Jing Ma
Ph.D Candidate

Department of Computer Science
University of Virginia

Location: Rice Hall, Charlottesville, VA 22904
News | Research Interest | Education | Publications | Experience | Projects | Services | Awards

Email: jm3mr@virginia.edu
[Google Scholar] [DBLP]

News


Research Interest

I am broadly interested in machine learning and data mining. My current research focuses on causal inference and graph mining, and I have profound research experience in active learning, crowdsourcing, and distributed computing.


Education


Publications

  1. Jing Ma, Jundong Li, “Learning Causality with Graphs”, AI Magazine, 2022.

  2. Qiang Huang, Jing Ma, Jundong Li, Huiyan Sun, Yi Chang, “SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training”, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2022. (Acceptance Rate: 26%).

  3. Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan, “Learning Causal Effects on Hypergraphs”, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (Acceptance Rate: 14.99%). [PDF] [Code]

  4. Yushun Dong, Jing Ma, Chen Chen, Jundong Li, “Fairness in Graph Mining: A Survey”, Arxiv, 2022. [PDF]

  5. Zheng Huang, Jing Ma, Yushun Dong, Natasha Foutz, Jundong Li, “Empowering Next POI Recommendation with Multi-Relational Modeling”, ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022. (short paper) (Acceptance Rate: 24.73%).

  6. Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li, “Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US”, International World Wide Web Conference (WWW), 2022. (Acceptance Rate: 17.7%). [PDF] [Code]

  7. Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li, “Learning Fair Node Representations with Graph Counterfactual Fairness”, ACM International Conference on Web Search and Data Mining (WSDM), 2022. (Acceptance Rate: 20.2%). [PDF] [Code]

  8. Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li, “Multi-Cause Effect Estimation with Disentangled Confounder Representation”, International Joint Conference on Artificial Intelligence (IJCAI), 2021. (Acceptance Rate: 13.9%). [PDF] [Code]

  9. Zhendong Chu, Jing Ma, Hongning Wang, “Learning from Crowds by Modeling Common Confusions”, AAAI Conference on Artificial Intelligence (AAAI), 2021. (Acceptance Rate: 21%). [PDF] [Code]

  10. Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li. “Deconfounding with Networked Observational Data in a Dynamic Environment”, ACM International Conference on Web Search and Data Mining (WSDM), 2021. (Acceptance Rate: 18.6%). [PDF] [Code]

  11. Jing Ma, Dezhi Hong, Hongning Wang. “Selective Sampling for Building Sensor Type Classification”, ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), 2020. (Acceptance Rate: 21.7%). [PDF] [Code]

  12. Jing Ma, Li Li. “Distributed K-means Algorithm for Optimizing the Extended Index Layer on RDD”, Computer Engineering and Applications (CE&A), 2019.

  13. Jing Ma, Bin Yao, Xiaofeng Gao, Yanyan Shen, Minyi Guo. “Top-k Critical Vertices Query on Shortest Path”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018. [PDF]

  14. Zhifei Mao, Jing Ma, Yuming Jiang, Bin Yao. “Performance evaluation of WiFi Direct for data dissemination in mobile social networks”, IEEE Symposium on Computers and Communications (ISCC), 2017. [PDF]



Experience

  • 2022 Summer intern: Causal Machine Learning, Microsoft Research
  • 2021 Summer intern: Office of Applied Research, Microsoft
  • 2016 Visiting student, Norwegian University of Science and Technology (NTNU), Norway

Academic Activities

  • 2022, Invited presentation "Causality learning on graphs" at LinkedIn's Search & Recommendation AI Seminar
  • 2022, Poster presentation at SDM 2022
  • 2022, Poster presentation at CAPWIC 2022
  • 2022, Paper presentation at WWW 2022
  • 2022, Paper presentation at WSDM 2022
  • 2021, Poster presentation at SDM 2021
  • 2021, Poster presentation at CAPWIC 2021
  • 2021, Paper presentation at WSDM 2022
  • 2021, Paper presentation at IJCAI 2021

Projects

  • 2020, “Quantifying the Impact of Data Sharing on Outbreak Dynamics”, UVA Global Infectious Disease Institute
  • 2019, U.S. Department of Energy (DOE) Project

Services

Membership:

  • 2021-Present, AnitaB.org membership
  • 2020-Present, SIGIR (ACM) Student Member

Conference Program Committee:

  • 2022, KDD, AAAI, WSDM, CIKM, ECMLPKDD
  • 2021, EMNLP, CIKM, SMDS, AAAI

Reviewer:

  • 2022, KDD, WWW, AAAI, WSDM, CIKM, ECMLPKDD
  • 2021, EMNLP, TKDE, KAIS, ICML, WWW, ICLR, BigData, WSDM, NeurIPS, CIKM, ECMLPKDD
  • 2020, SIGKDD, SIGIR, ICML, PAKDD
  • 2019, SIGIR

Awards

Awards:

  • 2022, CAPWIC Best Poster Award
  • 2022, WSDM NSF Travel Award
  • 2022, SIGIR Travel Grant
  • 2021, GHC Student Scholarship Award
  • 2021, WWW Student Scholarship Award
  • 2021, SDM Student Travel Award
  • 2021, CAPWIC Student Travel Award
  • 2021, SIGIR Travel Grant
  • 2020, KDD Student Registration Award
  • 2020, SDM Student Travel Award
  • 2020, CAPWIC Student Travel Award

Scholarships:

  • 2019, UVA Computer Science Fellowship, UVA
  • 2017, Excellent Graduate Award, SJTU (One of the ultimate accolades)
  • 2016, Postgraduate Academic Excellence Scholarship, SJTU (Top 8%)
  • 2015, Excellent Bachelor’s Thesis Award, SJTU (Top 8%)
  • 2015, Undergraduate Academic Excellence Scholarship, SJTU (Top 8%)
  • 2014, Undergraduate Academic Excellence Scholarship, SJTU (Top 8%)
  • 2013, Undergraduate Academic Excellence Scholarship, SJTU (Top 8%)