About Me

Hi! I’m a Ph.D. student of Computer Science at Rensselaer Polytechnic Institute (RPI) under the supervision of Prof. Yao Ma. I received a bachelor’s degree in Quantitative Business Analysis and Computer Science from the University of Sydney and a master’s degree in Operations Research and Information Engineering from Cornell University. I also have work experience at Gap Inc, Cardinal Operations, and EY.

Research Interest

  • Graph Deep Learning
  • Data-centric Machine Learning (Active Learning, Data Valuation, Self-Supervised Learning etc.)
  • Large Language Models for Decision Making & Learning to Optimize

News

  • [05/2024] Glad to join AT&T Labs as a summer research intern
  • [05/2024] One paper accepted by KDD2024
  • [03/2024] Received the SDM’24 Doctoral Forum Travel Award
  • [01/2024] Check out our preprints on Graph Data Valuation and Graph Contrastive Learning Benchmarks!
  • [12/2023] One paper accepted by SDM2024
  • [12/2023] Awarded ACM WSDM24 Student travel award
  • [08/2023] Join RPI following my advisor Yao Ma
  • [07/2023] Invited for the Oral Presentation at KDD MLG 2023
  • [05/2023] Glad that I passed my PhD qualifying exam at NJIT
  • [08/2022] New preprint “Enhancing Graph Contrastive Learning with Node Similarity”
  • [07/2022] Accepted as a volunteer at KDD22
  • [04/2022] Received the SDM22 Student Travel Award
  • [03/2022] Accepted to present my research at SDM’22 Doctoral Forum
  • [03/2022] Invited to serve as an external reviewer for ACM SIGKDD 2022
  • [01/2022] Invited to serve as a PC member for WSDM2022-MLoG (Machine Learning on Graphs Workshop at WSDM’22)
  • [12/2021] Received the ACM WSDM22 Student Travel Award
  • [11/2021] Served as a subreviewer for The Web Conference 2022
  • [09/2021] Join and be the first student at Data Analytics and Machine Intelligence (DAMI) Lab

Publications and Preprints

  • [arXiv 2024] “Precedence-Constrained Winter Value for Effective Graph Data Valuation.”
  • [arXiv 2024] “Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks.”
    • Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma.
    • Read the paper
  • [KDD 2024] “Enhancing Graph Contrastive Learning with Node Similarity.”
  • [SDM 2024] “Active Learning for Graphs with Noisy Structures.”

Symposiums and Workshops

  • [MLG 2023] “Active Learning for Graphs with Noisy Structures.”
    • 19th International Workshop on Mining and Learning with Graphs (MLG 2023).
    • More Info
  • [SDM Doctoral Forum 2022] “A General Graph Contrastive Learning Boosting Framework”
    • International Conference on Data Mining (SDM 2022) Doctoral Forum, SIAM, Poster.
    • More Info

Awards

  • SDM 2024 Doctoral Forum Travel Award
  • WSDM 2024 Student Travel Award
  • WSDM 2022 Student Travel Award
  • SDM 2022 Doctoral Forum Travel Award

Services

  • Reviewer, The International Conference on Learning Representations (ICLR) 2024
  • Reviewer, ACM Transactions on Knowledge Discovery from Data (TKDD), 2023 - 2024
  • Reviewer, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024
  • Reviewer, SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024
  • External Reviewer, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases(ECML PKDD), 2023
  • External Reviewer, The Conference on Information and Knowledge Management (CIKM), 2022
  • Reviewer, Machine Learning on Graphs Workshop at WSDM, 2022
  • External Reviewer, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), 2022
  • External Reviewer, The Web Conference (WWW), 2022

Teaching

  • Head Teaching Assistant, Machine Learning From Data (CSCI 4100/6100), Fall 2024 RPI
  • Teaching Assistant, CSCI 2600 Principles of Software, Spring 2024 RPI
  • Teaching Assistant, CSCI 1100 Computer Science I, Fall 2023 RPI
  • Teaching Assistant, CS 675 Introduction to Machine Learning, Fall 2022 NJIT

Volunteering

  • 2022 ACM SIGKDD, Washington DC, U.S., 2022
  • Cornell Course Roster Scheduling under COVID-19 Emergency, 2020
    • Details: Member of Cornell’s Roster Team, implemented an optimization model for room scheduling and assignment under COVID-19 capacity constraints. Read news report.

Fun Pictures