جستجوی استاد راهنمای دانشگاهی

Nebojša Bačanin Džakula is an academic affiliated with Singidunum University's Faculty of Mathematics, specializing in Computer Science. He earned his PhD in 2015 with a thesis on improving swarm intelligence metaheuristics for global optimization. His research focuses on AI-driven solutions for cybersecurity, energy forecasting, and optimization algorithms. He has authored/co-authored books on cloud computing and web programming. His work bridges metaheuristics with machine learning, addressing challenges in IoT security, renewable energy prediction, and healthcare diagnostics. He actively contributes to conferences like Sinteza and IEEE events, emphasizing practical applications of AI and optimization in real-world scenarios. Education: Completed doctoral studies at the Faculty of Mathematics (2009–2015). Extensive industry certifications include Microsoft, CompTIA, and Oracle credentials, enhancing his technical expertise. Research Interests: Develops hybrid models combining metaheuristics (e.g., PSO, GA) with deep learning for tasks like intrusion detection, price forecasting, and medical diagnostics. Specializes in optimizing neural networks and feature selection using advanced algorithms. His work often addresses societal challenges in sustainability, cybersecurity, and healthcare. Recent Publications: Focus on AI-driven solutions for IoT security, renewable energy prediction, and medical diagnostics (e.g., Parkinson’s detection via LSTM networks). His articles appear in prestigious journals like Engineering Applications of Artificial Intelligence and Applied Soft Computing.

• Artificial Intelligence
• Machine Learning
• Optimization Algorithms
• +۴ مورد دیگر

Prof. Michael Krivelevich holds the Baumritter Chair in Combinatorics at the School of Mathematical Sciences, Tel Aviv University. His research focuses on probabilistic methods in combinatorics, random graphs, and positional games. He has authored influential books such as Positional Games and contributed to foundational work in random graph theory. Currently teaching Introduction to Combinatorics and Graph Theory (Spring 2025), he has extensive experience in courses like Graph Theory and Hypergraph Coloring. His work bridges theoretical computer science, coding theory, and combinatorics, with over 150 publications. Recent research explores game-theoretic thresholds, random graph evolution, and equitable coloring algorithms. Education: Ph.D. in Mathematics, Tel Aviv University (not explicitly stated, inferred from career trajectory). Research Interests Krivelevich's work emphasizes random structures , extremal graph theory , and probabilistic combinatorics . He investigates phase transitions in random graphs, positional game strategies, and algorithmic challenges in graph coloring. His contributions include proving sharp thresholds for Hamilton cycle games and analyzing WalkSAT performance on smoothed k-CNF formulas. Collaborations span theoretical computer science and discrete mathematics. Publications Recent articles address Hamiltonicity in Maker-Breaker games, equitable coloring of random graphs, and smoothed analysis of satisfiability processes. His work often combines rigorous proofs with algorithmic insights. Teaching & Mentorship Guides students through advanced combinatorial topics and has taught foundational courses since 2002. No explicit student listings available in provided texts.

• Probabilistic Methods in Combinatorics
• Random Structures
• Hypergraphs
• +۷ مورد دیگر

Akanksha Agrawal is an Assistant Professor and Veena and Induprakas Keri Faculty Fellow at the Department of Computer Science and Engineering, Indian Institute of Technology Madras. Her research focuses on Parameterized Complexity & Algorithms, Graph Algorithms, Computational Geometry, Exact Algorithms, and Fine Grained Algorithms & Complexity. She has held postdoctoral positions at Ben-Gurion University of the Negev (Israel) and the Hungarian Academy of Sciences, funded by a PBC Fellowship. She earned her Ph.D. from the University of Bergen under Professors Saket Saurabh and Daniel Lokshtanov. Education: Ph.D., University of Bergen, Norway (2017-2021) Postdoctoral Researcher, Ben-Gurion University of the Negev, Israel (2021-2022) Postdoctoral Researcher, Hungarian Academy of Sciences, Hungary (2022-2023) Research Interests: Her work emphasizes parameterized complexity, graph algorithms, and computational geometry. She explores exact algorithms, fine-grained complexity, and algorithmic approaches to NP-hard problems. Her research bridges theoretical insights with practical algorithmic solutions. Recent Activities & Awards: ACM-India Eminent Speaker (2024-2026) Invited Talks: COMSNETS 2025, IISc Bengaluru (2024), Bali Parameterized Graph Algorithms (2024) Program Committee Roles: IPEC 2025 (Co-Chair), WG 2025, CALDAM 2025 Grants & Academic Services: Organizing Dagstuhl Seminar (Jan. 2025) with Maria Chudnovsky, Daniel Paulusma, and Oliver Schaudt Contributions to international conferences and workshops Teaching: Courses include Combinatorial Objects, Parameterized Algorithms, Design & Analysis of Algorithms, Approximation Algorithms, and Advanced Data Structures.

• Parameterized Complexity & Algorithms
• Graph Algorithms
• Computational Geometry
• +۳ مورد دیگر

Aleksandar Mihajlovic is a researcher and Art Director at Singidunum University, Serbia. With a doctoral degree in Contemporary Business Decision-Making (2022), a master's in Business Economics (2014), and a bachelor's in Computer Graphics and Design (2008), he combines academic rigor with creative leadership in the university's marketing strategy. Doctoral studies: Contemporary Business Decision-Making, Singidunum University (2022) Master studies: Business Economics, Singidunum University (2008–2014) Undergraduate: Computer Graphics and Design, Faculty of Informatics and Management (2005–2008) High school: Robotics and Flexible Production Systems Technician, Polytechnic Academy (1995–1999) His research spans visual communication , digital marketing , and artificial intelligence applications in creative industries. Key contributions include Co-authoring 11 academic papers (2015–2025) on topics like Instagram ad effectiveness, techno-feudalism, and responsive logo design. Developing the scientific research portal 'Singipedia' and international magazine 'SingiLogos'. Participating in 7 global projects including Erasmus+ and TEMPUS initiatives. His scientific awards include the JISA Discobolos Special Award (2010), IT Globus Award (2010), and Grafima Fair Special Award (2025). He serves on the organizing committee for conferences like Sinteza and Sitcon , and has judged marketing competitions while volunteering for NGOs like the City Organization of the Deaf of Belgrade.

• Visual Communication
• Graphic Design
• Digital Marketing
• +۵ مورد دیگر

Dragan S. Antic is a Professor at the Department of Automation, Faculty of Electronics, University of Niš. He earned his PhD in Automation from the same institution in 1994, following a Master's (1991) and Bachelor's (1987) degree in the same field. His research focuses on control systems, signal processing, and neuro-fuzzy systems, with a strong emphasis on sliding mode control, orthogonal function-based modeling, and adaptive neural networks. He has published 51 papers in journals with impact factors and currently participates in 2 national and 8 international research projects. Key research areas include dynamic system modeling, quasi-orthogonal filters, and finite-time stability analysis of time-delay systems. His work often integrates mathematical techniques with engineering applications, such as anti-lock braking systems and PID control optimization. Contact details include his office at Aleksandra Medvedeva 4, Niš, and the email dragan.antic@elfak.ni.ac.rs. Professional contributions include foundational research in endocrine neural networks and low-pass filter design, with notable publications in journals like Electronics Letters and Journal of the Franklin Institute . His efforts bridge theoretical advancements with practical engineering solutions in automation and control.

• Control Systems
• Signal Processing
• Neuro-Fuzzy Systems
• +۳ مورد دیگر

Yannic Maus is a University Professor at the Faculty of Computer Science and Biomedical Engineering at Graz University of Technology (TU Graz), Austria, where he heads the newly founded Institute of Algorithms and Theory (established in 2025). He also serves as co-leader of one of the five fields of expertise at TU Graz (FoE Information, Communication & Computation). His academic journey includes: PhD in Computer Science from University of Freiburg, Germany (2014-2018) MSc in Mathematics from RWTH Aachen, Germany BSc in Mathematics and Computer Science from RWTH Aachen, Germany (with a year at National University of Singapore) Professor Maus specializes in theoretical computer science and algorithm design, with a particular focus on distributed computing. His research spans distributed graph algorithms, efficient algorithms, data structures, complexity theory, and geometric algorithms. He approaches problems with both theoretical rigor and practical applications in mind, seeking clean mathematical solutions to questions motivated by real-world systems. His recent publications show a strong focus on distributed and parallel algorithms, particularly in graph theory. The research trends include distributed graph coloring, symmetry breaking, vertex cover problems, and massively parallel computing models. His work often bridges theoretical computer science with practical distributed systems considerations, with applications to large-scale networks and highly parallel systems. Professor Maus has received numerous accolades for his research: 2020 Principles of Distributed Computing Doctoral Dissertation Award Wolfgang-Gentner-Nachwuchsförderpreis 2019 GI Dissertationspreis 2018 Best Paper Awards at SIROCCO 2016, DISC 2016, and DISC 2017 Professor Maus actively mentors PhD students and has secured significant research funding, including FWF grants P36280-N (2023-2027), DOC 183 (2024-2028), I6915 (2024-2028), and FFG grant No. 59263962. His research group maintains strong international collaborations with institutions across Germany, Finland, Iceland, Israel, and beyond, providing students with opportunities for international research visits. He leads the Algorithms & Complexity research group at TU Graz, which includes PhD students Manuel Jakob, Florian Schager, Malte Baumecker, and Kritika Kashyap, as well as postdoc Tijn de Vos. The group is actively involved in theoretical computer science research with a focus on distributed and parallel algorithms, particularly for large-scale networks and highly parallel systems.

• Theoretical Computer Science
• Algorithm Design
• Distributed Computing
• +۶ مورد دیگر

Marina Milovanović is a Professor at the University of Singidunum, Faculty of Informatics and Computing, Department of Mathematics. She holds dual doctoral degrees from the Faculty of Science, University of Kragujevac (Department of Mathematics, 2014) and Faculty of Entrepreneurial Business, Union University (2008), along with Master's and Bachelor's degrees from the Faculty of Mathematics, University of Belgrade (2000-2005 and 1995-2000 respectively). Faculty of Science, University of Kragujevac, Department of Mathematics (PhD, 2014) Faculty of Entrepreneurial Business, Union University (PhD, 2008) Faculty of Mathematics, University of Belgrade (Master's, 2000-2005) Faculty of Mathematics, University of Belgrade (Bachelor's, 1995-2000) Svetozar Marković High School, science and mathematics major (1991-1995) Professor Milovanović specializes in Mathematics Education and Educational Technology, with particular expertise in interactive multimedia applications for teaching mathematics. Her research consistently bridges theoretical mathematics with practical educational technology solutions, evolving from traditional multimedia approaches to incorporating cutting-edge AI and machine learning techniques. She has authored multiple books including 'Interactive multimedia in mathematics teaching' (2015) and collections of solved mathematics problems for entrance exams. Her recent publication record through 2025 demonstrates active engagement in interdisciplinary research, particularly at the intersection of educational technology, artificial intelligence, and practical applications in fields ranging from software engineering to medical diagnostics. Her work shows a clear trajectory from foundational educational technology research toward more sophisticated AI-enhanced learning systems. Professor Milovanović has made significant contributions to semantic web applications in education, particularly through Moodle LMS enhancements, and has explored SCADA applications in industrial contexts. Her collaborative research spans multiple countries and institutions, reflecting an international scholarly network. She has extensive experience developing computer tools for engineering education and has published on diverse topics including petroleum industry processes, environmental management, and financial mathematics. Her work demonstrates consistent application of computational approaches to solve domain-specific problems across multiple disciplines.

• Mathematics Education
• Interactive Multimedia in Teaching
• Educational Technology
• +۵ مورد دیگر

Miloš Racković serves as a full Professor in the Department of Mathematics and Informatics at the University of Novi Sad, Serbia. He maintains active academic engagement through the Laboratory for the development of information systems, with his office located in the Information technologies and systems office (DMI&DF) on the second floor, room 49. Contact is available via telephone (485)-2868 or email rackovic@dmi.uns.ac.rs, and his personal website (http://www.is.pmf.uns.ac.rs/rackovicm/) provides additional resources. His research spans foundational and applied computer science, with seminal contributions in fuzzy database systems including PFSQL query language development and prioritized fuzzy logic for relational databases and XML. He has pioneered deep learning methodologies through innovative classification techniques using negative and missing features in convolutional neural networks. Additional expertise includes high-performance computing implementations of Lattice Boltzmann methods using OpenCL, robotics (symbolic modeling and trajectory planning), and blockchain applications for Industry 4.0 production processes. His sports analytics work applies neural networks to basketball player and referee movement analysis. Analysis of his 2012-2025 publications reveals a strategic evolution toward interdisciplinary applications, particularly in industrial transformation (blockchain-enabled traceability) and sports analytics. His work consistently bridges theoretical computer science with practical implementations, demonstrating increasing focus on real-world problem solving while maintaining strong foundations in database theory and computational methods. Professor Racković leads the Laboratory for the development of information systems, which focuses on advancing information system methodologies through formal modeling extensions (including Petri net innovations) and practical implementations for uncertainty management. The laboratory's work spans from foundational research in fuzzy logic systems to applied projects in high-performance computing and blockchain integration, fostering innovation in information technology development.

• Artificial Intelligence
• Machine Learning
• Databases
• +۴ 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.

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

Sandra M. Đosić is an Associate Professor at the Faculty of Electronics in Niš, University of Niš, Serbia, specializing in Electronics and Embedded Systems. She has been actively contributing to research in real-time systems, fault tolerance, wireless sensor networks, and indoor localization technologies. Research Interests: Her work spans fault-tolerant real-time systems, energy-efficient computing, UWB-based indoor localization, and communication protocols for wireless sensor networks. She explores techniques such as dynamic voltage and frequency scaling (DVFS), tone-based contention resolution, and deflection routing in networks-on-chip to enhance system reliability and efficiency. Publication Trends: Her recent publications (2009–2022) demonstrate a strong focus on improving robustness and performance in embedded and distributed systems. The research integrates signal processing, network optimization, and energy-aware design, primarily applied in industrial and indoor environments. Scientific Awards: No awards are mentioned in the provided text. Advising and Grants: While no specific students are listed, she is currently participating in two national research projects, indicating active involvement in funded research. Her collaborations with researchers such as Igor Stojanovic and Milica Jovanovic suggest a strong team-based research approach. Labs and Research Teams: Although no formal lab or team name is specified, her repeated co-authorship with colleagues from the Faculty of Electronics implies active participation in a research group focused on electronics, communications, and real-time systems.

• Electronics
• Real-Time Systems
• Fault-Tolerant Systems
• +۷ مورد دیگر

Professor Ivan Z. Milentijevic is a full professor at the Faculty of Electronics in Niš, University of Niš, within the Department of Electrical Engineering and Computer Science. He earned his PhD in Computer Science from the same institution in 1998, following a Master's (1994) and undergraduate degree (1989) in the same field. His research focuses on systolic arrays, digital signal processing architectures, and project-based learning methodologies. He has published 8 papers in journals with impact factor and is currently involved in 1 domestic and 1 international research project. Research interests include: Optimal design of systolic arrays for matrix operations FIR filter architectures and error-tolerant systems Reconfigurable hardware and parallel processing Educational technologies in project-based learning His recent work (2002–2008) emphasizes configurable architectures for signal processing and collaborative learning systems. Earlier contributions (1996–1998) focused on systolic array optimization for linear algebra operations. Advising/grants: No explicit student/advisor relationships listed. Current projects involve 1 domestic and 1 international collaboration. Grants and funding details not specified. Labs/teams: Affiliated with the Faculty of Electronics' research groups in computer engineering and signal processing, though specific lab names are not mentioned.

• Computer Science
• Electrical Engineering
• Digital Signal Processing
• +۳ مورد دیگر

Prof. Dr. Saša Adamović is a faculty member at Singidunum University in Belgrade, Serbia, affiliated with the Faculty of Informatics and Computer Science . His academic career spans over 15 years with a focus on Cryptography, Biometrics, and IoT Security . Born October 15, 1985, in Drvar, Bosnia and Herzegovina PhD in Advanced Security Systems (2013), Master’s in Contemporary Information Technologies (2008), and Bachelor’s in Business Informatics (all from Singidunum University) His research interests include: Biometric Cryptography Blockchain for IoT Security Catalan Number Applications in Cryptography Machine Learning in Security Systems Virtualization and Energy Efficiency Steganography and Forensics Recent publications highlight trends in: IoT Healthcare Security (2022) Biometric Authentication (2021) Combinatorial Cryptography (2021) Machine Learning for Diabetes Prediction (2021) Distance Learning Security (2023) He served as one of five Serbian representatives in the Open World program (USA) for expert exchange in technology development.

• Cryptography
• Biometric Security
• Internet of Things (IoT) Security
• +۳ مورد دیگر

Aleksandar Jevremović is a Full Professor at the Faculty of Informatics and Computing, Singidunum University (Belgrade, Serbia), and holds multiple academic and professional roles. He is the Serbian representative at the UNESCO IFIP Technical Committee on Human-Computer Interaction since 2018. He has served as Vice-Dean of his faculty (2015–2018) and held visiting professorships at institutions like Ss. Cyril and Methodius University (North Macedonia) and Tallinn University (Estonia). His research focuses on cybersecurity, IoT, AI, and e-learning innovation. Education and Affiliations: External Researcher at the Mathematical Institute of the Serbian Academy of Sciences and Arts Visiting Scholar at Cyprus Interaction Lab (Cyprus University of Technology) Alumni/Postdoc Researcher at Tallinn University's HCI Group Member of IEEE and the Informatics Association of Serbia Research Interests: Jevremović’s work spans cybersecurity (e.g., intrusion detection, secure IoT protocols), human-computer interaction (HCI), AI-driven education tools, and neurotechnological applications like EEG-based assessment systems. He emphasizes practical solutions for digital safety, such as children’s online protection and cryptographic key generation from biometric data. Grants and Projects: Member of the External Advisory Committee for the EU-funded ONTOCHAIN project (2022–2023) Mentor for training schools like AAPELE Training School and NET4Age-Friendly initiatives Trainer in IoT, cybersecurity, and health promotion programs across Europe Labs and Teams: He collaborates with interdisciplinary teams on projects like CASPER (Children Agents for Secure and Privacy Enhanced Reaction) and led the development of WIDE, a collaborative web development education platform.

• Human-Computer Interaction (HCI)
• Cybersecurity
• Internet of Things (IoT)
• +۶ مورد دیگر

Stanko Stankov is a researcher at the Faculty of Electronics, University of Niš, Serbia, affiliated with the Department of Automation. His work bridges academic research and industrial application in automation, control systems, and energy-efficient industrial processes. Master's Degree, Automation, Faculty of Electronics, University of Niš, 2013 Bachelor's Degree, Automation, Faculty of Electronics, University of Niš, 1987 His research focuses on industrial automation, particularly the application of PLC and SCADA systems in mineral wool production, water treatment, HVAC, and electrical installations. His work emphasizes real-time monitoring, process optimization, and energy efficiency in industrial settings. He has contributed to the design and implementation of control systems for complex technical plants, grounding, solar power, and security installations. The recent publications reveal a consistent trend in applied control engineering, with a focus on industrial process automation, data acquisition, and system integration. His work spans chemical, water, metallurgical, and energy sectors, demonstrating interdisciplinary relevance in engineering. Stanko Stankov holds professional licenses as a responsible designer and contractor in electrical and automation systems, indicating strong industry engagement. He has been involved in over 40 major design projects and the construction of more than 20 industrial facilities. He participates in national research projects and has contributed to journals such as Facta Universitatis , Tehnika , and Chemical Industry . His expertise includes solar power plants, fire protection, video surveillance, and telecommunications infrastructure.

• Industrial Automation
• Process Control
• SCADA Systems
• +۷ 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.

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