Wei Chen 陈薇
讲师、硕士生导师 |
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个人简介
陈薇，博士、讲师、硕士生导师。本科（2015年）和博士（2020年，保研，硕博连读）均毕业于广东工业大学。2018年9月受国家留学基金委资助赴美国卡内基梅隆大学进行联合培养。 研究兴趣专注于机器学习、因果推断、因果表征学习等人工智能相关的系列理论与方法，及其在智能运维、神经科学、心理健康等领域的应用。 主持国家自然科学基金青年项目、广东省自然科学基金面上项目、中国博士后科学基金面上项目、广州市科技计划项目，参与国家自然科学基金广东省联合基金重点项目、新一代人工智能国家科技重大专项等项目。 以第一作者或通讯作者发表学术论文20余篇，包括IEEE TNNLS、Science China Information Sciences、ICML、AAAI、IJCAI、Neurocomputing等人工智能或机器学习领域国际顶级期刊或顶会。 指导学生获中国国际“互联网+”大学生创新创业大赛总决赛金奖、语音识别顶会ICASSP通信网络智能运维大赛二等奖等。
欢迎对机器学习、数据挖掘、因果推断、人工智能等研究方向感兴趣的研究生或本科生联系我，一起开展科研工作。
个人简历请发送至本人邮箱chenweidelight@gmail.com
教育经历
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广东工业大学
中国, 广州 - 计算机科学与技术学士和计算机应用工程博士学位 2011 年 9 月 - 2020 年 7 月
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卡内基梅隆大学(Carnegie Mellon University)
美国 - 机器学习(联合培养)博士 2018 年 9 月 - 2019 年 9 月
相关链接
Github: https://github.com/DMIRLAB-Group
Causal Learn: causal-learn: Causal Discovery in Python
工作经历
广东工业大学
- 博士后研究员，讲师 2020 年 7 月 - 现在
研究兴趣
- 因果关系发现与因果性学习
- 人工智能、机器学习等等
News
- 2026/1/26, 一篇文章“CausalAgent: A Conversational Multi-Agent System for End-to-End Causal Inference”被IUI 2026录用！
- 2025/11/8, 一篇文章“Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants”被AAAI 2026录用！
- 2025/10/8, 一篇文章“Higher Order Cumulants-Based Method for Direct and Efficient Causal Discovery”被IEEE Transactions on Neural Networks and Learning Systems期刊录用！
- 2025/4/30, 一篇文章“Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting”被IJCAI 2025录用!
- 2025/4/16, 一篇文章“Temporal Latent Variable Structural Causal Model for Causal Discovery under External Interferences”被Neurocomputing录用!
- 2024/4/17, 一篇文章“Individual Causal Structure Learning from Population Data”被IJCAI 2024录用！
- 2023/12/10, 一篇文章“Identification of Causal Structure with Latent Variables based on Higher Order Cumulants”被AAAI 2024录用！
- 2023/4/25, 一篇文章“Causal Discovery with Latent Confounders Based on Higher-Order Cumulants”被ICML 2023录用！
科研项目
- 广东省自然科学基金面上项目，2025-01至2027-12，主持
- 广州市科技计划项目， 2024-01至2026-12，主持
- 国家自然科学基金青年基金项目，2023-01至2025-12，主持
- 科技创新2030“新一代人工智能”重大项目， 2021-12至2025-11，子课题负责人
- 中国博士后科学基金面上项目，2021-06至2022-06，主持
主要论文
- Jiawei Zhu#, Wei Chen#*, Ruichu Cai. CausalAgent: A Conversational Multi-Agent System for End-to-End Causal Inference. IUI 2026
- Wei Chen, Wanyang Gu, Linjun Peng, Ruichu Cai*, Zhifeng Hao, Kun Zhang. Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants. AAAI 2026
- Wei Chen, Linjun Peng, Zhiyi Huang, Ruichu Cai*, Zhifeng Hao, Kun Zhang*. Higher Order Cumulants-Based Method for Direct and Efficient Causal Discovery. IEEE Transactions on Neural Networks and Learning Systems 2025
- Wei Chen, Jiahao Zhang, Haipeng Zhu, Boyan Xu, Zhifeng Hao, Keli Zhang, Junjian Ye, Ruichu Cai*. Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting. IJCAI 2025
- Ruichu Cai, Xiaokai Huang, Wei Chen*, Zijian Li, Zhifeng Hao. Temporal Latent Variable Structural Causal Model for Causal Discovery under External Interferences. Neurocomputing 2025
- Wei Chen, Xiaokai Huang, Zijian Li, Ruichu Cai*, Zhiyi Huang, Zhifeng Hao. Individual Causal Structure Learning from Population Data. IJCAI 2024
- Wei Chen, Zhiyi Huang, Ruichu Cai*, Zhifeng Hao, Kun Zhang. Identification of Causal Structure with Latent Variables based on Higher Order Cumulants. AAAI 2024
- Ruichu Cai, Zhiyi Huang, Wei Chen*, Zhifeng Hao, Kun Zhang. Causal Discovery with Latent Confounders Based on Higher-Order Cumulants. ICML 2023
- Wei Chen, Ruichu Cai*, Kun Zhang, Zhifeng Hao. Causal Discovery in Linear Non-Gaussian Acyclic Model with Multiple Latent Confounders. IEEE Transactions on Neural Networks and Learning Systems, 2021
- Ruichu Cai, Yunjin Wu, Xiaokai Huang, Wei Chen*, Tom Z. J. Fu, Zhifeng Hao. Granger Causal Representation Learning for Groups of Time Series. Science China Information Sciences, 2024
- Ruichu Cai, Liting Huang, Wei Chen*, Jie Qiao, Zhifeng Hao. Learning Dynamic Causal Mechanisms from Non-stationary Data. Applied Intelligence, 2023
- Wei Chen, Jibin Chen, Ruichu Cai*, Yuequn Liu, Zhifeng Hao. Learning Granger Causality for Non-stationary Hawkes Processes. Neurocomputing, 2022
学术兼职
- 会议审稿人: ICML 2022-2025, NeurIPS 2022-2025, ICLR 2023-2026, IJCAI 2025, UAI 2022-2024, AAAI 2025-2026, AISTATS 2024, CLEAR 2024-2026, CDML 2020
- 期刊审稿人: Journal of the American Statistical Association, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), Neural Network, Neurocomputing, Transactions on Machine Learning Research (TMLR), and so on.