Encourages independent and critical thought.
Makes learning a joyful experience.
Makes complex ideas simple and clear.
Fosters collaboration and teamwork.
A true gem in the academic community.
Dr. Ben Duan serves as an Adjunct Lecturer in the Department of Data Science and Artificial Intelligence, Faculty of Information Technology, at Monash University, Australia. He is affiliated with the Monash Suzhou campus, contributing to teaching units including FIT5221 Intelligent Image and Video Analysis, FIT5215 Deep Learning, FIT5217 Statistical Data Modeling, and FIT5225 Cloud Computing and Security. Duan obtained his Ph.D. in big data and electronics from the University of Technology Sydney. Prior to his current role, he held a position as Research Fellow at the Hong Kong University of Science and Technology. His research specializations include reinforcement learning, graph neural networks, intelligent transportation systems, fintech, and data-driven AI models applied to industrial processes dominated by particle-fluid flows. Duan is a member of the Monash Suzhou Research Institute since 2024 and is currently accepting PhD students, offering full scholarship support for projects in his areas of interest. His scholarly activities align with several United Nations Sustainable Development Goals, such as Good Health and Well-being (SDG 3), Affordable and Clean Energy (SDG 7), Industry, Innovation and Infrastructure (SDG 9), and Sustainable Cities and Communities (SDG 11).
Ben Duan has authored or co-authored 33 research outputs, comprising 21 journal articles and 12 conference papers. Key publications feature "What is the root cause of congestion in urban traffic networks: road infrastructure or signal control?" (IEEE Transactions on Intelligent Transportation Systems, 2022, 47 citations), "A unified spatio-temporal model for short-term traffic flow prediction" (IEEE Transactions on Intelligent Transportation Systems, 2019, 129 citations), "Estimation of link travel time distribution with limited traffic detectors" (IEEE Transactions on Intelligent Transportation Systems, 2020, 20 citations), "Estimating link travel time distribution using network tomography technique" (IEEE Intelligent Transportation Systems Conference, 2019), and "Applying distributed constraint optimization approach to the user association problem in heterogeneous networks" (IEEE Transactions on Cybernetics, 2018). He holds provisional patents and maintains a Scopus author profile.