Jiaming Pei
Ph.D., Member IEEE
Stanford’s World's Top 2% Researcher
School of Computer Science,
The University of Sydney
Email: jpei0906@sydney.edu.au, jiamingpei0262@ieee.org
Jiaming Pei is a Ph.D. candidate in the School of Computer Science at The University of Sydney, supervised by Prof. Wei Li and Prof. Albert Zomaya. He also serves as a Guest Professor at the CVPR Lab, College of Intelligent Equipment, Shandong University of Science and Technology. His research interests focus on AI for Science and Robust & Trustworthy Artificial Intelligence, exploring how AI can drive innovation across domains such as transportation, economics, smart cities, and consumer electronics.
Dr. Pei’s research centers on developing robust, secure, and privacy-preserving AI frameworks, with particular emphasis on federated learning, generalization under heterogeneity, and reliable AI systems in complex environments. His work bridges theoretical advances with real-world applications, aiming to make AI a trustworthy and interpretable tool for scientific and societal progress.
He has published extensively in leading international journals and conferences, including IEEE Journal on Selected Areas in Communications, IEEE Transactions on Intelligent Transportation Systems, Knowledge-Based Systems, IEEE Communications Magazine, IEEE Transactions on Artificial Intelligence, IEEE Internet of Things Journal, and IEEE Network. His publications have accumulated over 1,400 citations, with an H-index of 18, including multiple ESI Highly Cited and Hot Papers.
Dr. Pei has been recognized as one of the World’s Top 2% Scientists (2025) and has received prestigious awards such as the Engineering Research Scholarship (ERS) and the Australian Government Research Training Program Scholarship (RTP). He has participated in several Australian Research Council (ARC) projects, including Discovery Early Career Researcher Award (DECRA) and Discovery Project (DP). As a member of IEEE and ACM, he actively contributes to the academic community as a reviewer and program committee member for top-tier venues such as ICLR, AAAI, CVPR, IJCAI, IEEE JSAC, and TITS.
His long-term vision is to advance trustworthy, explainable, and efficient AI systems that bridge the gap between computational intelligence and real-world scientific discovery, fostering sustainable technological and societal development.
AI4Science
Develop innovative AI algorithms to address interdisciplinary challenges across various scientific domains. Specific applications include:
- Transportation: Optimization of intelligent transportation systems, autonomous vehicles, and traffic flow management.
-Consumer Electronics: Enhancing device intelligence through AI-driven personalization and efficient resource utilization.
- Economics: Leveraging AI for economic modeling, decision-making, and forecasting. \newline
- Smart Cities: Applying AI to urban planning, resource management, and smart infrastructure for sustainable development.
Robust and Trustworthy AI
Design and optimize AI algorithms to ensure robustness and trustworthiness in complex and dynamic environments. This includes:
- Robustness: Improving model resilience to noisy, imbalanced, and heterogeneous data distributions. \newline
- Security: Enhancing AI systems against adversarial attacks and vulnerabilities. \newline
- Privacy-Preserving AI: Employing techniques such as federated learning and differential privacy to protect user data while maintaining model performance.
- Generalization: Ensuring algorithmic adaptability across diverse domains and applications without significant retraining efforts.
2022-2025: PhD in the School of Computer Science, The University of Sydney
2023-present: Guest professor in CVPR lab, College of intelligent equipment, Shandong University of Science and Technology
2021-2022: Visting Scholar in College of Information Engineering, Southwestern University of Finance and Economics
2017-2021: Bachelor in the School of computer Science and Technolgy, Taizhou University
2025 – World Top 2% Scientist
2022–2025 – Engineering Research Scholarship (ERS), Australian Government Research Training Program Scholarship, The University of Sydney
2021 – Outstanding Graduate, Taizhou University
2021 – Excellent Undergraduate Thesis, Taizhou University
Graduation Thesis: Research and Application of Intelligent Optimization Algorithm for Urban Public Transportation
2020 – First-Class Scholarship, Taizhou University
2019 – National Inspirational Scholarship, Ministry of Education of the People’s Republic of China