Rong ZHU Homepage

Rong ZHU 朱 鎔
red.zr@alibaba-inc.com

I am a research scientist in Institute for Intelligent Computing, Alibaba Group. I also serve as an adjunct industry mentor for the master of data science program in Chinese University of Hong Kong (Shen Zhen). I received my Ph.D. and B.S. degree from Harbin Institute of Technology in 2019 and 2013, respectively, supervised by Professor Jianzhong Li and Professor Zhaonian Zou. My research interests lies in the intersection of databases, machine learning and systems. At now stage, I focus on intelligent databases (AI4DB) algorithms and systems.

Selected Awards

Selected Publications

  • Tutorials, Surveys and Invited Papers

    Bolin Ding, Rong Zhu, Jingren Zhou. Learned query optimizers. In Foundations and Trends in Databases, 2024. (Invited Survey Paper)


    Rong Zhu, Lianggui Weng, Bolin Ding, Jingren Zhou. Learned query optimizer: what is new and what is next. In SIGMOD, 2024. (Tutorial)


    Rong Zhu, Ziniu Wu, Chengliang Chai, Andreas Pfadler, Bolin Ding, Guoliang Li, Jingren Zhou. Learned query optimizer: at the forefront of AI-driven databases. In EDBT, 2022. (Tutorial)


    Yaliang Li, Zhen Wang, Yuexiang Xie, Bolin Ding, Kai Zeng, Ce Zhang, Rong Zhu. AutoML: from methodology to application. In CIKM, 2021. (Tutorial)


  • AI4DB and Databases

    Rong Zhu, Lianggui Weng#, Wenqing Wei, Di Wu, Jiazhen Peng, Yifan Wang, Bolin Ding*, Defu Lian*, Bolong Zheng*, Jingren Zhou*. PilotScope: steering databases with machine learning drivers. In PVLDB, 2024. (Open Source Project)


    Lianggui Weng#, Rong Zhu#,*, Di Wu, Bolin Ding*, Bolong Zheng*, Jingren Zhou*. Eraser: eliminating performance regression on learned query optimizer. In PVLDB, 2024. (Github Repository)


    Pengfei Li, Wenqing Wei, Rong Zhu*, Bolin Ding*, Jingren Zhou*, Hua Lu*. ALECE: an Attention-based learned cardinality estimator for SPJ queries on dynamic workloads. In PVLDB, 2024. (Github Repository)


    Pengfei Li, Hua Lu, Rong Zhu*, Bolin Ding, Long Yang, Gang Pan. DILI: a distribution-driven learned index. In PVLDB, 2023. (Github Repository)


    Rong Zhu#, Wei Chen#, Bolin Ding, Xingguang Chen, Andreas Pfadler, Ziniu Wu, Jingren Zhou*. Lero: a learning-to-rank query optimizer. In PVLDB, 2023. (Github Repository)


    Yuxing Han, Ziniu Wu, Peizhi Wu, Rong Zhu*, Jingyi Yang, Liang Wei Tan, Kai Zeng, Gao Cong, Yanzhao Qin, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Jiangneng Li, Bin Cui. Cardinality estimation in DBMS: a comprehensive benchmark evaluation. In PVLDB, 2022. (Github Repository)


    Ziniu Wu, Peilun Yang#, Pei Yu#, Rong Zhu*, Yuxing Han, Yaliang Li, Defu Lian, Kai Zeng, Jingren Zhou. A unified transferable model for ML-enhanced DBMS. In CIDR, 2022. (Github Repository)


    Zizhong Meng, Peizhi Wu, Gao Cong, Rong Zhu, Shuai Ma. Unsupervised selectivity estimation by integrating gaussian mixture models and autoregressive model. In EDBT, 2022.


    Rong Zhu#, Ziniu Wu#, Yuxing Han, Kai Zeng, Andreas Pfadler, Zhengping Qian, Jingren Zhou, Bin Cui. FLAT: fast, lightweight and accurate method for cardinality estimation. In PVLDB, 2021. (Github Repository)


    Chen Ye, Hongzhi Wang, Kangjie Zheng, Youkang Kong, Rong Zhu, Jing Gao, Jianzhong Li. Constrained truth discovery. In IEEE TKDE, 2020.


  • Machine Learning

    Rong Zhu#, Andreas Pfadler#, Ziniu Wu*, Yuxing Han, Xiaoke Yang, Feng Ye, Zhenping Qian, Jingren Zhou, Bin Cui. Efficient and scalable structure learning for Bayesian networks: algorithms and applications. In ICDE, 2021.


    Rong Zhu*,, Sheng Yang, Andreas Pfadler, Zhengping Qian, Jingren Zhou. Learning efficient parameter server synchronization policies for distributed SGD. In ICLR, 2021.


  • Graph Processing Systems

    Wenfei Fan, Longbin Lai, Xue Li, Yong Li, Zhao Li, Zhengping Qian, Chao Tian, Lei Wang, Jingbo Xu, Youyang Yao, Qiang Yin, Wenyuan Yu, Kai Zeng, Kun Zhao, Jingren Zhou, Diwen Zhu, Rong Zhu. GraphScope: a unified engine for big graph processing. In PVLDB, 2021. (Alphabetic Order, Github Repository)


    Rong Zhu, Kun Zhao, Hongxia Yang*, Wei Lin, Chang Zhou, Baole Ai, Yong Li, Jingren Zhou. AliGraph: a comprehensive graph neural network platform. In PVLDB, 2019. (Github Repository)


  • Graph Data Mining

    Rong Zhu, Zhaonian Zou*, Jianzhong Li. Fast diversified coherent core search on multi-layer graphs. In VLDB Journal, 2019.


    Rong Zhu, Zhaonian Zou*, Jianzhong Li. Diversified coherent core search on multi-layer graphs. In ICDE, 2018.


    Rong Zhu, Zhaonian Zou*, Jianzhong Li. Fast rectangle counting on massive networks. In ICDM, 2018.


    Rong Zhu, Zhaonian Zou*, Jianzhong Li. SimRank on uncertain graphs. In IEEE TKDE, 2017.


    Rong Zhu, Zhaonian Zou*, Jianzhong Li. Towards efficient top-k reliability search on uncertain graphs. In KAIS, 2017.


    Zhaonian Zou*, Rong Zhu. Truss decomposition of uncertain graphs. In KAIS, 2017.


    Rong Zhu, Zhaonian Zou*, Jianzhong Li. SimRank computation on uncertain graphs. In ICDE, 2016.


    Rong Zhu, Zhaonian Zou, Jianzhong Li. Top-k reliability search on uncertain graphs. In ICDM, 2016. (Best Paper Candidate)


Research/Enigneering Projects

  • PilotScope: Middleware for Deploying AI Drivers in Databases

  • STATE-CEB: Comprehensive Benchmark for Cardinality Estimation

  • LEAST: Large-Scale Bayesian Network Structure Learning (Applied in 30+ business in Alibaba)

  • GraphScope: One-stop Large-Scale Graph Computing System (Certificate by China Association for Science and Technology)

Patents

  • CN114138798B

  • CN114328614B

  • CN114116757B

  • CN116108072B

  • CN116541418B

Services