所属学院： 计算机学院

导师类别： 硕士生导师

科研方向： 人工智能、机器学习、因果关系、强化学习

联系方式： qiaojie.chn@gmail.com

硕士招生学院： 计算机学院

个人主页： https://Jie-Qiao.github.io/

个人简述

乔杰，博士，特聘副教授、广东工业大学“青年百人”A类人才，硕士生导师。于2021年获广东工业大学计算机学院博士学位，随后以青年百人博士后研究员身份留校从事人工智能与因果推断领域的研究工作，期间获广东省青年优秀科研人才国际培养计划博士后项目资助，赴香港大学开展了为期近一年的学术访问。现任广东工业大学计算机学院特聘副教授，主要研究人工智能与因果关系，具体领域包括因果发现，因果推断，强化学习等。主持国家自然科学基金青年项目1项，参与国家自然科学基金项目2项。已发表高水平论文20余篇，包括CCF-A类会议NeurIPS、AAAI、IJCAI、ICML等，并长期担任IEEE TPAMI, NeurIPS, ICML, ICLR, AAAI, IJCAI, UAI, AISTATS, JMLR, Neural Network等顶级会议与权威期刊的审稿人。

教育背景

2016年09月-2021年12月 广东工业大学计算机工程与应用 博士

2012年09月-2016年06月 广东工业大学统计学 学士

工作经历

2025年05月至 今 广东工业大学，计算机学院，特聘副教授

2024年05月—2025年04月 香港大学，访问学者

2022年07月—2025年05月 广东工业大学，计算机学院，博士后研究员

主要论文

1. Jie Qiao, Ruichu Cai, Siyu Wu, Yu Xiang, Keli Zhang, Zhifeng Hao. “Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences.” The 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023). (CCF-A类论文)

2. Jie Qiao, Zhengming Chen, Jianhua Yu, Ruichu Cai, Zhifeng Hao. “Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model.” Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024). (CCF-A 类论文)

3. Jie Qiao∗, Yu Xiang∗, Zhengming Chen, Ruichu Cai, Zhifeng Hao. “Causal Discovery from Poisson Branching Structural Causal

4. Model Using High-Order Cumulant with Path Analysis.” Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024). (∗共同一作) (CCF-A 类论文)

5. Jie Qiao, Yiming Bai, Ruichu Cai, and Zhifeng Hao. “Learning causal structures using hidden compact representation.” Neurocomputing, 2021, 463: 328-333. (中科院二区期刊)

6. Jie Qiao, Yiming Bai, Ruichu Cai, and Zhifeng Hao. “Causal discovery from multi-domain data using the independence of modularities.” Neural Computing and Applications, 2022, 34(3): 1939–1949. (中科院二区期刊)

7. Jie Qiao, Ruichu Cai, Kun Zhang, Zhenjie Zhang, and Zhifeng Hao. “Causal Discovery with Confounding Cascade Nonlinear Additive Noise Models.” ACM Transactions on Intelligent Systems and Technology (TIST), 2021, 12(6): 1-28. (中科院三区期刊)

8. Ruichu Cai, Yuxuan Zhu, Jie Qiao∗, Zefeng Liang, Furui Liu, Zhifeng Hao. “Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples.” Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024) (∗ 通信作者) (CCF-A 类论文)

9. Yu Xiang∗, Jie Qiao∗, Zefeng Liang, Zihuai Zeng, Ruichu Cai, Zhifeng Hao. “On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function.” The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024) (∗ 共同一作) (CCF-A 类论文).

10. Weilin Chen∗, Jie Qiao∗, Ruichu Cai and Zhifeng Hao. “On the Role of Entropy-based Loss for Learning Causal Structures with Continuous Optimization.”IEEE Transactions on Neural Networks and Learning Systems (TNNLS). (∗ 共同一作) (CCF-A 类论文)

11. Zhengming Chen∗, Feng Xie∗, Jie Qiao∗, Zhifeng Hao, Kun Zhang, Ruichu Cai. “Identification of Linear Latent Variable Model with Arbitrary Distribution.” Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022). (∗ 共同一作) (CCF-A 类论文)

12. Yuequn Liu∗, Wenhui Zhu∗, Jie Qiao∗, et.al. ”Causal Alignment Based Fault Root Causes Localization for Wireless Network.” In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2022. (∗ 共同一作) (CCF-B 类论文)

13. Zhengming Chen, Jie Qiao, Feng Xie, Ruichu Cai, Zhifeng Hao, Keli Zhang. Testing Conditional Independence Between Latent Variables by Independence Residuals. IEEE Transactions on Neural Networks and Learning Systems. 2024. (中科院一区期刊)

14. Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, and Zhifeng Hao. “Causal discovery with cascade nonlinear additive noise models.” In 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019, 28(1): 1609-1615. (CCF-A 类论文)

15. Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, and Zhifeng Hao. “Causal discovery from discrete data using hidden compact representation.” Advances in neural information processing systems 31 (NeurIPS 2018), 2018. (CCF-A 类论文)

16. Ruichu Cai, Jie Qiao, Zhenjie Zhang, and Zhifeng Hao. “Self: structural equational likelihood framework for causal discovery.” In Proceedings of the AAAI Conference on Artificial Intelligence, 2018. (CCF-A 类论文)

17. Ruichu Cai, Siyu Wu, Jie Qiao, Zhifeng Hao, Keli Zhang, and Xi Zhang. “THPs: Topological Hawkes Processes for Learning Causal Structure on Event Sequences.” IEEE Transactions on Neural Networks and Learning Systems (TNNLS). (中科院一区期刊)

18. Ruichu Cai, Jincheng Ye, Jie Qiao, Huiyuan Fu, and Zhifeng Hao. “FOM: Fourth-order moment based causal direction identification on the heteroscedastic data.” Neural Networks, 2020, 124: 193-201. (中科院一区期刊)

19. Ruichu Cai, Zijian Li, Pengfei Wei, Jie Qiao, Kun Zhang, and Zhifeng Hao. “Learning disentangled semantic representation for domain adaptation.” In 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019. (CCF-A 类论文)

20. Ruichu Cai, Fengzhu Wu, Zijian Li, Jie Qiao, Wei Chen, Yuexing Hao, and Hao Gu. ”REST: Debiased Social Recommendation via Reconstructing Exposure Strategies.” In ACM Transactions on Knowledge Discovery in Data, Volume 18(2). (中科院三区期刊)

21. Zhengming Chen, Ruichu Cai, Feng Xie, Jie Qiao, Anpeng Wu, Zijian Li, Zhifeng Hao, Kun Zhang. “Learning Discrete Latent Variable Structures with Tensor Rank Conditions.” The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024). (CCF-A 类论文)

22. Yuequn Liu ,Ruichu Cai, Wei Chen, Jie Qiao, Yuguang Yan, Zijian Li, Keli Zhang, Zhifeng Hao. “TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences” Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024) (CCF-A 类论文)

科研项目

· 国家自然科学基金青年项目2025-2027 主持

· 联合基金-重点支持项目 2025-2028 参与

· 科技部研究计划重大项目2022-2025 参与

学术兼职

· 期刊审稿人：IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), Journal of Machine Learning Research (JMLR), Neural Network等.

· 会议审稿人：NeurIPS, ICML, ICLR, AAAI, IJCAI, UAI, AISTATS等.

教学活动

本科生课程：算法设计与分析

团队主页

数据挖掘与信息检索实验室 http://dmir.gdut.edu.cn/