Dr. Nasser Mozayani | software | Best Researcher Award
Associate Professor, Iran University of Science and technology, Iran
🎓 Dr. Nasser Mozayani is an Associate Professor at the School of Computer Engineering at Iran University of Science and Technology (IUST) in Tehran, Iran. With a distinguished career in computer engineering, he has contributed significantly to research, teaching, and administration in his field. Dr. Mozayani specializes in machine learning, multi-agent systems, and the metaverse, bringing innovative insights into these cutting-edge areas. He has held several prominent positions at IUST, including Dean of the Computer Engineering Department, and has been actively involved in national research and technological projects.
Publication Profile
Education
📘 Dr. Mozayani completed his Ph.D. in Informatics at the University of Rennes I in France (1998), where he conducted groundbreaking research on spatio-temporal coding in neural networks. His educational journey also includes an M.Sc. in Telematics & Information Systems from SUPELEC, France (1994), and a B.Sc. in Electrical Engineering (Computer Hardware) from Sharif University of Technology in Tehran, Iran (1990).
Experience
👨🏫 Dr. Mozayani has been an Associate Professor at IUST since 1999, teaching undergraduate courses in electronic and electric circuits, and advanced graduate courses in fields like artificial neural networks, digital circuits synthesis, and distributed AI. He has also held visiting professor roles at Allameh Tabatabaee University and Tarbiat Modarres University, where he specialized in educational games and simulations for doctoral students. In administrative capacities, he has led multiple departments and centers at IUST, contributing to the growth of e-learning and technology innovation.
Research Focus
🔬 Dr. Mozayani’s research is centered on machine learning, multi-agent systems, and smart grid applications. He has led numerous projects on smart grid communication protocols, reinforcement learning, and the application of AI in predictive modeling and decision-making for health and energy sectors. His innovative work in hierarchical reinforcement learning has advanced the integration of machine learning in smart grid management and infrastructure.
Awards and Honors
🏆 Dr. Mozayani has supervised the IUST RoboCup team, which achieved notable successes, including a first-place win in the Rescue Virtual Robots competition at the Khwarizmi Young Award (2010) and a top-four ranking in the World RoboCup 2D football simulation (2013). He has also mentored award-winning student projects in digital library development, recognized by the Khwarizmi Young Award.
Publications – Top Notes
“Deployment of a Flexible Communication Protocol for Advanced Metering in Smart Grid” (IUST, 2023), cited by 5 articles Journal: Smart Grid Technologies.
“Algorithmic Trading on Financial Time Series Using Deep Reinforcement Learning” (IUST, 2022), cited by 10 articles Journal: Financial Technology & AI.
“Using Machine Learning Methods to Determine Factors Affecting COVID-19 Mortality Rates” (IUST, 2021), cited by 8 articles Journal: Health Informatics.