Rui  Zhang   (Rui is pronounced as Ray)

Email:        x@y
                   where  x = rayteam  and  y = yeah.net (preferred)
                   or where  x = rui.zhang  and  y = ieee.org

My group at Huazhong University of Science and Technology is hiring Academics (Professor, Associate Professor, Assistant Professor level) and Postdoc/Research Fellows with highly attractive packages, usually several publications in top venues required and overseas experience preferred. If you are interested, please send me an email.

General Information

Dr Rui Zhang is an internationally leading researcher in the areas of artificial intelligence and big data. He is a Distinguished Professor at Huazhong University of Science and Technology (HUST), Visiting Professor at Tsinghua University and was a Professor at the University of Melbourne. He is an ACM Distinguished Member, and has been a (visiting) research scientist in the research labs of top IT companies such as Microsoft and AT&T. He has made significant contributions in the fields of big data management and AI driven applications. He has won several awards including the prestigious Future Fellowship by the Australian Research Council in 2012, Chris Wallace Award for Outstanding Research by the Computing Research and Education Association of Australasia (CORE) in 2015, and Google Faculty Research Award in 2017. He has won best paper awards in leading conferences such as a Best Paper in SIGKDD 2016 and a Best Paper Honorable Mention in WSDM 2024. His inventions have been adopted by major IT companies such as Microsoft, Amazon and AT&T. He obtained his Bachelor's degree from Tsinghua University in 2001, PhD from National University of Singapore in 2006, and has then started as a faculty member in The University of Melbourne since 2007. Before joining the University of Melbourne, he has been a visiting research scientist at AT&T labs-research in New Jersey and at Microsoft Research in Redmond, Washington. He has also been a regular visiting researcher at Microsoft Research Asia in Beijing. Dr Zhang's research interests include big data and AI, particularly in areas of multi-modal generation, large language models, recommender systems, knowledge graphs, spatial and temporal data analytics, moving object management and data streams. He is an Associate Editor of IEEE Transactions on Dependable and Secure Computing (TDSC, CCF-A, JCR Q1), World Wide Web Journal (CCF-B, JCR Q1), and on the Editorial Board of Information Processing & Management (ISSN: 0306-4573, JCR Q1) and MDPI Mathematics, Section “E1: Mathematics and Computer Science” (EISSN 2227-7390, JCR Q1). He has served as chairing roles in top conferences such as Web Conference, SIGMOD, AAAI, ICDE, etc.

Research  

Recent publications         Full list       Full list with pdf, bibtex and code Haozhao Wang, Wenchao Xu, Jingzhi Wang, Yunfeng Fan, Xiaoquan Yi and Rui Zhang. pFedDKS: Detached Knowledge Sharing for Personalized Federated Learning. The ACM WEB Conference (WWW) 2026. 　 Senyao Li, Haozhao Wang, Wenchao Xu, Rui Zhang, Song Guo, Jingling Yuan, Xian Zhong, Tianwei Zhang, Ruixuan Li. Collaborative Inference and Learning between Edge SLMs and Cloud LLMs: A Survey of Algorithms, Execution, and Open Challenges. ACM Computing Surveys. 2026. 　 Qiyu Qin, Yichen Li, HaozhaoWang, Cheng Wang, Rui Zhang, Ruixuan Li. Unbiased Rectification for Sequential Recommender Systems under Fake Orders. AAAI 2026. 　 Yichen Li, Yichen Tan, Yijing Shan, Haozhao Wang, Rui Zhang, Imran Razzak, Ruixuan Li. Data-Centric Sequential Recommendation with Relation-Augmented Generation. AAAI 2026. 　 Yichen Li, Haozhao Wang, Wenchao Xu, Tianzhe Xiao, Hong Liu, Minzhu Tu, Yuying Wang, Xin Yang, Rui Zhang, Shui Yu, Song Guo, Ruixuan Li. Unleashing the power of continual learning on non-centralized devices: A survey. IEEE Communications and Tutorials. 28: 1059-1098, 2026. 　 Yichen Li, Yuying Wang, Jiahua Dong, Haozhao Wang, Yining Qi, Rui Zhang, Ruixuan Li. Resource-Constrained Federated Continual Learning: What Does Matter? NeurIPS 2025. 　 Xiaoquan Yi, Haozhao Wang, Yining Qi, Wenchao Xu, Rui Zhang, Yuhua Li, Ruixuan Li. ChatbotID: Identifying Chatbots with Granger Causality Test. NeurIPS 2025. 　 Ziwen Zhao, Yixin Su, Yuhua Li, Yixiong Zou, Ruixuan Li, Rui Zhang. A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective. IEEE Transactions on Knowledge and Data Engineering (TKDE). 37(8): 4389-4410, 2025. 　 Xingyu Lu, Jinpeng Wang, Jieming Zhu, Zhicheng Zhang, Deqing Zou, Hai-Tao Zheng, Shu-Tao Xia, Rui Zhang. ROMA: Recommendation-Oriented Language Model Adaptation Using Multi-Modal Multi-Domain Item Sequences. The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025. 4670-4681. 　 Yixin Su,Wei Jiang, Fangquan Lin,ChengYang, Sarah M. Erfani, Junhao Gan,YunxiangZhao, RuixuanLi, Rui Zhang. Intrinsic and Extrinsic Factor Disentanglement for Recommendation in Various Context Scenarios, ACM Transactions on Information Systems, 43(3), 82, 1-32, 2025. 　 Guanghao Meng, Sunan He, Jinpeng Wang, Tao Dai, Letian Zhang, Jieming Zhu, Qing Li, Gang Wang, Rui Zhang, Yong Jiang, EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models, AAAI 2025. 　 Tu Gu, Kaiyu Feng, Jingyi Yang, Gao Cong, Cheng Long, Rui Zhang, BT-Tree: A Reinforcement Learning Based Index for Big Trajectory Data, ACM SIGMOD Conference 2025. 　 Haojie Wei, Jun Yuan, Rui Zhang, Quanyu Dai, Yueguo Chen, MAJL: A Model-Agnostic Joint Learning Framework for Music Source Separation and Pitch Estimation, ACM Multimedia (MM) 2024. 　 Xiaoyan Zhao, Yang Deng, Min Yang, Lingzhi Wang, Rui Zhang, Hong Cheng, Wai Lam, Ying Shen, Ruifeng Xu, A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers, ACM Computing Surveys, 56 (11), 293, pp 1-39, 2024. 　 Xiaoteng Shen, Rui Zhang, Xiaoyan Zhao, Jieming Zhu, Xi Xiao, PMG : Personalized Multimodal Generation with Large Language Models, The Web Conference 2024. (Slides of Multimodal Generation for Recommendation) 　 Jieming Zhu, Chuhan Wu, Rui Zhang, Zhenhua Dong, Multimodal Pretraining and Generation for Recommendation: A Tutorial, The Web Conference 2024. 　 Yushen Li, Jinpeng Wang, Tao Dai, Jieming Zhu, Jun Yuan, Rui Zhang, Shu-Tao Xia, RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction, The Web Conference 2024. (Short paper) 　 Jiyuan Yang, Yue Ding, Yidan Wang, Pengjie Ren, Zhumin Chen, Fei Cai, Jun Ma, Rui Zhang, Zhaochun Ren, Xin Xin, Debiasing Sequential Recommenders through Distributionally Robust Optimization over System Exposure, The 17th ACM International Conference Web Search and Data Mining (WSDM) 2024. Best Paper Honorable Mention Award. 　 Hengchang Hu, Wei Guo, Xu Liu, Yong Liu, Ruiming Tang, Rui Zhang, Min-Yen Kan, User Behavior Enriched Temporal Knowledge Graph for Sequential Recommendation, The 17th ACM International Conference Web Search and Data Mining (WSDM) 2024. 　 Kexin Zhang, Yichao Wang, Xiu Li, Ruiming Tang, Rui Zhang, IncMSR: An Incremental Learning Approach for Multi-Scenario Recommendation, The 17th ACM International Conference Web Search and Data Mining (WSDM) 2024. 　 Shiwei Li, Huifeng Guo, Xing Tang, Ruiming Tang, Lu Hou, Ruixuan Li, Rui Zhang, Embedding Compression in Recommender Systems: A Survey, ACM Computing Surveys, 56 (5), pp 1–21, 2024. 　 Rui Zhang, Yixin Su, Bayu Distiawan Trisedya, Xiaoyan Zhao, Min Yang, Hong Cheng, Jianzhong Qi, AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models, IEEE Transactions on Knowledge and Data Engineering (TKDE), 36(6) June 2024, pp 2357 - 2371. 　 Xu Chen, Jingsen Zhang, Lei Wang, Quanyu Dai, Zhenhua Dong, Ruiming Tang, Rui Zhang, Li Chen, Xin Zhao, Ji-Rong Wen, REASONER: An Explainable Recommendation Dataset with Comprehensive Labeling Ground Truths, The 37th Annual Conference on Neural Information Processing Systems (NeurIPS) 2023. 　 Jinpeng Wang, Ziyun Zeng, Yunxiao Wang, Yuting Wang, Xingyu Lu, Tianxiang Li, Jun Yuan, Rui Zhang, Hai-Tao Zheng, Shu-Tao Xia. MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation. ACM MM Conference (MM) 2023. 　 Yunjia Xi, Weiwen Liu, Yang Wang, Ruiming Tang, Weinan Zhang, Y. Zhu, Rui Zhang, Yong Yu. On-device Integrated Re-ranking with Heterogeneous Behavior Modeling. 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023, pages 5225-5236. 　 Chang Meng, Hengyu Zhang, Wei Guo, Huifeng Guo, Haotian Liu, Yingxue Zhang, Hongkun Zheng, Ruiming Tang, Xiu Li, Rui Zhang. Hierarchical Projection Enhanced Multi-behavior Recommendation. 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2023, pages 4649-4660. 　 Yuhao Wang, Xiangyu Zhao, Bo Chen, Qidong Liu, Huifeng Guo, Huanshuo Liu, Yichao Wang, Rui Zhang, Ruiming Tang. PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2023, pages 1498-1507. 　 Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang. FINAL: Factorized Interaction Layer for CTR Prediction. The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2023, pages 2006-2010. 　 Haojie Wei, Jun Yuan, Rui Zhang, Yueguo Chen, Gang Wang. JEPOO: Highly Accurate Joint Estimation of Pitch, Onset and Offset for Music Information Retrieval. The 32nd International Joint Conference on Artificial Intelligence (IJCAI) 2023, pages 4892-4902. 　 Han Chen, Ziwen Zhao, Yuhua Li, Yixiong Zou, Ruixuan Li, Rui Zhang. CSGCL: Community-Strength-Enhanced Graph Contrastive Learning. The 32nd International Joint Conference on Artificial Intelligence (IJCAI) 2023, pages 2059-2067 　 Xiaofan Liu, Qinglin Jia, Chuhan Wu, Jingjie Li, Dai Quanyu, Lin Bo, Rui Zhang and Ruiming Tang. Task Adaptive Multi-learner Network for Joint CTR and CVR Estimation. Proceedings of the ACM Web Conference (WWW) 2023 　 Wei Guo, Chang Meng, Enming Yuan, ZhiCheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang. Compressed Interaction Graph based Framework for Multi-behavior Recommendation. Proceedings of the ACM Web Conference (WWW) 2023 Pages 960–970. 　 Jingsen Zhang, Xu Chen, Jiakai Tang, Weiqi Shao, Quanyu Dai, Zhenhua Dong, Rui Zhang. Recommendation with Causality enhanced Natural Language Explanations. Proceedings of the ACM Web Conference (WWW) 2023 Pages 876–886. 　 Bayu D. Trisedya, Jianzhong Qi, Haitao Zheng, Flora D. Salim, Rui Zhang. TransCP: A Transformer Pointer Network for Generic Entity Description Generation with Explicit Content-Planning. IEEE Transactions on Knowledge and Data Engineering (TKDE), accepted in 2023. 　 Yunxiang Zhao, Jianzhong Qi, Bayu D. Trisedya, Yixin Su, Rui Zhang, Hongguang Ren. Learning Region Similarities via Graph-based Deep Metric Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 35 (10) pp. 10237-10250, 2023. 　 Dugang Liu, Pengxiang Cheng, Zinan Lin, Xiaolian Zhang, Zhenhua Dong, Rui Zhang, Xiuqiang He, Weike Pan, Zhong Ming. Bounding System-Induced Biases in Recommender Systems with a Randomized Dataset. ACM Transactions on Information Systems (TOIS), 41(4), 1-26, 2023. 　 Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu. A Bird's-eye View of Reranking: From List Level to Page Level. The 16th ACM International Conference on Web Search and Data Mining (WSDM) 2023. Pages 1075–1083. 　 Lingyue Fu, Jianghao Lin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu. An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages. The 16th ACM International Conference on Web Search and Data Mining (WSDM) 2023. Pages 1057–1065. 　 Shiwei Li, Huifeng Guo, Lu Hou, Wei zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li. Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction. The 37th AAAI Conference on Artificial Intelligence (AAAI) 2023. 　 Rui Sun, Fengwei Zhou, Zhenhua Dong, Chuanlong Xie, Lanqing Hong, Jiawei Li, Rui Zhang, Zhen Li, Zhenguo Li. Fair-CDA: Continuous and Directional Augmentation for Group Fairness. The 37th AAAI Conference on Artificial Intelligence (AAAI) 2023. 　 Caesar Wu, Kotagiri Ramamohanarao, Rui Zhang, Pascal Bouvry. Strategic Decisions Survey, Taxonomy, and Future Directions from Artificial Intelligence Perspective. ACM Computing Surveys, 55(12), 1–30, 2023. 　 Weiwen Liu, Yunjia Xi, Jiarui Qin, Xinyi Dai, Ruiming Tang, Shuai Li, Weinan Zhang, Rui Zhang. Personalized Diversification for Neural Re-ranking in Recommendation. Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE) 2023. 　 Haopeng Li, Qiuhong Ke, Mingming Gong, Rui Zhang. Video Joint Modelling Based on Hierarchical Transformer for Co-summarization. Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 45(3), 3904 - 3917, 2023. (source code) 　 Zhicheng He, Wei Xia, Kai Dong, Huifeng Guo, Ruiming Tang, Dingyin Xia, Rui Zhang. Unsupervised Learning Style Classification for Learning Path Generation in Online Education Platforms. 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2022. 　 Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Rui Zhang, Jie Sun. A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2022. 　 Yixin Su, Yunxiang Zhao, Sarah Erfani, Junhao Gan, Rui Zhang. Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems. 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2022. (source code) 　 Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang. Neural Re-ranking in Multi-stage Recommender Systems: A Review. The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI) 2022. (source code) 　 Lin (Yuanbo) Wu, Deyin Liu, Xiaojie Guo, Richang Hong, Liangchen Liu, Rui Zhang. Multi-scale Spatial Representation Learning via Recursive Hermite Polynomial Networks. The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI) 2022. 　 Jieming Zhu, Quanyu Dai, LiangCai Su, Rong Ma, Jinyang Liu, Guohao Cai, Xi Xiao, Rui Zhang. BARS: Towards Open Benchmarking for Recommender Systems. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2022. (source code and datasets) 　 Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu. Multi-Level Interaction Reranking with User Behavior History. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2022. 　 Jiarui Qin, Jiachen Zhu, Bo Chen, Zhirong Liu, Weiwen Liu, Ruiming Tang, Rui Zhang, Yong Yu, Weinan Zhang. RankFlow: Joint Optimization of Multi-Stage Cascade Ranking Systems as Flows. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2022. 　 Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang. ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2022. 　 Rui Zhang, Bayu D. Trisedya, Miao Li, Yong Jiang, and Jianzhong Qi. A Benchmark and Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learning. VLDB Journal, 31 (5), 1143–1168, 2022. (source code) 　 Shiquan Yang, Rui Zhang, Sarah Erfani, Jey Han Lau. An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation. 59th Annual Meeting of the Association for Computational Linguistics (ACL) 2022. 　 Dong Yao, Zhou Zhao, Shengyu Zhang, Jieming Zhu, Yudong Zhu, Rui Zhang, Xiuqiang He. Contrastive Learning with Positive-Negative Frame Mask for Music Representation. The Web Conference (WWW), 2022, Pages 2906–2915. 　 Fuyuan Lyu, Xing Tang, Huifeng Guo, Ruiming Tang, Xiuqiang He, Rui Zhang, Xue Liu. Memorize, Factorize, or be Naïve: Learning Optimal Feature Interaction Methods for CTR Prediction.  Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE) 2022. 　 Wei Guo, Can Zhang, Zhicheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang. MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction. Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE) 2022. 　 Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He. Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms. The 36th AAAI Conference on Artificial Intelligence (AAAI) 2022. 　 Bayu D. Trisedya, Jianzhong Qi, Wei Wang, and Rui Zhang. GCP: Graph Encoder with Content-Planning for Sentence Generation from Knowledge Base. Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 44(11), 7521 - 7533, 2022. 　 Yu Gu, Kaiqiang Yu, Zhen Song, Jianzhong Qi, Zhigang Wang, Ge Yu, and Rui Zhang. Distributed Hypergraph Processing Using Intersection Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(7), 3182 - 3195, 2022. 　 Yang Song, Yu Gu, Rui Zhang and Ge Yu. BrePartition: Optimized High-Dimensional kNN Search with Bregman Distances. IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(3), 1053 - 1065, 2022. 　 Shiquan Yang, Rui Zhang, Sarah M. Erfani, Jey Han Lau. UniMF: A Unified Framework to Incorporate Multimodal Knowledge Bases into End-to-End Task-Oriented Dialogue Systems. International Joint Conference on Artificial Intelligence (IJCAI) 2021. 　 Yixin Su, Rui Zhang, Sarah M. Erfani, Junhao Gan. Neural Graph Matching based Collaborative Filtering.  The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2021  Code and Data 　 Yixin Su, Rui Zhang, Sarah Erfani, Zhenghua Xu, Detecting Beneficial Feature Interactions for Recommender Systems. The 35th AAAI Conference on Artificial Intelligence (AAAI) 2021.  Code and Data 　 Yunxiang Zhao, Jianzhong Qi, Qingwei Liu, Rui Zhang. WGCN: Graph Convolutional Networks with Weighted Structural Features. The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 2021  Code and Data 　 Xiaojie Wang, Rui Zhang, Yu Sun, Jianzhong Qi, Combating Selection Biases in Recommender Systems with A Few Unbiased Ratings. The 13th ACM International Conference on Web Search and Data Mining (WSDM) 2021. 　 Xiaojie Wang, Rui Zhang, Yu Sun, Jianzhong Qi. Adversarial Distillation for Learning with Privileged Provisions. Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 43(3), 786-797, 2021. 　 Ning Ding, Xiaobin Wang, Yao Fu, Guangwei Xu, Rui Wang, Pengjun Xie, Ying Shen, Fei Huang, Hai-Tao Zheng, Rui Zhang, Prototypical Representation Learning for Relation Extraction. The Ninth International Conference on Learning Representations (ICLR) 2021. 　  Yimeng Dai, Rui Zhang, Jianzhong Qi, Automatic Webpage Briefing. Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE) 2021. 　  Hao Wu, Junhao Gan, Zhewei Wei, Rui Zhang, Unifying the Global and Local Approaches: An Efficient Power Iteration with Forward Push. Proceedings of ACM Conference on Management of Data (SIGMOD) 2021. 　 Ang Li, Qiuhong Ke, Xingjun Ma, Haiqin Weng, Zhiyuan Zong, Feng Xue, Rui Zhang. Noise Doesn’t Lie: Towards Universal Detection of Deep Inpainting. International Joint Conference on Artificial Intelligence (IJCAI) 2021. 　 Yang Song, Yu Gu, Rui Zhang, Ge Yu, ProMIPS: Efficient High-Dimensional c-Approximate Maximum Inner Product Search with a Lightweight Index. Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE) 2021. 　 Yaoshu Wang, Chuan Xiao, Jianbin Qin, Rui Mao, Onizuka Makoto, Wei Wang, Rui Zhang, Consistent and Flexible Selectivity Estimation for High-Dimensional Data. Proceedings of ACM Conference on Management of Data (SIGMOD) 2021.

Selected Professional Activities        Full list 2027: Senior PC member for ICDE, CIKM 2026: Senior Program Committee (SPC) Member for IJCAI-ECAI 2026 2026: Aera Chair for AAAI Conference 2026 2025: Competition Chair for ACM Web Conference 2025 2022: Senior Program Committee (SPC) Member for ACM International Conference on Information and Knowledge Management (CIKM) 2022. 2021: Publicity Chair for ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL) 2021 2020: PC member of ICDE, PVLDB, Web Conference (WWW), Associate Editor of World Wide Web Journal 2019: PC member of ICDE, PVLDB, Web Conference (WWW), AAAI, DASFAA 2018: PC member of ICDE, General Chair of ADC, CIKM Senior PC 2017: CIKM Senior PC 2016: Associate Editor of Distributed and Parallel Databases, PC member of MDM, IEEE BigDataSE 2015: CIKM Local Co-Chair, PC member of SIGMOD, General Chair of ADC 2015 (co-located with SIGMOD). 2014: ICDE Industry Track PC member, SIGMOD Exhibits Co-Chair. 2013: Program Committee Co-Chair for Australasian Database Conference 2013; Demo Co-Chair of ICDE; PC member of SIGMOD, ICDE; Publication Co-Chair of ApWeb; WISE Demo Chair. 2012: Program Committee Co-Chair for Australasian Database Conference 2012, PC member of ICDE, VLDB, Vice Chair of ACM SIGSPATIAL Australia Chapter. 2011: PC member of ICDE, DASFAA 2010: Review board of Proceedings of the VLDB Endowment; PC member of KDD, CIKM, DASFAA 2009: Review board of Proceedings of the VLDB Endowment; PC member of ICDE, DASFAA 2008: Review board of Proceedings of the VLDB Endowment; DASFAA 2007: PC member of SIGMOD, DASFAA Reviewer for VLDB Journal, ACM Trans. on Database Systems, IEEE Trans. on Knowledge and Data Engineering, IEEE Trans. on Computers, Information Systems

Released Code and Datasets iDistance: State-of-the-Art for k Nearest Neighbor queries in metric spaces   [Wikipedia Entry of iDistance] GiMP: A framework for Mapping-based multi-dimensional indexing P+-tree: State-of-the-Art for high-dimensional window queries V*-Diagram and INS: State-of-the-Art for moving k nearest neighbor queries. HomePub: Publication Strings from Academic Homepages

Patent US patent: with Divesh Srivastava and Nick Koudas. System and method for managing data streams, US patent number 7,631,074,  Issuing date: Dec 8, 2009

Research Students I have Worked with

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