جستجوی استاد راهنمای دانشگاهی

• Information Technology
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Aleksa Iričanin is a doctoral student and teaching assistant at the Department of Information Technologies, Faculty of Technical Sciences Čačak, University of Kragujevac. His academic career began during his master's studies, and he has been actively contributing to research in software engineering, machine learning, and data privacy. Education: Bachelor's and Master's degrees in Information Technology from Faculty of Technical Sciences Čačak Currently pursuing PhD in the same program Research Interests: Focused on code churn analysis, privacy-preserving machine learning, and horizontal scaling of PHP applications. His work integrates artificial intelligence with software maintenance and data privacy techniques like differential privacy. Publications: Recent articles explore trends in predictive modeling for software development, ethical AI frameworks, and cloud computing solutions for web applications. Contact: Office No. 025, Faculty of Technical Sciences Čačak, Svetog Save 65, Čačak, Serbia.

• Semantic Web Technologies
• Distributed Systems
• E-Learning Systems
• +۳ مورد دیگر

Милорад Б. Тошић is a Full Professor at the Faculty of Electronic Engineering, University of Niš, specializing in Computer Science. He earned all his academic degrees (BSc 1989, MSc 1992, PhD 1998) from the same institution in Electrical Engineering and Computer Science. His research spans Semantic Web Technologies, Distributed Systems, and E-Learning Systems, with notable contributions in federated testbeds, trust-based peer assessment, and collaborative wiki tagging. His work bridges theoretical computer science with practical applications in education and embedded systems. His publication trends show consistent contributions from 1991 to 2014, with recent focus shifting from hardware design (1990s) to semantic technologies and e-learning systems (2000s-2010s), demonstrating adaptability across evolving technological domains. US Patent Application No. 09/636,552 for Internet-Enabled Embedded Device Technology validated by Motorola, Microchip, Philips, and Delphi As former Science and Technology Advisor to the Serbian Minister (2002-2003), he contributed to national science policy. His current research involves 4 national and 3 international projects totaling 7 impact-factor journal publications. His patented embedded device technology has achieved commercial validation through major global electronics firms.

• Control Theory
• Automotive Engineering
• Quantum Computing
• +۳ مورد دیگر

Uroš Kalabić is a Teaching Professor at Singidunum University in Serbia. He holds a doctoral degree in Electrical and Computer Engineering from the University of Michigan (2015), a Master's degree from the same university (2011), and a Bachelor's degree in Electrical and Computer Engineering from the University of Toronto (2010). His research focuses on advanced control systems and their applications in automotive engineering, aerospace, and quantum computing. Doctoral studies: University of Michigan, Electrical and Computer Engineering (2015) Master's studies: University of Michigan, Electrical and Computer Engineering (2011) Undergraduate studies: University of Toronto, Electrical and Computer Engineering (2010) Kalabić's research interests span stochastic model predictive control , quantum optimization , autonomous traffic systems , and nonlinear control on manifolds . His work includes applications in automotive engine control, spacecraft attitude control, quantum search algorithms, and sustainable transportation schemes. He has published in top journals like AUTOMATICA and the Journal of Dynamic Systems, Measurement, and Control, focusing on control theory and its interdisciplinary applications. His publications reveal expertise in stochastic control , reinforcement learning , quantum computing , and transportation optimization . Notable contributions include constraint-separation principles in MPC, reference governors for probabilistic systems, and deep learning-based traffic management frameworks. Currently, no scientific awards or honors are documented in the provided materials. Similarly, there is no mention of student advising roles, laboratory leadership, or active research grants in the available descriptions.

• Neural Networks
• Wireless Communications
• Signal Processing
• +۸ مورد دیگر

Ivan Milovanović is a researcher at the Department of Postgraduate Studies , University of Singidunum, Belgrade, Serbia. He holds a doctoral degree in Advanced Protection Systems from Singidunum University (2015) and has previously completed master's and bachelor's studies in Contemporary Information Technologies and Graphics and Design at the same institution. His career spans roles in software development, wireless communication research, and neural network applications for electromagnetic signal processing. B.Sc. in Graphics and Design (2008), Singidunum University M.Sc. in Contemporary Information Technologies (2009), Singidunum University Ph.D. in Advanced Protection Systems (2015), Singidunum University Milovanović's research focuses on applying neural networks to solve complex problems in wireless communications, particularly in direction-of-arrival (DOA) estimation for stochastic electromagnetic sources. His work addresses challenges in localization accuracy, signal correlation, and power variation. He has contributed to advancements in 2D/1D DOA estimation using hybrid neural models, experimental validation of antenna array measurements, and noise interference analysis in wireless systems. Publications span topics like wireless sensor networks, channel modeling, and MESH network security. Recent publications highlight a strong interdisciplinary focus combining neural networks with electromagnetic signal processing , antenna array optimization , and wireless communication systems . His work explores stochastic source tracking, coherent signal resolution, and noise mitigation techniques, often collaborating with researchers like Z. Stanković and N. Dončov. While no scientific awards are explicitly mentioned in the provided text, his extensive publication record indicates active contributions to applied electromagnetics and telecommunications engineering.

Miloš Pavkovićمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +۵ مورد دیگر

Miloš Pavković is a researcher affiliated with Singidunum University in Serbia. He holds a doctoral degree in Software Engineering from the Faculty of Electrical Engineering, earned after 9 years of study (2012–2021), and a master’s degree in the same field from the same institution (2004–2009). His work spans artificial intelligence, software engineering, environmental modeling, and educational technology. Education : Basic studies in Software Engineering (Faculty of Electrical Engineering, 2004–2009); Doctoral studies in Software Engineering (Faculty of Electrical Engineering, 2012–2021). Pavković’s research focuses on AI applications, including recurrent neural networks for pollution forecasting, metaheuristic optimization, and large language models (LLMs) for web scraping. He has also contributed to software engineering tools for forum crawling, cybersecurity techniques for SQL injection detection, and computer vision applications in agriculture. His publications since 2013 reflect expertise in internet data retrieval, educational technology, and cross-disciplinary applications of AI in environmental and agricultural contexts. Recent works (2025) highlight advancements in pollution prediction and LLM-driven automation.

• Cybersecurity
• Machine Learning
• Internet of Things (IoT)
• +۳ مورد دیگر

Nikola Savanovic serves as an Assistant Professor at Singidunum University's Faculty of Informatics and Computing in Belgrade, Serbia. His academic work centers on cybersecurity, machine learning, and IoT systems within the Department of Informatics and Computing. Research Focus: His primary fields include cybersecurity (particularly intrusion detection in healthcare IoT systems), metaheuristic optimization of machine learning models, web technologies, and healthcare informatics. His recent work demonstrates strong interdisciplinary connections between computer science, medical technology, and financial systems. Publication Trends: Analysis of his 15 most recent articles reveals a dominant focus on cybersecurity applications (40%), machine learning optimization (30%), and healthcare technology (20%), with growing emphasis on metaheuristic algorithms for solving complex security and diagnostic problems. His work frequently appears in high-impact journals like Mathematics and Sustainability . Academic Background: PhD in Advanced Protection Systems (2016-2024), University of Singidunum Master's in Contemporary Information Technologies (2013-2016), Singidunum University Bachelor's in Informatics and Computing (2007-2013), Singidunum University Mechanical Technician for Computer Engineering (2003-2007), Polytechnic High School - School for New Technologies Authorship: He has co-authored 5 academic books including Web Design and Multimedia Systems (2023) and Knowledge Discovery in the Cyberspace (2017), demonstrating expertise in both theoretical and applied computing fields. His collaborative research spans multiple international institutions with consistent publication output since 2013. Technical Leadership: His conference presentations reveal active involvement in Serbia's academic technology community through events like IcETRAN and SINTEZA conferences, focusing on practical implementations of cybersecurity frameworks and educational technology solutions.

• Artificial Intelligence
• Machine Learning
• Computer Science
• +۳ مورد دیگر

Ivan Radosavljevic is a researcher at Singidunum University's Department of Postgraduate Studies, actively contributing to the fields of Artificial Intelligence, Machine Learning, and Software Engineering. His work spans diverse applications including environmental monitoring, educational technology, medical diagnostics, and geospatial systems. Research interests focus on AI-driven solutions for air quality assessment, synthetic dataset generation for semantic segmentation, real estate price prediction from internet ads, and medical imaging analysis. He has developed software tools for remote rendering monitoring, automated grading, and eye-tracking-based code interaction studies. His publications demonstrate expertise in integrating fuzzy logic with GIS for environmental applications, creating innovative educational technologies, and applying machine learning to healthcare diagnostics. Ivan collaborates with colleagues across multiple domains while maintaining a strong focus on practical implementations of artificial intelligence.