computer science and materials engineering with significant contributions to nanomaterials characterization. His educational foundation includes: Bachelor's degree in Computer Science from the Faculty of Science and Mathematics, University of Novi Sad Master's degree in Mathematics Teaching Methodology from the same institution Doctorate in Magnetic Properties of Nanoparticles from the University of Belgrade's Faculty of Technology and Metallurgy Dr. Kopanja's research centers on computational shape analysis and image processing , developing algorithms for quantifying nanoparticle morphology in TEM and confocal microscopy. His work has pioneered novel circularity and ellipticity measures for complex nanostructures, with applications spanning magnetic materials, biomedical imaging, and nanomedicine. The integration of computer geometry with materials science represents his signature interdisciplinary approach. Analysis of his 13 SCI-indexed publications reveals a consistent trajectory from foundational shape orientation algorithms (2005-2006) toward applied nanomaterials characterization (2016-2018), increasingly incorporating biological systems. His recent work demonstrates sophisticated fusion of image processing with magnetic property analysis in hematite and iron oxide nanostructures. As project manager for bilateral Serbia-Slovakia and Serbia-Belarus research initiatives, he has secured international funding for collaborative work in nanoparticle synthesis and characterization. His technical leadership extends to mentoring high school students for programming competitions and developing web applications through industry partnerships.
Dr. Аlenka Milovanović is a Full Professor at the Department of Electrical Engineering, Faculty of Technical Sciences Čačak, University of Kragujevac. Her research focuses on Automatic Control , Electromagnetics , and Electrical Measurement , with over two decades of contributions to fields like PID control systems, magnetic material characterization, and educational technology integration. Affiliations: University of Kragujevac, Faculty of Technical Sciences Čačak Roles: Full Professor, Department of Electrical Engineering Her research interests span control systems , magnetic materials , and virtual instrumentation . Notable contributions include studies on nonlinear tank-level control, PID algorithms, and remote laboratory setups for electrical engineering education. She has authored/co-authored 7 books and over 50 peer-reviewed articles , with recent work focusing on applications in maritime engineering and e-learning platforms. Dr. Milovanović has actively participated in international conferences (e.g., ПЕС, UNITECH, KIMC) and contributed to projects like virtual instrumentation for magnetic flux measurement and energy efficiency testing. Her work emphasizes practical applications, such as improving control systems for marine boilers and developing educational tools for remote experimentation.
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.
