Dr. Yu YANG

I am an Assistant Professor with the School of Data Science at City University of Hong Kong. I am also a member of Hong Kong Institute for Data Science (HKIDS). I obtained my Ph.D. in Computing Science from Simon Fraser University in Feb 2019. Before that, I obtained my M.E. from University of Science and Technology of China in 2013, and my B.E. from Hefei University of Technology in 2010, both in Computer Science.

My research interests lie in the algorithmic aspects of data science, with an emphasis on devising effective and efficient algorithmic tools for mining data of combinatorial structures (such as graphs, sets and sequences) and data-driven operations management. I also have strong interests in machine learning theory, especially in applying learning theory to accelerate data processing. Openings in my group.


Selected Publications

[Google Scholar]

[ _ indicates my advisees, indicates student collaborators in other groups, * indicates equal contribution]

Papers in Refereed Journals

Papers in Refereed Conferences


Academic Services

  • Editorial Board

    • Associate Editor for Frontiers In Big Data
  • PC Member

    • SIGMOD: International Conference on Management of Data (2022)
    • Neural Information Processing Systems (2022)
    • SIGKDD Conference on Knowledge Discovery and Data Mining (2018, 2019, 2020, 2021, 2022)
    • Proceedings of the VLDB Endowment (2021)
    • ACM SIGIR Conference on Research and Development in Information Retrieval (2020, 2021, 2022)
    • ACM International Conference on Web Search and Data Mining (2021, 2022, 2023)
    • ACM International Conference on Information and Knowledge Management (2019, 2021, 2022)
    • SIAM International Conference on Data Mining (2019, 2020, 2021, 2022, 2023)
  • Journal Reviewer

    • IEEE Transactions on Knowledge and Data Engineering (TKDE)
    • ACM Transactions on Knowledge Discovery from Data (TKDD)
    • INFORMS Journal on Computing (JOC)
    • IISE Transactions
    • Data Mining and Knowledge Discovery (DMKD)
    • Knowledge and Information Systems (KAIS)

Teaching

  • SDSC5003 - Storing and Retrieving Data (CityU HK), Instructor
  • SDSC3001 - Big Data: The Arts and Science of Scaling (CityU HK), Instructor
  • SDSC3002 - Data Mining (CityU HK), Instructor
  • SDSC2004/GE2343 - Data Visualization (CityU HK), Instructor

Algorithmic Data Science Group

I am fortunate to work with a group of talented Ph.D. students and Research Assistants to solve challenging and crucial algorithmic problems in data science:

  • Mr. Yang HU (joint Ph.D. student with XJTU, 2021.9-present, BS from Nanjing University of Aeronautics and Astronautics)
  • Mr. Yuan LI (Ph.D. student, 2022.9-present, BS from Central South University)
  • Mr. Longtao TANG (Ph.D. student, 2020.9-present, BS from University of Science and Technology of China)
  • Mr. Jun WANG (Ph.D. student, 2020.9-present, MS and BS from University of Science and Technology of China)
  • Mr. Yifan YANG (joint Ph.D. student with USTC, 2022.9-present, BS from University of Science and Technology of China)
  • Mr. Hongbin ZHANG (joint Ph.D. student with XJTU, 2020.9-present, BS from China University of Mining and Technology)
  • Mr. Qixin ZHANG (Ph.D. student, 2020.9-present, BS from University of Science and Technology of China)
  • Mr. Lyuyi ZHU (Ph.D. student, 2021.9-present, BS from Zhejiang University)
  • Mr. Zhicheng LIANG (RA, 2022.8-present, MS from CityU HK, BS from Jinan University)
  • Alumni

  • Mr. Xiangru JIAN (RA, 2020.9-2022.8, MS from CityU HK, BS from Tongji University, next hop: PhD student in CS, University of Waterloo)
  • Acknowledgement

    Our research is generously supported by City University of Hong Kong, Hong Kong RGC, Hong Kong Institute for Data Science, Alibaba Group, DataStory, etc.

    Openings

    I am looking for highly motivated PhD students and Postdoc fellows. Please send me your CV and transcripts if you are interested. Due to the high volume of emails, I may not be able to reply to each of them. However, I do read every applicant's email. Please do not be offended if I do not reply.
    I am not interested in applying "fancy" deep nets and tricks in "interesting" applications. Potential research topics for students who want to work with me include, but are not limited to:

  • Submodular optimization and applications
  • Discrete choice models
  • Stochastic, online, and combinatorial optimization problems in Operations Management
  • Representation learning and generative models for graphs
  • Approximate nearest neighbor search in high-dimensional spaces
  • General graph mining and learning
  • I expect students to have a strong background in probability & statistics, algorithm design & analysis, optimization and programming.