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蔡瑞初,，教授、博士生導(dǎo)師、DMIR實(shí)驗(yàn)室主任,、國(guó)家優(yōu)秀青年基金獲得者。

2010年于華南理工大學(xué)獲得工學(xué)博士學(xué)位,，并進(jìn)入廣東工業(yè)大學(xué)工作,；2015年并被評(píng)為教授、博士生導(dǎo)師,；曾先后到新加坡國(guó)立大學(xué),、UIUC高等數(shù)字科學(xué)研究中心訪問學(xué)習(xí)。

蔡教授專注于因果關(guān)系發(fā)現(xiàn)與因果性學(xué)習(xí),、深度學(xué)習(xí)等領(lǐng)域的理論與應(yīng)用研究,。在上述領(lǐng)域先后主持國(guó)家優(yōu)秀青年基金、科技部”科技創(chuàng)新2030“重大項(xiàng)目,、省杰出青年基金,、省特支計(jì)劃等項(xiàng)目；提出了因果關(guān)系發(fā)現(xiàn)與因果性學(xué)習(xí)系列理論與方法,，在ICML,、NIPS、AAAI,、IJCAI等領(lǐng)域重要會(huì)議和TNNLS,、TKDE等國(guó)際著名期刊發(fā)表論文100余篇；解決了因果故障定位,、因果決策優(yōu)化,、因果個(gè)性推薦等應(yīng)用難題，相關(guān)成果在華為,、網(wǎng)易,、騰訊、滴滴,、唯品會(huì),、南方電網(wǎng)、南方通信建設(shè)等企業(yè)實(shí)施,，取得了良好的經(jīng)濟(jì)和社會(huì)價(jià)值,；獲得省科學(xué)技術(shù)一等獎(jiǎng)（第三完成人）、國(guó)家發(fā)明專利獎(jiǎng)優(yōu)秀獎(jiǎng)（第三完成人）等獎(jiǎng)項(xiàng),；指導(dǎo)學(xué)生獲得NeurIPS 2019解耦學(xué)習(xí)算法大賽第一名,、亞太因果推理大會(huì)推理大賽第一名,、“互聯(lián)網(wǎng)+”全國(guó)決賽金獎(jiǎng)等獎(jiǎng)項(xiàng)等獎(jiǎng)項(xiàng)；先后擔(dān)任Neural Networks雜志Action Editor,，NeurIPS,、ICML等會(huì)議的Area Chair，IJCAI,、AAAI等會(huì)議的SPC等,。

·   因果關(guān)系發(fā)現(xiàn)

·   因果性學(xué)習(xí)

·   圖神經(jīng)網(wǎng)絡(luò)

博士后：因果推斷與因果性學(xué)習(xí)，待遇從優(yōu),！感興趣的同學(xué)可以直接給我郵件,，請(qǐng)附一份簡(jiǎn)歷和代表作。 

博士/碩士/優(yōu)秀本科學(xué)生：常年招收本人研究方向感興趣的學(xué)生與我合作科研工作,，現(xiàn)招收廣東工業(yè)大學(xué)計(jì)算機(jī)學(xué)院2024年9月入學(xué)的博士/碩士研究生,，感興趣的同學(xué)請(qǐng)郵件聯(lián)系我。

如果考慮選擇我作為您碩士/博士期間的導(dǎo)師,，那么請(qǐng)耐心閱讀以下注意事項(xiàng)：

1,、請(qǐng)先認(rèn)真思考對(duì)我的研究方向是否感興趣！

2,、如果有意愿讀博,，請(qǐng)直接告訴我，我會(huì)優(yōu)先考慮,！ 

3,、熟悉至少一門編程工具M(jìn)ATLAB/C/C++/JAVA/R/Python編程，最好熟悉Linux操作命令,；

4,、較好的抽象思維能力，對(duì)數(shù)學(xué)感興趣（起碼不排斥）,，有數(shù)學(xué)建模競(jìng)賽等經(jīng)歷是加分項(xiàng),；

5、積極主動(dòng),、能夠承擔(dān)一定壓力,、愿意接受挑戰(zhàn)。

6,、團(tuán)隊(duì)科研經(jīng)費(fèi)充足,，提供足夠的科研條件支持，包括參加學(xué)術(shù)會(huì)議,、發(fā)放研究補(bǔ)助/研究獎(jiǎng)勵(lì),、推薦表現(xiàn)優(yōu)秀的學(xué)生在研二研三到國(guó)外知名高校/研究機(jī)構(gòu)聯(lián)合培養(yǎng)（前提是你要足夠優(yōu)秀）。 

7,、研究生畢業(yè)之前必須寫出高水平學(xué)術(shù)論文（SCI/一級(jí)學(xué)報(bào)/CCF C類以上會(huì)議）,；

因果關(guān)系發(fā)現(xiàn)

· 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.

因果性學(xué)習(xí)

·  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

深度學(xué)習(xí)

·  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

因果效應(yīng)

·  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高級(jí)會(huì)員（生物信息學(xué)專業(yè)組委員,、大數(shù)據(jù)專委會(huì)通訊委員）、廣東省計(jì)算機(jī)學(xué)會(huì)青年工作委員會(huì)常委,、IEEE會(huì)員,、ACM會(huì)員

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、新一代人工智能國(guó)家科技重大專項(xiàng)：因果推理與決策理論模型研究

2,、國(guó)家自然科學(xué)基金優(yōu)秀青年基金：高維異構(gòu)數(shù)據(jù)數(shù)據(jù)因果推斷理論與方法

3,、國(guó)家自然科學(xué)基金面上項(xiàng)目：高維不完全觀察數(shù)據(jù)上的因果關(guān)系推斷及其應(yīng)用（已結(jié)題）

4、廣東省自然科學(xué)基金杰出青年基金：高維數(shù)據(jù)因果關(guān)系發(fā)現(xiàn)理論及其應(yīng)用（已結(jié)題）

5,、廣東省高等學(xué)校優(yōu)秀青年教師培養(yǎng)計(jì)劃入選對(duì)象（已結(jié)題）

6,、廣州市科技計(jì)劃項(xiàng)目：多源異構(gòu)大數(shù)據(jù)企業(yè)輿情智能監(jiān)測(cè)平臺(tái)（已結(jié)題）

7、國(guó)家自然科學(xué)基金青年基金：基于因果關(guān)系推斷的致病基因發(fā)現(xiàn)算法研究（已結(jié)題） 

1,、北京嘀嘀無線科技發(fā)展有限公司:  網(wǎng)約車場(chǎng)景下的XXXX問題研究（在研）

2、北京嘀嘀無線科技發(fā)展有限公司:  XXXX長(zhǎng)期效應(yīng)評(píng)估項(xiàng)目（已結(jié)題）

3,、華為技術(shù)有限公司：XXXX因果發(fā)現(xiàn)及隱變量檢測(cè)技術(shù)合作項(xiàng)目（在研）

4,、華為技術(shù)有限公司：高維因果網(wǎng)絡(luò)構(gòu)建及應(yīng)用技術(shù)合作項(xiàng)目 （已結(jié)題）

5、騰訊科技（深圳）有限公司：基于圖神經(jīng)網(wǎng)絡(luò)的領(lǐng)域自適應(yīng)網(wǎng)絡(luò)嵌入算法研究 （已結(jié)題）

6,、廣州唯品會(huì)研究院有限公司：基于大數(shù)據(jù)的用戶畫像個(gè)性化推薦算法（已結(jié)題）

7,、廣州唯品會(huì)研究院有限公司：基于機(jī)器學(xué)習(xí)的協(xié)同過濾服裝尺碼推薦算法（已結(jié)題）

1、國(guó)家優(yōu)秀青年基金獲得者

2,、廣東省自然科學(xué)基金杰出青年基金獲得者

3,、廣東特支計(jì)劃科技創(chuàng)新青年拔尖人才

4、珠江科技新星

5,、海量視頻內(nèi)容快速檢索與深度分析的關(guān)鍵技術(shù)及其應(yīng)用,，廣東省科學(xué)技術(shù)獎(jiǎng)（科技進(jìn)步），一等獎(jiǎng),，2015,，第三完成人

6、基于等價(jià)關(guān)系模型的智能算法設(shè)計(jì)理論與方法,，廣東省科學(xué)技術(shù)獎(jiǎng)（自然科學(xué)）,，二等獎(jiǎng)，2013,，第四完成人  

7,、一種基于產(chǎn)品信息結(jié)構(gòu)化的Web問答檢索系統(tǒng)，中國(guó)專利獎(jiǎng),，優(yōu)秀獎(jiǎng),，2019，第三完成人

1,、https://dmir.gdut.edu.cn/  (部分時(shí)間不能訪問)

2,、https://ruichucai.github.io/