Biography

I am an Associate Professor at Institute of Computing Technology (ICT), Chinese Academy of Sciences (CAS), where I obtained my Ph.D. in 2021. I am more than lucky to be co-supervised by Prof. Qing He and Prof. Fuzhen Zhuang during my doctoral studies. Before coming to ICT, I got my B.Eng. degree in Computer Science and Technology from Bejing Institute of Technology. From Sept. 2019 to Sept. 2020, I visited the UCL NLP Lab at University College London (UCL), where I worked with Prof. Sebastian Riedel and Dr. Pasquale Minervini.
My research interests lie in data mining and machine learning, with a special focus on the representation and application of knowledge graphs. Currently, I am working on the following topics:

• Knowledge Graphs (KGs), KG Construction/Embedding/Completion, KG for NLP Tasks
• Recommendation Systems (RS), KG for RS/Information Retrieval (IR), Fairness-aware RS
• Spatio-temporal Data Mining, Multivariate Time Series Forecasting, Traffic Forecasting

Recruiting: I have several 1-2 openings for visiting (bachelor, master, or Ph.D.) students on Knowledge Graph, Recommendation System, or other Data Ming and NLP topics. Both remote and onsite visiting are welcome. Ping me if interested!

Education

Experience

Publications

[Google Scholar]

2024

• Zhuo Chen, Zhao Zhang, Zixuan Li, Fei Wang, Yutao Zeng, Xiaolong Jin, Yongjun Xu. Self-Improvement Programming for Temporal Knowledge Graph Question Answering. The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), 2024.
• Huajie Zhang, Yuxin Ying, Fuzhen Zhuang, Haiqin Weng, Ying Sun, Zhao Zhang, Yiqi Tong and Yan Liu. Multi-round counterfactual generation: interpreting and improving models of text classification. The Web Conference (WWW), 2024. Short Paper
• 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. The 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024.
• Wei Chen, Yiqing Wu, Zhao Zhang, Fuzhen Zhuang, Zhongshi He, Ruobin Xie, Feng Xia. FairGap: Fairness-aware Recommendation via Generating Counterfactual Graph. ACM Transactions on Information Systems (TOIS), 2024.



2023

• Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang, Zhulin An, Fei Wang, Yongjun Xu. Weighted Knowledge Graph Embedding. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2023.
• Zhao Zhang, Fuwei Zhang, Fuzhen Zhuang, Yongjun Xu. Knowledge Graph Error Detection with Hierarchical Path Structure. The 32st ACM International Conference on Information and Knowledge Management (CIKM), 2023. Best Short Paper Award
• Yuanzhou Yao, Zhao Zhang, Kaijia Yang, Huasheng Liang, Qiang Yan and Yongjun Xu. An Auxiliary Task Boosted Multi-task Learning Method for Service Account Retrieval with Limited Human Annotation. The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.
• Meng Yuan, Fuzhen Zhuang, Zhao Zhang, Deqing Wang, Jin Dong. Knowledge-based Multiple Adaptive Spaces Fusion for Recommendation. The 17th ACM Conference on Recommender Systems (RecSys), 2023.
• Tangwen Qian, Yuan Wang, Yongjun Xu, Zhao Zhang, Lin Wu, Qiang Qiu, Fei Wang. A Model-agnostic Hierarchical Framework towards Trajectory Prediction. Journal of Computer Science and Technology (JCST), 2023.
• Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Jie Zhou, Yongjun Xu, Qing He. Attacking Pre-trained Recommendation. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 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. The Web Conference (WWW), 2023.
• Qiming Li, Zhao Zhang, Fuzhen Zhuang, Yongjun Xu, and Chao Li. Topic-aware Intention Network for Explainable Recommendation with Knowledge Enhancement. ACM Transactions on Information Systems (TOIS), 2023.
• Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu. Heterogeneous Graph Neural Network with Multi-view Representation Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.
• Yongjun Xu, Fei Wang, Zhulin An, Qi Wang, Zhao Zhang. Artificial intelligence for science - bridging data to wisdom. The Innovation, 2023.
• Fei Wang, Di Yao, Yong Li, Tao Sun, Zhao Zhang. AI-enhanced Spatial-Temporal Data Mining Technology: New Chance for Next-generation Urban Computing. The Innovation, 2023.



2022

• Zhao Zhang, Fuzhen Zhuang, Hengshu Zhu, Chao Li, Hui Xiong, Qing He, Yongjun Xu. Towards Robust Knowledge Graph Embedding via Multi-task Reinforcement Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 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. The Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 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. The 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022.
• Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu. Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting. 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022.
• Zezhi Shao, Zhao Zhang, Wei Wei, Fei Wang, Yongjun Xu, Xin Cao, Christian S Jensen. Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting. 48th International Conference on Very Large Databases (VLDB), 2022.
• Tangwen Qian, Yongjun Xu, Zhao Zhang, Fei Wang. Trajectory Prediction from Hierarchical Perspective. 30th ACM International Conference on Multimedia (MM), 2022.
• Tao Sun, Fei Wang, Zhao Zhang, Lin Wu, Yongjun Xu. Human Mobility Identification by Deep Behavior Relevant Location Representation. The International Conference on Database Systems for Advanced Applications (DASFAA), 2022. Best Student Paper Award
• Shuokai Li, Yongchun Zhu, Ruobing Xie, Zhengwei Tang, Zhao Zhang, Fuzhen Zhuang, Qing He, Hui Xiong. Customized Conversational Recommender Systems. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2022.
• Fuwei Zhang, Zhao Zhang, Xiang Ao, Fuzhen Zhuang, Yongjun Xu and Qing He. Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion. The 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
• Zezhi Shao, Zhao Zhang, Fei Wang, Wei Wei and Yongjun Xu. Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting. The 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
• Yuanzhou Yao, Zhao Zhang, Yongjun Xu, Chao Li. Data Augmentation for Few-Shot Knowledge Graph Completion from Hierarchical Perspective. The 29th International Conference on Computational Linguistics (COLING), 2022.
• Wei Chen, Jinglong Du, Zhao Zhang, Fuzhen Zhuang, Zhongshi He. A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis. The 29th International Conference on Computational Linguistics (COLING), 2022.
• Qiming Li, Zhao Zhang, Boyu Diao, Yongjun Xu, Chao Li. Towards Understanding the Effect of Node Features on the Predictions of Graph Neural Networks. The 31st International Conference on Artificial Neural Networks (ICANN), 2022.
• Jian Pan, Zhao Zhang, Fuzhen Zhuang, Jingyuan Yang and Zhiping Shi. Knowledge-aware Topological Networks for Recommendation. China Conference on Knowledge Graph and Semantic Computing (CCKS), 2022.



2021

• Zhao Zhang, Fuzhen Zhuang, Meng Qu, Zheng-Yu Niu, Hui Xiong, Qing He. Knowledge Graph Embedding with Shared Latent Semantic Units. Neural Networks, 2021.
• Runchuan Wang, Zhao Zhang, Fuzhen Zhuang, Dehong Gao, Yi Wei, Qing He. Adversarial Domain Adaptation for Cross-lingual Information Retrieval with Multilingual BERT. The 30th ACM International Conference on Information & Knowledge Management (CIKM), 2021.



2020

• Zhao Zhang, Fuzhen Zhuang, Hengshu Zhu, Zhiping Shi, Hui Xiong, Qing He. Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion. The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020.
• Shiyu Zhang, Zhao Zhang, Fuzhen Zhuang, Zhiping Shi, Xu Han. Compressing Knowledge Graph Embedding with Relational Graph Auto-encoder. The 10th International Conference on Electronics Information and Emergency Communication (ICEIEC), 2020.



2019

• Zhao Zhang, Fuzhen Zhuang, Xuebing Li, Zheng-Yu Niu, Jia He, Qing He, Hui Xiong. Knowledge Triple Mining via Multi-Task Learning. Information Systems, 80 (2019), 64-75.
• Xuebing Li, Ying Sun, Fuzhen Zhuang, Jia He, Zhao Zhang, Shijun Zhu, Qing He. Potential Off-Grid User Prediction System Based on Spark. ZTE Communications, 2019.



2018

• Zhao Zhang, Fuzhen Zhuang, Meng Qu, Fen Lin, Qing He. Knowledge Graph Embedding with Hierarchical Relation Structure. The 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018.
• Zhao Zhang, Fuzhen Zhuang, Zheng-Yu Niu, Deqing Wang, Qing He. MultiE: Multi-Task Embedding for Knowledge Base Completion. The 27th ACM International Conference on Information and Knowledge Management (CIKM), 2018.

Honors

• CIKM 2023 Best Short Paper Award, 2023.
• DASFAA 2022 Best Student Paper Award, 2022.
• Student Travel Award, AAAI, 2020.
• Pacemaker to Merit Student, University of Chinese Academy of Sciences, 2019.
• E Fund Scholarship, Institute of Computing Technology, Chinese Academy of Sciences, 2019.
• First-class Academic Scholarship, University of Chinese Academy of Sciences, 2018 & 2019.
• Student Travel Award, EMNLP, 2018.
• CASC Scholarship, Bejing Institute of Technology, 2015.