Biography

Zhao Zhang is an Associate Professor at School of Computer Science and Engineering, Beihang University. Before joining Beihang University, he was an associate professor at the Institute of Computing Technology, Chinese Academy of Sciences, working with Prof. Yongjun Xu and Prof. Fei Wang. Zhao obtained his Ph.D. in 2021 from ICT, CAS, he was more than lucky to be co-supervised by Prof. Qing He and Prof. Fuzhen Zhuang during his doctoral studies. Previously, Zhao got the B.Eng. degree in Computer Science and Technology from Bejing Institute of Technology. From Sept. 2019 to Sept. 2020, Zhao visited the UCL NLP Lab at University College London (UCL), where he worked with Prof. Sebastian Riedel and Dr. Pasquale Minervini.
Zhao Zhang's research interests lie in data mining and applied machine learning, with a special focus on the representation and application of knowledge. Currently, he is working on the following topics:

• Large Language Model (LLM), Retrieval-augmented Generation (RAG), Agentic Reasoning, Agent Memory
• Knowledge Graph (KG), KG Construction/Embedding/Completion, KG for NLP/data mining Tasks
• Recommendation System (RS), Information Retrieval (IR), LLM-based RS/IR, GNN/KG for RS/IR, Trustworthy RS

Recruiting: The master's and doctoral programs for enrollment in 2026 have already been filled. Master and PhD positions admited in 2027 are still available. There are also internship positions that are open to undergraduate students at Beihang University.

Education

Experience

Publications

[Google Scholar]

2026

• Wei Chen, Xingyu Guo, Shuang Li, Zhao Zhang, Yan Zhong, Fuzhen Zhuang, Deqing wang. Learning Adaptive Distribution Alignment with Neural Characteristic Function for Graph Domain Adaptation. International Conference on Learning Representations (ICLR), 2026.
• Wei Chen, Xingyu Guo, Shuang Li, Yan Zhong, Zhao Zhang, Fuzhen Zhuang, Hongrui Liu, Libang Zhang, Guo Ye, Huimei He. Learning Structure-Semantic Evolution Trajectories for Graph Domain Adaptation. International Conference on Learning Representations (ICLR), 2026.
• Zhuo Chen, Fei Wang, Zixuan Li, Zhao Zhang, Weiwei Ding, Chuanguang Yang, Yongjun Xu, Xiaolong Jin, Jiafeng Guo. KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA. The Web Conference (WWW), 2026.
• Fuwei Zhang, Xiaoyu Liu, Dongbo Xi, Jishen Yin, huan chen, Peng Yan, Fuzhen Zhuang, Zhao Zhang. Multi-Aspect Cross-modal Quantization for Generative Recommendation. The 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026.
• Jiawei He, Zhanpeng Guan, Fuwei Zhang, Zhao Zhang, Yongjun Xu. Bootstrapping in the Loop: Multi-hop Question Answering via Alternating Decomposition and Retrieval. The 19th ACM International WSDM Conference (WSDM), 2026.
• Xiaoyu Liu, Fuwei Zhang, Yiqing Wu, Xinyu Jia, Zenghua Xia, Fuzhen Zhuang, Zhao Zhang, Fei Jiang, Wei Lin.: CAT-ID2: Category-Tree Integrated Document Identifier Learning for Generative Retrieval In E-commerce. The 19th ACM International WSDM Conference (WSDM), 2026.



2025

• Yujie Li, Shao Zezhi, Chengqing Yu, Tangwen Qian, Zhao Zhang, Yifan Du, Shaoming He, Fei Wang, Yongjun Xu. STA-GANN: A Valid and Generalizable Spatio-Temporal Kriging Approach. 34rd ACM International Conference on Information and Knowledge Management (CIKM), 2025.
• Wei Chen, Meng Yuan, Zhao Zhang, Ruobing Xie, Fuzhen Zhuang, Deqing Wang, Rui Liu. FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2025.
• Fuwei Zhang, Xiaoyu Liu, Jia Xinyu, Yingfei Zhang, Shuai Zhang, Xiang Li, Wei Lin, Fuzhen Zhuang, Zhao Zhang. Multi-level Relevance Document Identifier Learning for Generative Retrieval. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.
• Fuwei Zhang, Xiaoyu Liu, Jia Xinyu, Yingfei Zhang, Zenghua Xia, Fei Jiang, Wei Lin, Fuzhen Zhuang, Zhao Zhang. HierGR: Hierarchical Semantic Representation Enhancement for Generative Retrieval in Food Delivery Search. The 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025.
• Wei Chen, Zhao Zhang, Meng Yuan, Kepeng Xu, Fuzhen Zhuang. FCKT: Fine-Grained Cross-Task Knowledge Transfer with Semantic Contrastive Learning for Targeted Sentiment Analysis. The 34th International Joint Conference on Artificial Intelligence (IJCAI), 2025.
• Yiqing Wu, Ruobing Xie, Zhao Zhang, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Zhanhui Kang, Zhulin An, Yongjun Xu. ID-centric pre-training for recommendation. ACM Transactions on Information Systems (TOIS), 2025.
• Chengqing Yu, Fei Wang, Zezhi Shao, Tangwen Qian, Zhao Zhang, Wei Wei, Zhulin An, Qi Wang, and Yongjun Xu. GinAR+: A Robust End-To-End Framework for Multivariate Time Series Forecasting with Missing Values. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2025.
• Zhanpeng Guan, Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang, Fei Wang, Zhulin An, Yongjun Xu. AdaE: Knowledge Graph Embedding with Adaptive Embedding Sizes. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2025.
• Meng Yuan, Zhao Zhang, Wei Chen, Chu Zhao, Tong Cai, Deqing Wang, Rui Liu, Fuzhen Zhuang. HEK-CL: Hierarchical Enhanced Knowledge-Aware Contrastive Learning for Recommendation. ACM Transactions on Information Systems (TOIS), 2025.
• Yiqing Wu, Zhao Zhang, Fei Wang, Yongjun Xu, Jincai Huang. Toward more economical large-scale foundation models: No longer a game for the few. The Innovation, 2025.
• Zhanpeng Guan, Zhao Zhang, Yiqing Wu, Fuwei Zhang, Yongjun Xu. Should We Use a Fixed Embedding Size? Customized Dimension Sizes for Knowledge Graph Embedding. The 31st International Conference on Computational Linguistics (COLING), 2025.
• Yuxiao Gao, Fuwei Zhang, Zhao Zhang, Xiaoshuang Min, Fuzhen Zhuang. Mixed-Curvature Multi-Modal Knowledge Graph Completion. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025.
• Wei Chen, Guo Ye, Yakun Wang, Zhao Zhang, Libang Zhang, Daixin Wang, Zhiqiang Zhang, Fuzhen Zhuang. Smoothness Really Matters: A Simple yet Effective Approach for Unsupervised Graph Domain Adaptation. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025.



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 MULTIMEDIA (MM), 2024.
• Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang, Zhiqiang Zhang, Jun Zhou and Deqing Wang. Multi-view Temporal Knowledge Graph Reasoning. 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024.
• Caijun Xu, Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang and Rui Liu. Exploring High-Order User Preference with Knowledge Graph for Recommendation. 33rd ACM International Conference on Information and Knowledge Management (CIKM), 2024.
• Yiqing Wu, Ruobing Xie, Zhao Zhang, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Zhanhui Kang, Yongjun Xu. DFGNN: Dual-frequency Graph Neural Network for Sign-aware Feedback. 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (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. 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
• Chengqing Yu, Fei Wang, Zezhi Shao, Tangwen Qian, Zhao Zhang, Wei Wei, Yongjun Xu. GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing. 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024.
• Zezhi Shao, Fei Wang, Yongjun Xu, Wei Wei, Chengqing Yu, Zhao Zhang, Di Yao, Tao Sun, Guangyin Jin, Xin Cao, Gao Cong, Christian S.Jensen, Xueqi Cheng. Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
• Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang, Yu Zhao, Deqing Wang, Hongwei Zheng. Temporal Knowledge Graph Reasoning with Dynamic Memory Enhancement. IEEE Transactions on Knowledge and Data Engineering (TKDE), 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 Scenario 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

• Outstanding Mentor Award, Tencent Rhino-Bird Elite Training Program, 2024.
• Outstanding Research Fellow of the Institute of Computing Technology, Chinese Academy of Sciences, 2023.
• CIKM 2023 Best Short Paper Award, 2023.
• DASFAA 2022 Best Student Paper Award, 2022.
• Excellence Award of Rhino Bird Special Research Project, 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.