2022–2026
PhD in Computer Science
The University of Sydney, Australia
Thesis: Towards High-Efficient Federated Learning Systems
Supervisors: Dr. Wei Li and Prof. Albert Y. Zomaya
Welcome to Jiaming Pei's academic homepage.
My research focuses on developing efficient, robust, and trustworthy artificial intelligence systems for transportation, distributed computing, and cyber-physical applications.
Dr. Jiaming Pei
PhD in Computer Science
FRSA, SFNAAI, Top2% Scientist
IEEE, ACM Member
School of Computer Science
The University of Sydney
E-mail: jiamingpei0262@gmail.com, jpei0906@sydney.edu.au
I received my PhD in Computer Science from the University of Sydney. My research investigates efficient and dependable artificial intelligence methods for distributed and resource-constrained systems. In particular, I am interested in federated learning, distributed optimization, intelligent transportation systems, robust and trustworthy AI, and neuro-symbolic learning.
My work aims to connect fundamental machine learning methods with practical applications in transportation, the Internet of Things, smart cities, autonomous systems, and cyber-physical systems. I am particularly interested in learning under heterogeneous data, constrained communication, limited computing resources, and dynamically changing environments.
Research Interests- Federated and Distributed Learning
- AI for Transportation and Smart Cities
- Robust and Trustworthy Artificial Intelligence
- Distributed Optimization and Edge Intelligence
- Multi-Agent communication and collaboration
Education and Experience
Education
2017–2021
Bachelor in Information system and Information Management
Taizhou University, China
Graduation thesis: Analysis of Intelligent Optimization Algorithm for Urban Public Transportation (Outstanding Thesis Award 2021)
Professional Experience
2026–Present
University of Sydney
Researcher
2021–2022
Visiting Scholar
Southwestern University of Finance and Economics
News
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August 2026
My paper, titled " PAM: Improve the Performance of Randomized Online Algorithms with Machine-learned Predictions in Online Energy Management ", were accepted for publication in IEEE Internet of Things Journal !
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August 2026
My corresponding author papers, titled " Low-Altitude Two-Tier Data Collection Scheme in Edge-Empowered Marine Computing Networks ", " Trust-Aware Incentive for Semantic-Oriented Multi-Access Offloading in Mobile Edge-Cloud Networks ", were accepted for publication in IEEE Globecom 2026 !
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July 2026
My co-author paper, titled " CARED: Circulant Attention and Reliability-Guided Expert Diffusion for Robust Remote Physiological Signal Reconstruction ", was accepted for publication in IEEE JBHI !
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July 2026
My corresponding author paper, titled " Secure Semantic Consensus as the Control Plane of Federated Agentic Networks ", was accepted for publication in IEEE Communications Standards Magazine !
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July 2026
My co-author paper, titled " Privacy-Preserving Federated Early Warning of Memory Poisoning for Consumer AI Agents ", was accepted for publication in IEEE Transactions on Consumer Electronics !
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June 2026
My first-author paper, titled " Explainable Federated Clustering via Visual Embedding and Boundary Interpretation ", was accepted for publication in Neurocomputing !
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May 2026
My student paper, titled " CSIF-CD: A Unified Cross-Stage Interactive Feedback Framework for Remote Sensing Image Change Detection ", was accepted for publication in IEEE Geoscience and Remote Sensing Letters !
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April 13, 2026
Congratulations! I received my Ph.D. degree in Computer Science from The University of Sydney!
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March, 2026
My first-author paper, titled " A Multi-Stage Neuro-Symbolic Framework for Trustworthy Agentic Intelligence in ICE Systems ", was accepted for publication in IEEE Transactions on Consumer Electronics !
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March, 2026
My first-author paper, titled " Generative AI-Native Edge Sensors: Collaborative Data Reconstruction via Lightweight Federated Learning ", was accepted for publication in IEEE Journal of Selected Areas in Sensors !
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March, 2026
My first-author paper, titled " Resource Allocation Using Reinforcement Learning in Industrial Cyber-Physical Systems ", was accepted for publication in IEEE Transactions on Industrial Cyber-Physical Systems!
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March, 2026
My first-author paper, titled " Adaptive Federated Learning for Future IoV-Oriented IoT End-to-End Network Planning ", was accepted for publication in IEEE Internet of Things Journal !