CV

Education Background

• Ph.D. in Computer Science, 2020 - 2024.
  • The Department of Computing, The Hong Kong Polytechnic University (PolyU), Hong Kong.
  • Supervisor: Prof. Song Guo
  • Research Interest: Federated Learning, Deep Reinforcement Learning, Federated Unlearning, Game Theory.
• Visiting Ph.D. in Computer Science, 2023 - 2024.
  • School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
  • Supervisor: Prof. Anne-Marie Kermarrec
  • Research Interest: Federated Unlearning.
• B.S. in Automation, 2015 - 2019.
  • Xuteli School, Beijing Institute of Technology (BIT), China
  • Supervisor: Prof. Kun Liu
  • Research Interest: Game Theory, Control Theory.

Work Experience

• Researcher, Dec. 2024 - Now
  • System Group, Theory Lab (Huawei 2012 Labs), Huawei Hong Kong Research Center.
  • Duties includes:
    • Graph-RAG for LLM
    • Multi-modal Alignment
    • LLM Speculative Decoding
    • Model Quantization
• Research Intern, Dec. 2023 - Aug. 2024.
  • System Group, Theory Lab (Huawei 2012 Labs), Huawei Hong Kong Research Center.
  • Duties includes:
    • AI-empowered Time Series Forecasting.
    • Multi-modal Large Language Model based Information Retrieval.
    • Multi-modal Alignment for Large Language Model Inference.
• Research Assistant, Sept. 2019 - Sept. 2020.
  • Department of Computing, The Hong Kong Polytechnic University (PolyU).
  • Supervisor: Prof. Song Guo
  • Duties includes:
    • Deep Reinforcement Learning-based incentive mechanism design for mobile edge network optimization (e.g., Federated Learning).
    • Survey the important challenges, open issues and future research directions in mobile edge network.
• Research Assistant, Nov. 2018 - Jul. 2019.
  • State Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology (BIT).
  • Supervisor: Prof. Kun Liu
  • Duties included:
    • Cooperative UAV-UGV system modeling and control law design.
    • Tracking algorithm design under dynamic visibility constraint.
• Embedded System Software Engineer, Jun. 2018 - Oct. 2018.
  • R&D Department, Zhejiang Dahua Technology Co. Ltd.
  • Duties included:
    • Project code debugging and automatic testing
    • Use case test of the dome camera’s artificial intelligence modules, including Face Recognition, Tripwire Intrusion, People Counting, etc.
    • Testing internal code coverage rate research project.

Publications

QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation

Leijie Wu, Yaohong Ding, Akash Dhasade, Martijn De Vos, Anne-marie Kermarrec, Song Guo. "QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation." Middleware24. 2024.

Rethinking Personalized Client Collaboration in Federated Learning

Leijie Wu, Song Guo, Yaohong Ding, Junxiao Wang, Wenchao Xu, Yufeng Zhan, and Anne-Marie Kermarrec. "Rethinking Personalized Client Collaboration in Federated Learning." IEEE Transactions on Mobile Computing (TMC). 2024.

Chiron: A Robustness-Aware Incentive Scheme for Edge Learning Via Hierarchical Reinforcement Learning

Yi Liu, Song Guo, Yufeng Zhan, Leijie Wu, Zicong Hong, and Qihua Zhou. "Chiron: A Robustness-Aware Incentive Scheme for Edge Learning Via Hierarchical Reinforcement Learning." IEEE Transactions on Mobile Computing (TMC). 2024.

Long-term Adaptive VCG Auction Mechanism for Sustainable Federated Learning with Periodical Client Shifting

Leijie Wu, Song Guo, Yi Liu, Zicong Hong, Yufeng Zhan, and Wenchao Xu. "Long-term Adaptive VCG Auction Mechanism for Sustainable Federated Learning with Periodical Client Shifting." IEEE Transactions on Mobile Computing (TMC). 2023.

On Knowledge Editing in Federated Learning: Perspectives, Challenges, and Future Directions

Leijie Wu, Song Guo, Junxiao Wang, Zicong Hong, Jie Zhang, and Jingren Zhou. "On Knowledge Editing in Federated Learning: Perspectives, Challenges, and Future Directions." ArXiv. 2023.

Demystify Self-Attention in Vision Transformers from a Semantic Perspective: Analysis and Application

Leijie Wu, Song Guo, Yaohong Ding, Junxiao Wang, Wenchao Xu, Jie Zhang, and Richard Yida Xu. "Demystify Self-Attention in Vision Transformers from a Semantic Perspective: Analysis and Application." ArXiv. 2022.

Federated Unlearning: Guarantee the Right of Clients to Forget

Leijie Wu, Song Guo, Junxiao Wang, Zicong Hong, Jie Zhang, and Yaohong Ding. "Federated Unlearning: Guarantee the Right of Clients to Forget." IEEE Network. 2022.

Sustainable Federated Learning with Long-term Online VCG Auction Mechanism

Leijie Wu, Song Guo, Yi Liu, Zicong Hong, Yufeng Zhan, and Wenchao Xu. "Sustainable Federated Learning with Long-term Online VCG Auction Mechanism." IEEE 42nd International Conference on Distributed Computing Systems (ICDCS). 2022: 895-905.

Incentive-Driven Long-term Optimization for Edge Learning by Hierarchical Reinforcement Mechanism

Yi Liu*, Leijie Wu*, Yufeng Zhan, Song Guo, and Zicong Hong (* indicates co-first authors with equal contribution). "Incentive-Driven Long-term Optimization for Edge Learning by Hierarchical Reinforcement Mechanism." IEEE 41st International Conference on Distributed Computing Systems (ICDCS). 2021: 35-45.

L4L: Experience-Driven Computational Resource Control in Federated Learning

Yufeng Zhan, Peng Li, Leijie Wu, and Song Guo. "L4L: Experience-Driven Computational Resource Control in Federated Learning." IEEE Transactions on Computers (TC). 2021.

A Survey of Incentive Mechanism Design for Federated Learning

Yufeng Zhan, Jie Zhang, Zicong Hong, Leijie Wu, Peng Li, and Song Guo. "A Survey of Incentive Mechanism Design for Federated Learning." EEE Transactions on Emerging Topics in Computing (TETC). 2021.

Talks

Conference Talk: QuickDrop: Efficient Federated Unlearning via Synthetic Data Generation

December 05, 2024

Middleware '24: Proceedings of the 25th International Middleware Conference at The Hong Kong Polytechnic University, Kowloon, Hong Kong SAR

Conference Talk: Long-term Adaptive VCG Auction Mechanism for Sustainable Federated Learning with Periodical Client Shifting

June 24, 2024

COMP 50th Anniversary Research Student Conference at New World Millennium Hong Kong Hotel, TST East, Kowloon, Hong Kong SAR

Conference Talk: Sustainable Federated Learning with Long-term Online VCG Auction Mechanism

July 12, 2022

IEEE 42nd International Conference on Distributed Computing Systems (ICDCS) at Savoia Regency Hotel, Bologna, Italy

Tutorial 1 on Relevant Topic in Your Field

March 01, 2013

Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA

Teaching

• Teaching Assistant, COMP4431: Artificial Intelligence, 2020 Fall.
• Teaching Assistant, COMP4434: Big Data Analytics, 2021 Fall.
• Teaching Assistant, COMP5511: Artificial Intelligence Concept, 2022 Spring.
• Teaching Assistant, COMP5511: Artificial Intelligence Concept, 2022 Fall.
• Teaching Assistant, COMP4121: E-Commerce Technology and Applications, 2023 Spring.

Skills

• Programming languages: C, C++, Matlab, Python.
• Development environments or tools: Ubuntu, Tensorflow, PyTorch, Spark, Ray, Docker, Selenium.

Service and leadership

• Reviewers for IEEE TMC, IEEE TCC, IEEE IoTJ, IEEE TNSESI, IEEE TSUSC, and IEEE INFOCOM.