Fuzhen Zhuang (庄福振)
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I am currently a full Professor in Institute of Artificial Intelligence, Beihang University.
I am the Director of Research Center for Intelligent Perception and Cognition (智能感知与认知研究中心主任), Institute of Artificial Intelligence, Beihang University.
My research interests include Machine Learning and Data Mining, including Transfer Learning, Multi-task Learning, Multi-view Learning, Recommendation Systems and Knowledge Graph.
I have published more than 150 papers in the prestigious refereed conferences and journals, such as KDD, WWW, SIGIR, ICDE, IJCAI, AAAI, EMNLP, Nature Communications, IEEE TKDE, ACM TKDD, IEEE T-CYB, IEEE TNNLS, ACM TIST, etc.
Address: XueYuan Road No.37, HaiDian District, BeiJing, China.
Homepage of Our Research Group: https://ktl.buaa.edu.cn/.
Email: zhuangfuzhen@buaa.edu.cn & zfz20081983@gmail.com
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Motto: If you want to harvest, please try your best! Keep your heart passional, everything is possible!
I am always seeking for the high intelligent and diligent intern students! If you are interested in my group, please contact me by email zhuangfuzhen@buaa.edu.cn.
The new book "Transfer Learning Algorithms: Applications and Practices" (迁移学习算法:应用与实践) has launched.
书籍:迁移学习算法:应用与实践。正式出版,2023。
News
I am invited to serve as the Area Chair of KDD 2025 (Aug Cycle).
I am invited to serve as the Area Chair of AAAI 2025.
I serve as the Area Chair of KDD 2024, AAAI 2024, the Senior PC of SDM 2024 and PAKDD 2024.
Two papers have been accepted by NeurIPS 2024.
Xi Chen, Chuan Qin, Chuyu Fang, Chao Wang, Chen Zhu, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong.: Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking. NeurIPS 2024.
Mingyi Li, Xiao Zhang, Qi Wang, Tengfei LIU, Ruofan Wu, Weiqiang Wang, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu.: Resource-Aware Federated Self-Supervised Learning with Global Class Representations. NeurIPS 2024.
One paper has been accepted by ACM MM 2024.
Yuting Zhang, Zhao Zhang, Yiqing Wu, Ying Sun, Fuzhen Zhuang*, Wenhui Yu, Lantao Hu, Han Li, Kun Gai, Zhulin An, Yongjun Xu.: Tag Tree-Guided Multi-grained Alignment for Multi-Domain Short Video Recommendation. ACM MM 2024.
Two papers have been accepted by TOIS 2024.
Ying Sun, Yang Ji, Hengshu Zhu, Fuzhen Zhuang, Qing He, Hui Xiong.: Market-aware Long-term Job Skill Recommendation with Explainable Deep Reinforcement Learning. TOIS 2024.
Yiheng Jiang, Yuanbo Xu, Yongjian Yang, Funing Yang, Pengyang Wang, Chaozhuo Li, Fuzhen Zhuang, Hui Xiong.: TriMLP: A Foundational MLP-like Architecture for Sequential Recommendation. TOIS 2024.
Four papers have been accepted by TKDE 2024.
Yuanbo Xu, Fuzhen Zhuang, En Wang, Chaozhuo Li, Jie Wu.: Learning without Missing-At-Random Prior Propensity-A Generative Approach for Recommender Systems. TKDE 2024.
Xiao Zhang, Shuqing Xu, Huashan Chen, Zekai Chen, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu.: Rethinking Robust Multivariate Time Series Anomaly Detection: A Hierarchical Spatio-Temporal Variational Perspective. TKDE 2024.
Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang*, Yu Zhao, Deqing Wang, Hongwei Zheng.: Temporal Knowledge Graph Reasoning with Dynamic Memory Enhancement. TKDE 2024.
Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang∗, Xu Zhang, Leyu Lin, Qing He.: Personalized Prompt for Sequential Recommendation. TKDE 2024.
Four papers have been accepted by KDD 2024.
Yuting Zhang, Yiqing Wu, ruidong han, Ying Sun, Yongchun Zhu, Xiang Li, Wei Lin, Fuzhen Zhuang*, Zhulin An, Yongjun Xu.: Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation. KDD 2024.
Yanjie Gou, Yuanzhou Yao, Zhao Zhang, Yiqing Wu, Yi Hu, Fuzhen Zhuang, Jiangming Liu, Yongjun Xu.: Controllable Multi-Behavior Recommendation for In-Game Skins with Large Sequential Model. KDD 2024.
Yiqing Wu, Ruobing Xie, Zhao Zhang, Xuonezhang, Fuzhen Zhuang, Leyu Lin, Zhanhui Kang, Yongjun Xu.: Dual-frequency Graph Neural Network for Sign-aware Recommendation. KDD 2024.
Huaming Du, Long Shi, Xingyan Chen, Yu Zhao, Hegui Zhang, Carl Yang, Fuzhen Zhuang, Gang Kou.: Representation Learning of Temporal Graphs with Structural Roles. KDD 2024.
One paper has been accepted by AAAI 2024.
Wei Chen, YuXuan Liu, Zhao Zhang, Fuzhen Zhuang*, Jiang Zhong.: Modeling Adaptive Inter-Task Feature Interactions via Sentiment-Aware Contrastive Learning for Joint Aspect-Sentiment Prediction. AAAI 2024.
Two papers have been accepted by TOIS 2023.
Wei Chen, Yiqing Wu, Zhao Zhang, Fuzhen Zhuang*, Zhongshi He, Ruobin Xie, Feng Xia.: FairGap: Fairness-aware Recommendation via Generating Counterfactual Graph. TOIS 2023.
Yuting Zhang, Ying Sun, Fuzhen Zhuang*, Yongchun Zhu, Zhulin An, Yongjun Xu.: Triple Dual Learning for Opinion-Based Explainable Recommendation. TOIS 2023.
Two paper has been accepted by ICDE 2024.
Yongjing Hao, Pengpeng Zhao, Junhua Fang, Jianfeng Qu, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou.: Meta-optimized Structural and Semantic Contrastive Learning for Graph Collaborative Filtering. ICDE 2024.
Yongjing Hao, Pengpeng Zhao, Junhua Fang, Jianfeng Qu, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou.: Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation. ICDE 2024.
Our paper has been selected as Best Short Paper in CIKM 2023.
Zhao Zhang, Fuwei Zhang, Fuzhen Zhuang*, Yongjun Xu.: Knowledge Graph Error Detection with Hierarchical Path Structure. CIKM 2023.
One paper has been accepted by TKDE 2023.
Tao Zou, Le Yu, Leilei Sun, Bowen Du, Deqing Wang, Fuzhen Zhuang.: Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction. TKDE 2023.
Two papers have been accepted by KDD 2023.
Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang*, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu.: Modeling Dual Period-Varying Preferences for Takeaway Recommendation. KDD 2023. (ADS Track)
Chuyu Fang, Chuan Qin, Qi Zhang, Kaichun Yao, Jingshuai Zhang, Hengshu Zhu, Fuzhen Zhuang*, Hui Xiong.: RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent Recruitment. KDD 2023. (ADS Track)
Eight papers have been accepted by SIGIR 2023.
Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang*, Zhulin An, Fei Wang, Yongjun Xu.: Weighted Knowledge Graph Embedding. SIGIR 2023. (Full paper)
Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong.: Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph. SIGIR 2023. (Full paper)
Xiao Zhang, Ziming Ye, Jianfeng Lu, Fuzhen Zhuang, Yanwei Zheng, Dongxiao Yu.: Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity. SIGIR 2023. (Full paper)
Hanwen Du, Huanhuan Yuan, Pengpeng Zhao, Fuzhen Zhuang, Guanfeng Liu, Lei Zhao, Yanchi Liu, Victor S. Sheng.: Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation. SIGIR 2023. (Full paper)
Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Junhua Fang, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu, Victor Sheng.: Meta-optimized Contrastive Learning for Sequential Recommendation. SIGIR 2023. (Full paper)
Xinyu Du, Huanhuan Yuan, Pengpeng Zhao, Jianfeng Qu, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu, Victor S Sheng.: Frequency Enhanced Hybrid Attention Network for Sequential Recommendation. SIGIR 2023. (Full paper)
Shuokai Li, Jingbo Zhou, Jizhou Huang, Hao Chen, Fuzhen Zhuang, Qing H, Dejing Dou.: Matching Point of Interests and Travel Blog with Multi-view Information Fusion. SIGIR 2023. (Short paper)
Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Jie Zhou, Yongjun Xu, Qing He.: Attacking Pre-trained Recommendation. SIGIR 2023. (Short paper)
One paper has been accepted by ACL 2023.
Ting Jiang, Deqing wang, Fuzhen Zhuang, Ruobing Xie, Feng Xia.: Pruning Pre-trained Language Models Without Fine-Tuning. ACL 2023.
One paper has been accepted by TPAMI 2023.
Chuanguang Yang, Zhulin An, Helong Zhou, Fuzhen Zhuang, Yongjun Xu, Qian Zhang.: Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition. TPAMI 2023.
Two papers have been accepted by TheWebConf 2023.
Yuxin Ying, Fuzhen Zhuang, Yongchun Zhu, Deqing Wang, Hongwei Zheng.: CAMUS: Attribute-Aware Counterfactual Augmentation for Minority Users in Recommendation. TheWebConf 2023.
Yuanzhou Yao, Zhao Zhang, Kaijia Yang, Huasheng Liang, Qiang Yan, Fuzheng Zhuang, Boyu Diao, Yongjun Xu, Chao Li.: A Knowledge Enhanced Hierarchical Fusion Network for CTR Prediction under Account Search Senario in WeChat. TheWebConf 2023 (Industry Track).
One paper has been accepted by TOIS 2022.
Qiming Li, Zhao Zhang, Fuzhen Zhuang, Yongjun Xu, and Chao Li. Topic-aware Intention Network for Explainable Recommendation with Knowledge Enhancement. TOIS 2022.
One paper has been accepted by KDD 2022.
Xiexiong Lin, Huaisong Li, Tao Huang, Feng Wang, Taifeng Wang, Tianyi Zhang, Fuzhen Zhuang, Linlin Chao.: A Logic Aware Neural Generation Method for Explainable Data-to-text. KDD 2022. (ADS Track)
One paper has been accepted by IJCAI 2022.
Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang.: Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. IJCAI 2022.
Three papers have been accepted by SIGIR 2022.
Shuokai Li, Ruobing Xie, Yongchun Zhu, Xiang Ao, Fuzhen Zhuang, Qing He.: User-Centric Conversational Recommendation with Multi-Aspect User Modeling. SIGIR 2022. (Long)
Yongchun Zhu, Qiang Sheng, Juan Cao, Shuokai Li, Danding Wang, Fuzhen Zhuang.: Generalizing to the Future: Mitigating Entity Bias in Fake News Detection. SIGIR 2022. (Short)
Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xiang Ao, Xu Zhang, Leyu Lin, Qing He.: Selective Fairness in Recommendation via Prompts. SIGIR 2022. (Short)
One paper has been accepted by TheWebConf 2022.
Zhendong Chen, Siu Cheung Hui, Lejian Liao, Fuzhen Zhuang, Fei Li, Meihuizi Jia, Jiaqi Li.: EvidenceNet: Evidence Fusion Network for Fact Verification. TheWebConf 2022.
Five papers have been accepted by TKDE 2022.
Yu Zhao, Shaopeng Wei, Huaming Du, Xingyan Chen, Qing Li, Fuzhen Zhuang, Ji Liu, Kang Kou.: Learning Bi-typed Multi-relational Heterogeneous Graph via Dual Hierarchical Attention Networks. TKDE 2022.
Yu Zhao, Huaming Du, Ying Liu, Shaopeng Wei, Xingyan Chen, Fuzhen Zhuang, Qing Li, Gang Kou.: Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks. TKDE 2022.
Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang.: Memory-Guided Multi-View Multi-Domain Fake News Detection. TKDE 2022.
Yuyang Xu, Haochao Ying, Siyi Qian, Fuzhen Zhuang, Xiao Zhang, Deqing Wang, Jian Wu, Hui Xiong.: Time-aware Context-Gated Graph Attention Network for Clinical Risk Prediction. TKDE 2022.
Yu Zhao, Han Zhou, Anxiang Zhang, Ruobing Xie, Qing Li, Fuzhen Zhuang*.: Connecting Embeddings Based on Multiplex Relational Graph Attention Networks for Knowledge Graph Entity Typing. TKDE 2022.
One paper has been accepted by AAAI 2022.
Fuwei Zhang, Zhao Zhang, Xiang Ao, Dehong Gao, Fuzhen Zhuang, Yi Wei, Qing He: Mind the Gap: Cross-Lingual Information Retrieval with Hierarchical Knowledge Enhancement. AAAI 2022.
Research Interests
Machine Learning
Data Mining
Transfer Learning
Multi-task Learning
Multi-view Learning
Recommender Systems.
Knowledge Graph.
Professional Experience
Professor. Institute of Artificial Intelligence, Beihang University, Apr 2021 - Present.
Associate Professor. Institute of Computing Technology Chinese Academy of Sciences, Sep 2013 - Mar 2021.
Technical Consultant. Baidu Inc., Sep 2016 - Feb 2017.
Visiting Scholar. Microsoft Research Asia, Apr 2015 - Oct 2015.
Assistant Professor. Institute of Computing Technology, CAS, Jul 2011 - Sep 2013.
Visiting Student. University of Minnesota Twin Cities (UMN), Sep 2010 - Mar 2011.
Visiting Internship Student. Hong Kong University of Science and Technology (HKUST), Jul 2010 - Aug 2010.
Education
Ph.D. in Computer Science. Institute of Computing Technology, Chinese Academy of Sciences, July, 2011.
B.E. in Computer Science. Chongqing University (CQU), 2006.
Honors and Award
Dec. 2020 Excellent researcher in Institute of Computing Technology, CAS
Dec. 2019 Excellent researcher in Institute of Computing Technology, CAS
Jan. 2017 The Youth Innovation Promotion Association of Chinese Academy of Sciences
Jan. 2016 The outstanding researcher in Institute of Computing Technology, CAS
Dec. 2012-2015 Excellent researcher in Institute of Computing Technology, CAS (one time per year)
Jul. 2015 The Champion of IJCAI 2015 Data Mining Competition (1/753)
Oct. 2013 Best Doctoral Dissertation Award, Chinese Association for Artificial Intelligence
Dec. 2011 Outstanding Graduate Student, Graduate University of Chinese Academy of Sciences
Oct. 2010 Best Paper Candidate & Student Travel Award, ACM CIKM 2010
Apr. 2010 Best Paper Candidate, SIAM SDM 2010
Jun. 2007-2010 Excellent Student, Chinese Academy of Sciences (one time per year)
Jan. 2009 Xia Peisu Scholarship, Institute of Computing Technology
Jul. 2006 Excellent Graduate Student, ChongQing City (top 0.5%)
Research Grants
“The Research on Intelligent Recruitment Algorithms Based on Graph Neural Networks”, the National Natural Science Foundation of China, 590,000RMB, 2022.1 - 2025.12.
“Study on Open Knowledge Computable Model and Computing Method for Network Big Data”, the National Natural Science Foundation of China, 640,000RMB (2,560,000RMB in total), 2019.1 - 2022.12.
“Multi-source Uncertain Data Mining Method and Technique”, the National Key Research and Development Program of China, 600,000RMB (3,420,000RMB in total), 2018.5 - 2021.5.
“The Research on Recommendation Algorithms based on Deep Learning”, the National Natural Science Foundation of China, 640,000RMB, 2018.1 - 2021.12.
“The Youth Innovation Promotion Association CAS 2017146”, Chinese Academy of Sciences, 800,000RMB, 2017.1 - 2020.12.
“The Research on Multi-task Multi-view Learning Algorithms to Heterogeneous Environment”, the National Natural Science Foundation of China, 780,000RMB, 2015.1 - 2018.12.
“The Application of Machine Learning Algorithm in Operator Big Data”, ZTE, 200,000RMB, 2017.1 - 2017.12.
“2015 Microsoft Research Asia Collaborative Research Program”, MSRA, 100,000RMB, 2016.1 - 2016.12.
“The Research on Knowledge Graph Constructing Methods based on Web Data”, Baidu Inc., 100,000RMB, 2016.1 - 2016.12.
“The Research of Transfer Learning Algorithms based on Generative Model with Applications”, the National Natural Science Foundation of China, 240,000RMB, 2013.1 - 2015.12.
“Research and Development of Public Service Support Technology in Urban Population Life Cycle”, National High-tech R&D Program of China (863 Program), 713,600RMB (4,460,000RMB in total), 2013.1 - 2015.12.
“The Develop of Parallel Data Mining System”, Key Lab of Web Data in ICT, 300,000RMB, 2011.8 - 2012.7.
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