About me

Welcome to my Homepage! I am Xudong Wang (王旭东) [xudongwang@link.cuhk.edu.cn], PhD Candidate in Computer Science from School of Data Science (SDS), The Chinese University of Hongkong, Shenzhen (CUHK-Shenzhen). Before that, I got the M.Sc. in Data Science from CUHK-Shenzhen in 2022. And in 2020, I got B.Sc. in Statistics from School of Mathematics and B.Ec. in Finance from School of Economics of Shandong University (SDU) respectively.

My research fields are Artificial intelligence (AI) and Machine Learning (ML). And my Phd research topics are Graph Representation Learning and Smart Grid. My Phd supervisors are Prof. Chris Ding [Google Scholar] and Prof. Tongxin Li.

Welcome to more exchanges and If you are interested in my research works, you can contact me via email: [xudongwang@link.cuhk.edu.cn].

Publication

• Paper: Learning Graph Representation via Graph Entropy Maximization

  • https://icml.cc/virtual/2024/poster/32687

  • Ziheng Sun, Xudong Wang, Chris Ding, Jicong Fan

  • The 41th International Conference on Machine Learning (ICML 2024)

• Paper: EVSense: a robust and scalable approach to non-intrusive EV charging detection

  • https://dl.acm.org/doi/10.1145/3538637.3538860.

  • Xudong Wang, Guoming Tang, Yi Wang, Srinivasan Keshav, Yu Zhang

  • The 13th ACM SIGEnergy International Conference on Future Energy Systems (ACM e-Energy 2022)

• Paper: More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring

  • https://www.computer.org/csdl/proceedings-article/ithings-greencom-cpscom-smartdata-cybermatics/2022/541700a292/1Hcn1zhTUic.

  • Yu Zhang, Guoming Tang, Qianyi Huang, Yi Wang, Hong Xu, Xudong Wang

  • The 15th IEEE International Conference on Cyber, Physical and Social Computing (IEEE CPSCom 2022)

• Paper: FedNILM: Applying Federated Learning to NILM Applications at the Edge

  • https://arxiv.org/abs/2106.07751.

  • Yu Zhang, Guoming Tang, Qianyi Huang, Yi Wang, Xudong Wang, Jiadong Lou

  • arXiv Preprint.

• Patent: 一种电动汽车充电监测方法及系统

  • 发明人: 武洋静; 王旭东

  • 专利号: CN202210620528, ICPC分类号: H02J3/00

Talk

• Presentation in International Conference ACM e-Energy 2022
  • Recording: https://youtu.be/sBAtrK5vS9U.
  • Slides: link

Teaching

• Teaching Assistant (TA) in SDS, CUHK-Shenzhen:
  • Leading TA, MFE5310 (PG Course) - Machine learning and its application, Term 2, AY2021-2022.
  • Leading TA, DDA3020 (UG Course) - Machine learning, Term 1, AY2022-2023.
    • Selected of my tutorial materials: Tutorial for Numpy and Sklearn API, Tutorial for Numpy Linear Algebra and Least Square Optimization Problem in Python.
    • Selected of my tutorial recordings: [1],[2].
  • Leading TA, MFE5310 (PG Course) - Machine learning and its application, Term 2, AY2022-2023.
  • TA, CSC6021 & AIR6001 & MDS6105 (PG Course) - Artificial Intelligence, Term 1, AY2023-2024.
    • Selected of my tutorial materials: Tutorial for Graph Representation.
  • Leading TA, MFE5310 (PG Course) - Machine learning and its application, Term 2, AY2023-2024.

HONORS & AWARDS