蔡瑞初，教授、博士生导师、DMIR实验室主任、国家优秀青年基金获得者。

2010年于华南理工大学获得工学博士学位，并进入广东工业大学工作；2015年并被评为教授、博士生导师；曾先后到新加坡国立大学、UIUC高等数字科学研究中心访问学习。

蔡教授专注于因果关系发现与因果性学习、深度学习等领域的理论与应用研究。在上述领域先后主持国家优秀青年基金、科技部”科技创新2030“重大项目、省杰出青年基金、省特支计划等项目；提出了因果关系发现与因果性学习系列理论与方法，在ICML、NIPS、AAAI、IJCAI等领域重要会议和TNNLS、TKDE等国际著名期刊发表论文100余篇；解决了因果故障定位、因果决策优化、因果个性推荐等应用难题，相关成果在华为、网易、腾讯、滴滴、唯品会、南方电网、南方通信建设等企业实施，取得了良好的经济和社会价值；获得省科学技术一等奖（第三完成人）、国家发明专利奖优秀奖（第三完成人）等奖项；指导学生获得NeurIPS 2019解耦学习算法大赛第一名、亚太因果推理大会推理大赛第一名、“互联网+”全国决赛金奖等奖项等奖项；先后担任Neural Networks杂志Action Editor，NeurIPS、ICML等会议的Area Chair，IJCAI、AAAI等会议的SPC等。

·   因果关系发现

·   因果性学习

·   图神经网络

博士后：因果推断与因果性学习，待遇从优！感兴趣的同学可以直接给我邮件，请附一份简历和代表作。 

博士/硕士/优秀本科学生：常年招收本人研究方向感兴趣的学生与我合作科研工作，现招收广东工业大学计算机学院2024年9月入学的博士/硕士研究生，感兴趣的同学请邮件联系我。

如果考虑选择我作为您硕士/博士期间的导师，那么请耐心阅读以下注意事项：

1、请先认真思考对我的研究方向是否感兴趣！

2、如果有意愿读博，请直接告诉我，我会优先考虑！ 

3、熟悉至少一门编程工具MATLAB/C/C++/JAVA/R/Python编程，最好熟悉Linux操作命令；

4、较好的抽象思维能力，对数学感兴趣（起码不排斥），有数学建模竞赛等经历是加分项；

5、积极主动、能够承担一定压力、愿意接受挑战。

6、团队科研经费充足，提供足够的科研条件支持，包括参加学术会议、发放研究补助/研究奖励、推荐表现优秀的学生在研二研三到国外知名高校/研究机构联合培养（前提是你要足够优秀）。 

7、研究生毕业之前必须写出高水平学术论文（SCI/一级学报/CCF C类以上会议）；

因果关系发现

· Yu Xiang†, Jie Qiao†, Zhefeng Liang, Zihuai Zeng, Ruichu Cai*, Zhifeng Hao. On the Identifiability of Poisson Branching Structural Causal Model Using Probability Generating Function. NeurIPS 2024.

· 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. NeurIPS 2024.

·  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.
·  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. AAAI 2024.
·  Jie Qiao, Zhengming Chen, Jianhua Yu, Ruichu Cai*, Zhifeng Hao. Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model. AAAI 2024.
·  Jie Qiao, Yu Xiang, Zhengming Chen, Ruichu Cai*, Zhifeng Hao. Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis. AAAI 2024.  

·  Weilin Chen, Jie Qiao, Ruichu Cai*, Zhifeng Hao. On the role of entropy-based loss for learning causal structures with continuous optimization. TNNLS 2023.

·  Ruichu Cai, Zhiyi Huang, Wei Chen, Zhifeng Hao, Kun Zhang. Causal Discovery with Latent Confounders Based on Higher-Order Cumulants. ICML 2023.

·  Jie Qiao, Ruichu Cai*, Kun Zhang, Zhenjie Zhang, Zhifeng Hao. Causal Discovery with Confounding Cascade Nonlinear Additive Noise Models. ACM Transactions on Intelligent Systems and Technology (TIST), 2021: 12(6): 1-28
·  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
·  Feng Xie, Ruichu Cai*, Yan Zeng, Jiantao Gao, Zhifeng Hao. An Efficient Entropy-Based Causal Discovery Method for Linear Structural Equation Models with IID Noise Variables. IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(5): 1667 - 1680
·  Ruichu Cai, Jincheng Ye, Jie Qiao, Huiyuan Fu, Zhifeng Hao. FOM: Fourth-Order Moment based Causal Direction Identification on the Heteroscedastic Data. Neural Networks, 2020, 124:193-201
·  Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang. Triad Constraints for Learning Causal Structure of Latent Variables. NeurIPS 2019
·  Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao. Causal Discovery with Cascade Nonlinear Additive Noise Model. IJCAI 2019
·  Ruichu Cai, Zhenjie Zhang, Zhifeng Hao, Marianne Winslett. Sophisticated Merging over Random Partitions: A Scalable and Robust Causal Discovery Approach. IEEE Transactions on Neural Networks and Learning Systems, 2018:29(8) : 3623 - 3635
·  Ruichu Cai, Jie Qiao, Zhenjie Zhang , et al. SELF: Structural Equational Likelihood Framework for Causal Discovery. AAAI 2018
·  Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang, Zhifeng Hao. Causal Inference from Discrete Data using Hidden Compact Representation. NeurIPS 2018
·  Ruichu Cai, Zhenjie Zhang, Zhifeng Hao. SADA: A General Framework to Support Robust Causation Discovery. ICML 2013
·  Jie Qiao, Ruichu Cai, Siyu Wu, Yu Xiang, Kun Zhang, Zhifeng Hao. Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event. IJCAI 2023
·  Ruichu Cai, Siyu Wu, Jie Qiao, Zhifeng Hao, Keli Zhang, Xi Zhang. THPs: Topological Hawkes Processes for Learning Causal Structure on Event Sequences. IEEE Transactions on Neural Networks and Learning Systems. 2017, 28(8):1801-1813.
·  Ruichu Cai, Zhenjie Zhang, Zhifeng Hao, Marianne Winslett. Understanding Social Causalities Behind Human Action Sequences. IEEE Transactions on Neural Networks and Learning Systems. 2017, 28(8):1801-1813.

因果性学习

·  Yan Zeng, Ruichu Cai, Fuchun Sun, Libo Huang, Zhifeng Hao. A survey on causal reinforcement learning. TNNLS 2024

·  Ruichu Cai*, Fengzhu Wu, Zijian Li, Jie Qiao, Wei Chen, Yuexing Hao, Hao Gu. REST: Debiased Social Recommendation via Reconstructing Exposure Strategies. TKDD 2023
·  Zijian Li, Ruichu Cai*, Tom Fu, Zhifeng Hao, Kun Zhang. Transferable time-series forecasting under causal conditional shift. TPAMI 2023
·  Ruichu Cai, Jiawei Chen, Zijian Li, Wen Chen, Keli Zhang, Junjian Ye, Zhuozhang Li, Xiaoyan Yang, Zhenjie Zhang. Time Series Domain Adaptation via Sparse Associative Structure Alignment. AAAI 2021
·  Ruichu Cai, Jiahao Li, Zhenjie Zhang, Xiaoyan Yang, Zhifeng Hao. DACH: Domain Adaptation without Domain Information. IEEE Transactions on Neural Networks and Learning Systems, 2020:31(12):5055-5067
·  Ruichu Cai, Zijian Li, Pengfei Wei, Jie Qiao, Kun Zhang, Zhifeng Hao. Learning Disentangled Semantic Representation for Domain Adaptation. IJCAI 2019

深度学习

·  Jiahao Li, Ruichu Cai*, Yuguang Yan. Combinatorial Routing for Neural Trees. IJCAI 2024.

·  Yuguang Yan, Zhihao Xu, Canlin Yang, Jie Zhang, Ruichu Cai*, Michael Kwok-Po Ng. An Optimal Transport View for Subspace Clustering and Spectral Clustering. AAAI 2024
·  Yuguang Yan, Yuanlin Chen, Shibo Wang, Hanrui Wu, Ruichu Cai*. Hypergraph Joint Representation Learning for Hypervertices and Hyperedges via Cross Expansion. AAAI 2024
·  Xuexin Chen, Ruichu Cai*, Zhengting Huang, Yuxuan Zhu, Julien Horwood, Zhifeng Hao, Zijian Li, Jose Miguel Hernandez-Lobato. Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation. ICML 2023

·  Xuexin Chen, Ruichu Cai*, Yuan Fang, Min Wu, Zijian Li, Zhifeng Hao. Motif Graph Neural Network. IEEE Transactions on Neural Networks and Learning Systems. 2023, Early Access
·  Wu, Ruichu Cai. A selection-pattern-aware recommendation model with colored-motif attention network. Neurocomputing, 2023: 538: 126-178
·  Ruichu Cai, Jinjie Yuan, Boyan Xu, Zhifeng Hao. SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL. NeurIPS 2021
·  Ruichu Cai, Hao Zhang, Wen Liu, Shenghua Gao, Zhifeng Hao. Appearance-Motion Memory Consistency Network for Video Anomaly Detection. AAAI 2021
·  Ruichu Cai, Zhihao Liang, Boyan Xu, zijian li, Yao Chen and Yuexing Hao. TAG: Type Auxiliary Guiding for Code Comment Generation. ACL 2020
·  Ruichu Cai, Xuexin Chen, Yuan Fang, Min Wu, Yuexing Hao. Dual-Dropout Graph Convolutional Network for Predicting Synthetic Lethality in Human Cancers. Bioinformatics, 2020, 36(16):4458-4465
·  Ruichu Cai, Boyan Xu, Xiaoyan Yang, Zhengjie Zhang, Zijian Li, Zhihao Liang. An Encoder-Decoder Framework Translating Natural Language to Database Queries. IJCAI 2018

因果效应

·  Yuguang Yan, Hao Zhou, Zeqin Yang, Weilin Chen, Ruichu Cai*, Zhifeng Hao. Reducing Balancing Error for Causal Inference via Optimal Transport. ICML 2024
·  Feng Xie, Zhengming Chen, Shanshan Luo, Wang Miao, Ruichu Cai, Zhi Geng. Automating the Selection of Proxy Variables of Unmeasured Confounders. ICML 2024
·  Weilin Chen, Ruichu Cai*, Zeqin Yang, Jie Qiao, Yuguang Yan, Zijian Li, Zhifeng Hao. Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning. ICML 2024
·  Ruichu Cai*, Weilin Chen, Zeqin Yang, Shu Wan, Chen Zheng, Xiaoqing Yang, Jiecheng Guo. Long-term Causal Effects Estimation via Latent Surrogates Representation Learning. Neural Networks, 2024
·  Yuguang Yan, Zeqin Yang, Weilin Chen, Ruichu Cai*, Zhifeng Hao, Michael Kwok-Po Ng. Exploiting Geometry for Treatment Effect Estimation via Optimal Transport. AAAI 2024
Ruichu Cai, Zeqin Yang, Weilin Chen, Yuguang Yan, Zhifeng Hao. Generalization Bound for Estimating Causal Effects from Observational Network Data. CIKM 2023

2019年及之前

·  Ruichu Cai, Zijie Lu, Li Wang, Zhenjie Zhang. DITIR: Distributed Index for High Throughput Trajectory Insertion and Real-time Temporal Range Query. PVLDB 2017
·  Ruichu Cai, Zhenjie Zhang, Srinivasan Parthasarathy, Anthony K. H. Tung, Zhifeng Hao, Wen Zhang. Multi-Domain Manifold Learning for Drug-Target Interaction Prediction. SDM 2016
·  Ruichu Cai, Zhifeng Hao, Marianne Winslett, Xiaokui Xiao, Yang Yin, Zhenjie Zhang, Shuigeng Zhou. Deterministic Identification of Specific Individuals from GWAS Results[J]. Bioinformatics, 2015, 31(11): 1701-1707
·  Ruichu Cai, Tung K.H. Anthony, Zhifeng Hao, Zhenjie Zhang. What is Unequal among the Equals? Ranking Equivalent Rules from Gene Expression Data. IEEE Transactions on Knowledge and Data Engineering, 2011;23(11):1735-1747

CCF高级会员（生物信息学专业组委员、大数据专委会通讯委员）、广东省计算机学会青年工作委员会常委、IEEE会员、ACM会员

Action Editor: Neural Networks

The Youth Editor: Fundamental Research

Area Chair: ICML2022, ICML2023, ICML2024, NeurIPS2022, NeurIPS2023, NeurIPS2024, ICLR2024, UAI2021, UAI2022, UAI2023 

Senior PC: AAAI 2019, AAAI 2020, IJCAI 2019, IJCAI2020

PC: AAAI 2015-2019, IJCAI 2018-2019, NIPS 2016-2022, ICML 2015-2022, AISTATS 2016-2022, ICLR 2018-2022

Publication Co-Chair: APWEB 2015

Reviewer: TNNLS, TKDE, TIST, Neural Network, Pattern Recognition, Bioinformatics, Neurocomputing, Information Sciences,  National Science Review, Plos ONE, Science China-Information Sciences

1、新一代人工智能国家科技重大专项：因果推理与决策理论模型研究

2、国家自然科学基金优秀青年基金：高维异构数据数据因果推断理论与方法

3、国家自然科学基金面上项目：高维不完全观察数据上的因果关系推断及其应用（已结题）

4、广东省自然科学基金杰出青年基金：高维数据因果关系发现理论及其应用（已结题）

5、广东省高等学校优秀青年教师培养计划入选对象（已结题）

6、广州市科技计划项目：多源异构大数据企业舆情智能监测平台（已结题）

7、国家自然科学基金青年基金：基于因果关系推断的致病基因发现算法研究（已结题） 

1、北京嘀嘀无线科技发展有限公司:  网约车场景下的XXXX问题研究（在研）

2、北京嘀嘀无线科技发展有限公司:  XXXX长期效应评估项目（已结题）

3、华为技术有限公司：XXXX因果发现及隐变量检测技术合作项目（在研）

4、华为技术有限公司：高维因果网络构建及应用技术合作项目 （已结题）

5、腾讯科技（深圳）有限公司：基于图神经网络的领域自适应网络嵌入算法研究 （已结题）

6、广州唯品会研究院有限公司：基于大数据的用户画像个性化推荐算法（已结题）

7、广州唯品会研究院有限公司：基于机器学习的协同过滤服装尺码推荐算法（已结题）

1、国家优秀青年基金获得者

2、广东省自然科学基金杰出青年基金获得者

3、广东特支计划科技创新青年拔尖人才

4、珠江科技新星

5、海量视频内容快速检索与深度分析的关键技术及其应用，广东省科学技术奖（科技进步），一等奖，2015，第三完成人

6、基于等价关系模型的智能算法设计理论与方法，广东省科学技术奖（自然科学），二等奖，2013，第四完成人  

7、一种基于产品信息结构化的Web问答检索系统，中国专利奖，优秀奖，2019，第三完成人

1、https://dmir.gdut.edu.cn/  (部分时间不能访问)

2、https://ruichucai.github.io/