Preprints

1. Causal Inference with Large Language Model: A Survey [PDF]
   Jing Ma
   Arxiv (2024)
2. Certified Causal Defense with Generalizable Robustness [PDF]
   Yiran Qiao, Yu Yin, Chen Chen, Jing Ma
   Arxiv (2024)
3. A Benchmark for Fairness-Aware Graph Learning [PDF]
   Yushun Dong, Song Wang, Zhenyu Lei, Zaiyi Zheng, Jing Ma, Chen Chen, Jundong Li
   Arxiv (2024)
   

Book Chapters

1. Causal Inference on Graphs [PDF]
   Jing Ma, Ruocheng Guo, Jundong Li
   Machine Learning for Causal Inference, Springer (2023)
2. Causal Inference and Recommendations [PDF]
   Yaochen Zhu, Jing Ma, Chen Chen, Jundong Li
   Machine Learning for Causal Inference, Springer (2023)
   

Tutorials

1. Causal Inference with Latent Variable: Recent Advances and Future Prospectives [PDF]
   Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li
   ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)
2. Machine Learning for Causal Inference [PDF]
   Zhixuan Chu, Jing Ma, Jundong Li, Sheng Li
   AAAI Conference on Artificial Intelligence (AAAI 2023)
3. Fairness in Graph Mining: Metrics, Algorithms, and Applications [PDF]
   Yushun Dong, Jing Ma, Chen Chen, Jundong Li
   The IEEE International Conference on Data Mining (ICDM 2022)
   

Conferences/Journals

1. Invariant Shape Representation Learning For Image Classification [PDF]
   Tonmoy Hossain, Jing Ma, Jundong Li, Miaomiao Zhang
   IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025.
2. A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law [PDF] [Reading List] Survey Certification
   Zhiyu Zoey Chen, Jing Ma, Xinlu Zhang, Nan Hao, An Yan, Armineh Nourbakhsh, Xianjun Yang, Julian McAuley, Linda Petzold, William Yang Wang
   Transactions on Machine Learning Research (TMLR), 2024.
3. Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions? [PDF]
   Zhe Hu, Tuo Liang, Jing Li, Yiren Lu, Yunlai Zhou, Yiran Qiao, Jing Ma, Yu Yin
   Neural Information Processing Systems (NeurIPS Oral), 2024. (Acceptance rate: 25.8%)
4. A Survey of Out-of-distribution Generalization for Graph Machine Learning from a Causal View [PDF]
   Jing Ma
   AI Magazine, 2024
5. View-consistent Object Removal in Radiance Fields [PDF]
   Yiren Lu, Jing Ma, Yu Yin
   ACM Multimedia (MM), 2024
6. GNNs Also Deserve Editing, and They Need It More Than Once [PDF]
   Shaochen Zhong, Duy Le, Zirui Liu, Zhimeng Jiang, Andrew Ye, Jiamu Zhang, Jiayi Yuan, Kaixiong Zhou, Zhaozhuo Xu, Jing Ma, Shuai Xu, Vipin Chaudhary, Xia Hu
   International Conference on Machine Learning (ICML), 2024. (Acceptance rate: 27.5%)
7. PyGDebias: A Python Library for Debiasing in Graph Learning [PDF]
   Yushun Dong, Zhenyu Lei, Zaiyi Zheng, Song Wang, Jing Ma, Alex Jing Huang, Chen Chen, and Jundong Li
   The Web Conference (formerly WWW), 2024. (Demo paper)
8. SD-Attack: Targeted Spectral Attacks on Graphs [PDF]
   Xianren Zhang, Jing Ma, Yushun Dong, Chen Chen, Min Gao, Jundong Li
   Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024
9. Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data [PDF]
   Qiang Huang, Jing Ma, Jundong Li, Ruocheng Guo, Huiyan Sun, Yi Chang
   ACM Transactions on Knowledge Discovery from Data (TKDD), 2023
10. Fair Few-shot Learning with Auxiliary Sets [PDF]
    Song Wang, Jing Ma, Lu Cheng, Jundong Li
    European Conference on Artificial Intelligence (ECAI), 2023. (Acceptance rate: 24%)
11. Learning Causal Effects on Hypergraphs (Extended abstract)
    Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan
    International Joint Conference on Artificial Intelligence (IJCAI), 2023
12. Path-Specific Counterfactual Fairness for Recommender Systems [PDF]
    Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Acceptance Rate: 22.1%)
13. Learning for Counterfactual Fairness from Observational Data [PDF] [Code]
    Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Acceptance Rate: 22.1%)
14. A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection [PDF]
    Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory R Madden, Daniel Borrajo, Jundong Li
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023. (Acceptance Rate: 22.1%)
15. Fairness in Graph Mining: A Survey [PDF]
    Yushun Dong, Jing Ma, Chen Chen, Jundong Li
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023
16. Interpreting Unfairness in Graph Neural Networks via Training Node Attribution [PDF]
    Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
    AAAI Conference on Artificial Intelligence (AAAI), 2022 (Acceptance rate: 19.6%)
17. CLEAR: Generative Counterfactual Explanations on Graphs [PDF] [Code]
    Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li
    Neural Information Processing Systems (NeurIPS), 2022 (Acceptance rate: 25.6%)
18. Learning Causality with Graphs [PDF] Most Widely-read Paper
    Jing Ma, Jundong Li
    AI Magazine, 2022
19. SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training [PDF]
    Qiang Huang, Jing Ma, Jundong Li, Huiyan Sun, Yi Chang
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2022. (Acceptance Rate: 26%)
20. Learning Causal Effects on Hypergraphs [PDF] [Code] Best Paper Award
    Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, Jaime Teevan
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. (Acceptance Rate: 14.99%)
21. Empowering Next POI Recommendation with Multi-Relational Modeling [PDF]
    Zheng Huang, Jing Ma, Yushun Dong, Natasha Foutz, Jundong Li
    ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), short paper, 2022. (Acceptance Rate: 24.73%)
22. Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US [PDF] [Code]
    Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li
    International World Wide Web Conference (WWW), 2022. (Acceptance Rate: 17.7%)
23. Learning Fair Node Representations with Graph Counterfactual Fairness [PDF] [Code]
    Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2022. (Acceptance Rate: 20.2%)
24. Multi-Cause Effect Estimation with Disentangled Confounder Representation [PDF] [Code]
    Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li
    International Joint Conference on Artificial Intelligence (IJCAI), 2021. (Acceptance Rate: 13.9%)
25. Learning from Crowds by Modeling Common Confusions [PDF] [Code]
    Zhendong Chu, Jing Ma, Hongning Wang
    AAAI Conference on Artificial Intelligence (AAAI), 2021. (Acceptance Rate: 21%)
26. Deconfounding with Networked Observational Data in a Dynamic Environment [PDF] [Code]
    Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li
    ACM International Conference on Web Search and Data Mining (WSDM), 2021. (Acceptance Rate: 18.6%)
27. Selective Sampling for Building Sensor Type Classification [PDF] [Code]
    Jing Ma, Dezhi Hong, Hongning Wang
    ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), 2020. (Acceptance Rate: 21.7%)
28. Distributed K-means Algorithm for Optimizing the Extended Index Layer on RDD
    Jing Ma, Li Li
    Computer Engineering and Applications (CE&A), 2022
29. Top-k Critical Vertices Query on Shortest Path [PDF]
    Jing Ma, Bin Yao, Xiaofeng Gao, Yanyan Shen, Minyi Guo
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018
30. Performance evaluation of WiFi Direct for data dissemination in mobile social networks [PDF]
    Zhifei Mao, Jing Ma, Yuming Jiang, Bin Yao
    IEEE Symposium on Computers and Communications (ISCC), 2017