جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Optimization
• Machine Learning
• +۷ مورد دیگر

Sebastian Pokutta is a Professor at Technische Universität Berlin, Vice President at the Zuse Institute Berlin (ZIB), and Chair of the Cluster of Excellence MATH+ and MODAL. His research lies at the intersection of Artificial Intelligence, Optimization, and Machine Learning, with applications in sustainability, quantum computing, and mathematical discovery. Research Interests: Development of novel optimization algorithms, particularly Frank-Wolfe and Conditional Gradient methods. Integration of machine learning with decision-making and combinatorial optimization. AI for Science (AI4Science), including applications in quantum mechanics and ecology. AI and creativity, human-AI co-creativity, and social science modeling using multi-agent LLMs. His recent publications (2025) demonstrate a strong focus on scalable optimization, interpretability, and algorithmic foundations. The work spans theoretical advances in convergence analysis, practical implementations in Julia (FrankWolfe.jl), and real-world deployments in biomass estimation and quantum certification. Scientific Awards: Gödel Prize (2023) STOC Test of Time Award (2022) Science Prize of the Association for Pediatric Orthopedics (2025) Google Research Awards (2021, 2020) NSF CAREER Award (2015) He advises a vibrant research group, with former students and postdocs securing faculty positions at institutions like Inria, Carlos III University, and James Madison University. His group has received funding from Google, DFG, and Math+, and he leads major collaborative efforts such as the Thematic Einstein Semester on Mathematical Optimization for Machine Learning. Labs and Teams: Interactive Optimization and Learning Lab at TU Berlin and ZIB. Leadership in MODAL and MATH+ research clusters, fostering interdisciplinary collaboration in mathematical optimization and AI.

• Optimization for Machine Learning
• Collaborative Learning
• Federated Learning
• +۶ مورد دیگر

Sebastian U. Stich is a tenured Professor at CISPA Helmholtz Center for Information Security and a member of the European Lab for Learning and Intelligent Systems (ELLIS). His research focuses on optimization for machine learning, collaborative learning (distributed, federated, and decentralized methods), efficient optimization techniques, adaptive stochastic methods, and privacy/security in machine learning. Recent appointments include ERC Consolidator Grant 2024 for the CollectiveMinds project. Key contributions in federated/decentralized learning, uncertainty estimation, and communication-efficient optimization. Active in workshop organization, including the Optimization for Machine Learning workshop at NeurIPS 2024. Teaching modern optimization methods at Saarland University (2023-2025). His work has been recognized with awards such as the Google Research Scholar Award (2023) and Meta Privacy-Enhancing Technologies Award (2022) . His research group includes postdocs Dr. Anton Rodomanov and Dr. Rotem Mulayoff, and PhD students Xiaowen Jiang and Yuan Gao.

• Control Systems
• Machine Learning
• Robotics
• +۶ مورد دیگر

Marko Tanasković is a researcher at Singidunum University's Faculty of Informatics and Computing, specializing in control systems, robotics, and electrical engineering. He holds a PhD from ETH Zurich (2015) in Information Technology and Electrical Engineering, following degrees from University of Belgrade (BEng, 2009) and ETH Zurich (MEng, 2011). His research focuses on adaptive control systems, machine learning applications in engineering, and sensorless motor control. Key contributions include: Development of predictive algorithms for traffic systems and industrial automation Innovations in rotor orientation determination for PMSM motors Integration of AI in fraud detection and building climate control Recent work includes a 2024 study on wearable health monitoring devices and a 2022 paper on drone forensics. He has authored/co-authored over 15 peer-reviewed articles and holds patents in motor control technologies. Current affiliations include Singidunum University's Department of Electrical Engineering and Collaboration with ETH Zurich alumni networks. Active in international conferences such as Sinteza and IEEE events.

• Mechanical Engineering
• Machine Design
• Tribology
• +۴ مورد دیگر

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.

Luis Barbaمشاهده پروفایل

پژوهشگر ارشد

• Computational Geometry
• Algorithms
• Graph Theory
• +۴ مورد دیگر

Luis Barba is a Research Fellow in the Machine Learning and Optimization group at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, working under Professor Martin Jaggi. He completed his PhD through a cotutelle program between Carleton University, Ottawa and Université Libre de Bruxelles, Brussels, supervised by Professors Stefan Langerman, Jit Bose, Pat Morin and Vida Dujmović. Prior to that, he earned his master's degree at Universidad Nacional Autónoma de México (UNAM) under Professor Jorge Urrutia. Dr. Barba's research spans computational geometry, algorithms, graph theory, and more recently, machine learning and optimization. His work addresses fundamental problems in geometric data structures, Voronoi diagrams, graph coloring, and distributed learning. He has made significant contributions to understanding time-space trade-offs in geometric algorithms and developing efficient methods for problems like geodesic Voronoi diagrams and dynamic graph coloring. Dr. Barba's publication record demonstrates a clear evolution from theoretical computational geometry to practical applications in machine learning. Early in his career, he focused on fundamental geometric problems including linear-time algorithms for geodesic Voronoi diagrams and efficient convex hull computation in polygonal domains with obstacles. More recently, his work has shifted toward machine learning, where he has developed novel optimization techniques for distributed and federated learning settings, including implicit gradient alignment methods and multilayer lookahead approaches. Dr. Barba has published extensively in top-tier conferences and journals including Symposium on Computational Geometry (SoCG), Canadian Conference on Computational Geometry (CCCG), Algorithmica, and Discrete and Computational Geometry. His collaborative work demonstrates strong connections across the computational geometry and algorithms communities, with frequent co-authorship with leading researchers in these fields. Throughout his career, Dr. Barba has maintained a consistent focus on algorithmic efficiency and computational complexity, whether addressing theoretical geometric problems or practical machine learning challenges. His work exemplifies how deep theoretical insights can inform practical computational approaches across different domains of computer science.

Đorđević Markoمشاهده پروفایل

دانشیار

• Computational Biology
• Systems Biology
• Infectious Diseases
• +۷ مورد دیگر

Marko Djordjevic is an Associate Professor at the Faculty of Biology, University of Belgrade. His research spans computational biology of infectious diseases, bacterial immune systems (CRISPR/Cas and restriction-modification systems), and quantitative understanding of infection progression with applications to SARS-CoV-2 and computational physics of quark-gluon plasma. Diploma in Physics, Faculty of Physics, University of Belgrade, Serbia. PhD in Biophysics and Bioinformatics, Department of Physics, Columbia University, USA. Postdoctoral training at the Mathematical Biosciences Institute, Ohio State University, USA. Djordjevic's research focuses on nonlinear regulatory dynamics of bacterial immune systems, their role in horizontal gene transfer, and modeling infection progression under social mitigation measures. His secondary interest in computational physics examines quark-gluon plasma dynamics via high-p⊥ observables and tomography. His recent publications address CRISPR/Cas regulation, restriction-modification systems, and SARS-CoV-2 transmissibility drivers. Grants from the Serbian Ministry of Science, Science Fund of Serbia, EU Marie Curie IRG, and Swiss National Science Foundation support his work.

• Organic Chemistry
• Polymer Chemistry
• Analytical Chemistry
• +۳ مورد دیگر

Dr. Aleksandra D. Mitrović serves as an Assistant Professor in the Department of Organic Chemistry at the Faculty of Chemistry, University of Belgrade, a position she has held since 2019. Her academic journey began with undergraduate studies in Chemical Sciences at the same institution (2004-2010), followed by doctoral research completed in 2017. Her educational background includes: Undergraduate studies in Chemical Sciences, University of Belgrade - Faculty of Chemistry (2004-2010) Doctorate in Chemical Sciences, University of Belgrade - Faculty of Chemistry (2009-2017) Dr. Mitrović's research spans Organic Chemistry, Polymer Chemistry, and Analytical Chemistry, with significant contributions to nanomolecular machine design, carbon material modification, and environmental pollutant analysis. Her work bridges synthetic chemistry with practical applications in security and health. Recent publications demonstrate growing emphasis on micro/nano-plastic toxicity and enzyme-based material engineering, reflecting interdisciplinary collaboration across European research consortia. Her scientific achievements have been recognized through competitive awards: DAAD scholarship (2012) for research at Friedrich-Alexander University Humboldt postdoctoral scholarship (2018) Alexander von Humboldt Foundation research grant (2019) Current research is supported by major grants including IMPTOX (2021-2025), a Horizon 2020 project investigating microplastic-allergy links funded by the European Commission, and previous OPCW-funded work on chemical warfare agent detection. She also led a Philip Morris-funded project on enzymatic carbon material modification (2019-2020). As a member of the Faculty Council since 2023 and active participant in the Serbian Chemical Society and Humboldt Club Serbia, she contributes to institutional governance and international scientific exchange.

• Mechanical Engineering
• Machine Structures
• Mechanization
• +۵ 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.

• Production Engineering
• Industrial Engineering
• Materials Science
• +۵ مورد دیگر

Dragan Adamović is a Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac. His work focuses on manufacturing processes, materials science, tribology, and biomaterials. He has extensive experience in numerical modeling of metal forming processes like ironing and deep drawing, with a strong emphasis on optimizing mechanical properties through thermal treatments and surface treatments such as shot peening. His research integrates computational methods (e.g., FEA) with experimental validation, addressing challenges in automotive engineering, biomedical applications, and industrial safety. Notable contributions include studies on friction coefficient determination in forming processes, wear behavior of alloyed steels, and the development of biodegradable metallic implants. He also investigates occupational safety in industries like concrete production and bakery environments. Adamović has authored over 50 peer-reviewed articles since 2003, covering topics from welding technologies to additive manufacturing applications. His work bridges theoretical material science with practical industrial solutions, emphasizing sustainability and process efficiency in modern production systems.

• Control Systems
• Machine Learning
• Electrical Engineering
• +۴ مورد دیگر

Marko Tanasković (born December 6, 1986) is a researcher at Singidunum University with a PhD in Information Technology and Electrical Engineering from ETH Zurich (2015). His academic background includes master's (ETH Zurich, 2011) and bachelor's (University of Belgrade, 2009) studies in Electrical Engineering. Doctoral studies: Information Technology and Electrical Engineering, ETH Zurich (2011-2015) Master studies: Information Technology and Electrical Engineering, ETH Zurich (2009-2011) Basic studies: Electrical Engineering, University of Belgrade (2005-2009) Tanasković's research focuses on control systems , predictive modeling , and optimization algorithms for mechanical and electrical systems. His work addresses adaptive model predictive control (MPC), sensorless motor positioning, and data-driven approaches for nonlinear systems. Recent publications (2018-2024) demonstrate expertise in: Embedded control systems (rotor polarity detection) Drone forensics and autonomous navigation Industrial automation (LabVIEW applications) Biomedical sensor development ('Smart Anklet') Machine learning optimization (firefly algorithm)

• Vehicle Dynamics
• Noise, Vibration and Harshness (NVH)
• Automotive Engineering
• +۵ مورد دیگر

Professor Danijela Miloradović is a distinguished faculty member at the University of Kragujevac, Faculty of Engineering Sciences, Department of Motor Vehicles and Engines. She currently holds the position of Full Professor, having been promoted to this rank in 2022 after serving as Associate Professor (2017-2022) and Assistant Professor (2012-2017). Her extensive academic career spans over 25 years at the same institution, with progressive appointments from Research Associate in 1994 to her current position. Prof. Miloradović's research focuses primarily on vehicle dynamics, noise, vibration and harshness (NVH), steering and suspension systems, brake systems, and vehicle safety. Her work has significant practical applications in automotive engineering, particularly in improving vehicle performance, safety, and environmental impact. She has made notable contributions to understanding the interaction between steering and suspension systems, brake noise problems, and vehicle vibration comfort. Her publication record is impressive, with over 50 scientific and professional papers, including numerous articles in prominent international journals. Her research has evolved from fundamental vehicle dynamics studies to more specialized areas like brake wear particle emissions and their environmental impact. Recent work shows a strong focus on sustainable automotive technologies and environmental considerations in vehicle design. Among her notable recognitions are the KSME award for the second best paper in JMST magazine (2017) and the "Editor's Choice Article" award from the journal "Machines" (2022). She has also received early career recognition as the best student at the Faculty of Mechanical Engineering in 1990 and for excellent academic achievement in 1994. Prof. Miloradović has been actively involved in mentoring doctoral students, serving as mentor for Aleksandar Poznić's doctoral dissertation and participating in numerous doctoral defense committees. She has also contributed significantly to educational development through textbook writing, curriculum design, and supervision of numerous academic courses in vehicle dynamics and related fields. Her leadership extends to administrative roles including serving as Vice-Dean for Teaching (2012-2015), Head of the Department of Motor Vehicles and Engines, and currently as President of the Faculty Council of the Faculty of Engineering Sciences. She has also played key roles in organizing international conferences and serving on accreditation committees for academic programs.

Igor Džinčićمشاهده پروفایل

استاد

• Furniture Design
• Wood Processing
• Numerical Analysis of Furniture Construction
• +۵ مورد دیگر

Igor Džinčić is a Full Professor at the Faculty of Forestry, University of Belgrade, where he has been teaching since 2001. He specializes in Final Wood Processing with a focus on furniture design and manufacturing. His academic career progressed from trainee assistant in 2001 to full professor in 2021, demonstrating his expertise and commitment to the field. Professor Džinčić's research interests include: Furniture design and construction Numerical analysis of furniture structures Material consumption optimization Gluing technologies in wood processing Technological processes of furniture production Quality assurance of furniture products His scholarly work consistently focuses on the mechanical properties of furniture, particularly chairs and frame furniture, with numerous publications examining joint strength, material properties, and quality control methods. His research bridges theoretical analysis with practical applications in wood processing and furniture manufacturing, making significant contributions to both academic knowledge and industry practices. Professor Džinčić has held significant leadership positions: Manager of the Furniture Quality Control Institute since 2019 President of the Committee for Standards in the Field of Furniture (KS D136) since 2010 Member of the Committee for Standards in Doors, Windows, and Building Hardware (KS U162) since 2012 He has published 41 scientific papers and co-authored a university textbook on furniture design. His teaching spans all academic levels, covering subjects related to furniture construction, wood processing technologies, CAD systems, and quality control in wood products manufacturing, influencing generations of forestry and wood technology students.

• Machine Tools
• Thermal Analysis
• Computer-Aided Design
• +۵ مورد دیگر

Aleksandar Živković is a Full Professor at the Chair of Computer Aided Technological Systems and Design, Faculty of Technical Sciences, University of Novi Sad. He joined the institution in 2004 and has held progressive academic positions: Assistant (2007), Assistant Professor (2013), Associate Professor (2018), and Full Professor (2023). His academic focus is on Machine Tools, Technological Systems, and Automation of Design Procedures . Education PhD in Mechanical Engineering (2013) – Faculty of Technical Sciences. Thesis: Computer and experimental analysis of the behaviour of ball bearings for special purposes . Master's in Mechanical Engineering (2007) – Faculty of Technical Sciences. Thesis: Experimental and computational analysis of the thermal-elastic behaviour of high-speed main spindles . Bachelor's in Production Engineering (2003) – Faculty of Technical Sciences. Thesis: Analysis of static behaviour of the main spindle . Research Focus Živković's research integrates computational and experimental methods to solve industrial challenges. Key areas include: Thermal and dynamic behavior of high-speed machine tool spindles Design and analysis of bearings for specialized applications Finite element modeling of mechanical and biomechanical systems 3D printing and virtual prototyping for medical devices (e.g., hip/knee prostheses) Optimization of machining processes using AI and fuzzy logic Publications His 15 most recent articles (2012–2022) demonstrate a strong focus on thermal modeling of spindles, bearing technology, biomechanics, and machining optimization. Methodologies frequently employ neural networks, FEM, experimental validation, and parametric design. Administrative Roles Secretary of the Chair of Computer Aided Technological Systems and Design (2015–2021)

• Mechanical Engineering
• Materials Science
• Applied Mechanics
• +۵ مورد دیگر

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 Popovićمشاهده پروفایل

پژوهشگر

• Nuclear Engineering
• Materials Science
• Environmental Engineering
• +۳ مورد دیگر

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.