Xu (Eric) Wang
I am a Ph.D. candidate in the School of Computing at Queen’s University (WineMocol Lab), supervised by Prof. Yuanzhu Chen and Prof. Octavia Dobre.
My research centers on decentralized federated learning (DFL) over real-world networks: how the topology of the underlying network shapes what a decentralized system can learn, and how to make such systems robust. On the design side, I introduced teleportation links and connectivity enrichment to mitigate catastrophic forgetting and community isolation in DFL networks. On the security side, I study community-level attacks that disrupt cross-community information flow, as well as defenses against malicious models in federated learning deployed on real-world energy storage systems. A full list of my papers is on Google Scholar.
Research Interests
- Federated Learning and Edge Computing
- Computer Networks and Network Science
- Cyber Security
News
- June 2026: Our paper “DOCAttack: Data-Oriented Community Attack in Decentralized Federated Learning” was accepted by IEEE Transactions on Network Science and Engineering!
- February 2026: Our paper “Disrupting Cross-Community Information Flow in Decentralized Federated Learning” was accepted at IEEE INFOCOM 2026 Workshops!
- September 2025: Our paper “Teleportation Links: Mitigating Catastrophic Forgetting in Decentralized Federated Learning” was accepted by IEEE Transactions on Network Science and Engineering!
Older News
- May 2025: Our paper “Connectivity Enrichment for Decentralized Federated Learning Networks with Teleportation” was accepted at IEEE INFOCOM 2025 Workshops!
- December 2024: Our book chapter “Federated Learning in Mesh Networks” was accepted by Artificial Intelligence for Future Networks (IEEE Press & Wiley)!
- May 2024: Our paper “Designing Robust 6G Networks with Bimodal Distribution for Decentralized Federated Learning” was accepted at IEEE INFOCOM 2024 Workshops!
- April 2024: Our paper “Robust Federated Learning for Energy Storage Systems” was accepted at IEEE WCNC 2024!
- June 2023: Our paper “A Communication-Efficient Protocol for Federated Learning in Energy Storage Systems” was accepted at CANAI 2023!
- January 2023: Our paper “Malicious Model Detection for Federated Learning Empowered Energy Storage Systems” was accepted at IEEE ICNC 2023!
- May 2022: Our paper “Federated Learning for Anomaly Detection: A Case of Real-World Energy Storage Deployment” was accepted at IEEE ICC 2022!
- June 2021: Our paper “A Fast Self-Jamming Cancellation Architecture and Algorithm for Passive RFID Sensor System” was accepted by IEEE Communications Letters!
- May 2019: Our paper “Fast Data-Driven Sensitivity Measurement for Wireless Receivers” was accepted at IEEE ICC 2019!
- May 2019: Our paper “Data-Driven Measurement of Receiver Sensitivity in Wireless Communication Systems” was accepted by IEEE Transactions on Communications!
- May 2019: Our paper “Power Quality Measurement of Wind Turbines based on MATLAB” was accepted by Acta Energiae Solaris Sinica!
- May 2017: Our paper “Voltage Flicker Measurement of Wind Turbines using Kaiser Window Correction based on FFT and HHT” was accepted by Journal of Electronic Measurement and Instrumentation!
Education
Ph.D. in Computer Science (Expected October 2026) Queen’s University, Kingston, Ontario, Canada
M.Sc. in Signal Processing and Intelligent Control (2018) Inner Mongolia University of Technology, China
B.Sc. in Communication Engineering (2015) Shenyang Institute of Technology, China
Awards and Recognition
- Graduate Research Award (Second Place), IEEE Kingston Section, 2025
- Student Travel Award, Queen’s University, 2024, 2025
- Student Travel Award, Canadian AI Association, 2023
- Mitacs Accelerate Fellowship, 2023
- Queen’s Graduate Award, 2021–2024
- National Scholarship for Postgraduates, Ministry of Education of China, 2018
- Outstanding Graduate, Inner Mongolia University of Technology, 2018
Academic Service
Professional Service:
- TPC Member, IEEE ICC 2026, 2027
- TPC Member, IEEE CCECE 2026
- Session Chair, IEEE ICC 2025
- Student Volunteer, IEEE ICC 2025
- TPC Member, IEEE VTC2024-Fall
- Session Chair, IEEE ICC 2024
- Faculty Mentor, Google Research exploreCSR, 2022
Departmental Service:
- Student Representative, Appointments Committee, School of Computing, Queen’s University (2023–present)
- Student Representative, Renewal, Tenure, and Promotion Committee, School of Computing, Queen’s University (2023–present)
Journal/Conference Reviewer:
- Journals: IEEE TNSM, IEEE TCCN, IEEE WCL, IEEE JSAC, ACM Computing Surveys, IEEE TEVC, IEEE JSTSP, IEEE IoT Journal, IEEE TNSE, IEEE OJ-COMS, China Communications, IEEE/CAA JAS
- Conferences: IEEE Globecom, IEEE ICC, IEEE VTC, IEEE MILCOM, IEEE LATINCOM, IEEE WCNC, IEEE PIMRC, FCN (Future Communications and Networks)
Research & Teaching Impact
My research and teaching align with the United Nations Sustainable Development Goals:
SDG 4 (Quality Education): Through teaching Discrete Structures, I promote accessible and concept-driven foundational education in computing, strengthening students’ mathematical and logical foundations.
SDG 9 (Industry, Innovation and Infrastructure): My research focuses on resilient and decentralized learning systems that remain reliable under network failures, adversarial behavior, and resource constraints.
SDG 11 (Sustainable Cities and Communities): Supporting sustainable digital infrastructure for large-scale intelligent systems.