I am Hu Zirui 胡梓锐 (2001.02), received my B.Eng. degree (2018 - 2022) from Software Engineering College and Department of Chinese Language and Literature of East China Normal University in 2022. I am a Third-Year PhD advised by Prof. Rong Zhang and co-advised by Prof. Xuan Zhou, Research Prof. ChengCheng Yang, and Prof. Peng Cai and at School of Data Science and Engineering of East China Normal University (2022.09 - 2027.06).

My research focuses on database kernel technology, especially for OLAP query optimization, AI4DB, and database system testing.

I maintain curated paper lists for OLAP , AI4DB and cutting-edge industry practices from leading tech giants such as Google, Amazon, Alibaba, and Huawei. These resources aim to keep researchers and practitioners up to date with the latest advancements in these fields.

I love badminton🏸, basketball🏀, calligraphy🖊, and singing🎤 in my spare time.

📝 Publications

All papers are listed in descending order by year (# indicates co-first authors).

• [ICDE’25] Artemis: A Customizable Workload Generation Toolkit for Benchmarking Cardinality Estimation. Zirui Hu, Rong Zhang, Chengcheng Yang, Xuan Zhou, Quanqing Xu, Chuanhui Yang (Computer Science, CCF-A Conference, Theme: Cardinality Estimation, Benchmark), PDF.
• [SIGMOD’25] A Query-Aware Enormous Database Generator For System Performance Evaluation. Xuhua Huang, Zirui Hu, Siyang Weng, Rong Zhang, Chengcheng Yang, Xuan Zhou, Weining Qian, Chuanhui Yang, Quanqing Xu (Computer Science, CCF-A, Theme: Synthetic Data Generation), PDF.
• [ICDE’25] Rabbit: Retrieval-Augmented Generation Enables Better Automatic Database Knob Tuning. Wenwen Sun#, Zhicheng Pan#, Zirui Hu, Yu Liu, Chengcheng Yang, Rong Zhang, Xuan Zhou(Computer Science, CCF-A Conference, Theme: AI4DB, Database Tuning), PDF.
• [ICDE’24] Mirage: Generating Enormous Databases for Complex Workloads. Qingshuai Wang, Hao Li, Zirui Hu, Rong Zhang, Chengcheng Yang, Peng Cai, Xuan Zhou, and Aoying Zhou (Computer Science, CCF-A Conference, Theme: Synthetic Data Generation), PDF. .
• [DASFAA’24] Touchstone+ : Query Aware Database Generation for Match Operators. Hao Li, Qingshuai Wang, Zirui Hu, Xuhua Huang, Lv Ni, Rong Zhang, Xuan Zhou (Computer Science, CCF-B Conference, Theme: Synthetic Data Generation), PDF.
• [Digital Economy and Sustainble Development’24] Determinants of Successful Mergers and Acquisitions in China: Evidence from Machine Learning. Shengdi Zhou, Faqin Lan, Zirui Hu, Yongting Liu (Economics, Journal, Theme: AI4Finace), PDF.
• [Journal of Software’24] The Benchmarking Ability of HTAP Benchmarks. Siyang Weng, Rong Yu, Qingshuai Wang, Zirui Hu, Lv Ni, Rong Zhang, Xuan Zhou, Aoying Zhou, Quanqing Xu, Chuanhui Yang, Wei Liu, Panfei Yang (Computer Science, CCF T1-Journal, Theme: HTAP Benchmark), PDF.
• [Journal of Software’23] Data Sharing Model and Optimization Strategies in HTAP Database Systems. Zirui Hu, Siyang Weng, Qingshuai Wang, Rong Yu, Jinkai Xu, Rong Zhang, Xuan Zhou (Computer Science, CCF T1-Journal, Theme: HTAP System), PDF.
• WAITING FOR MORE …
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📑 Interesting Paper Sharing

1. Retrofitting High Availability Mechanism to Tame Hybrid Transaction/Analytical Processing. 2021 OSDI, Theme: HTAP System, PDF, PPT.
2. Are We Ready For Learned Cardinality Estimation? 2021 VLDB, Theme: AI4Cardinality Estimation, PDF, PPT.
3. Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction. 2022 VLDB, Theme: AI4Cost Model, PDF, PPT.
4. Diva: Making MVCC Systems HTAP-Friendly. 2022 SIGMOD, Theme: HTAP & MVCC, PDF, PPT.
5. Lero: A Learning-to-Rank Query Optimizer. 2023 VLDB, Theme: AI4Query Optimizer, PDF, PPT.
6. Detecting Logic Bugs of Join Optimizations in DBMS. 2023 SIGMOD, Theme: Functional Bug Detection, PDF, PPT.
7. Detecting Metadata-Related Logic Bugs in Database Systems via Raw Database Construction. 2024 VLDB, Theme: Functional Bug Detection, PDF, PPT.
8. PUPPY: Finding Performance Degradation Bugs in DBMSs via Limited-Optimization Plan Construction. 2025 ICSE, Theme: Performance Bug Detection, PDF, PPT.
9. Constant Optimization Driven Database System Testing. 2025 SIGMOD, Theme: Functional Bug Detection, PDF, PPT.

Please note, these PowerPoints are intended solely for personal learning purposes. All papers discussed here are authored by others, not by us. If you have any detailed questions or would like to explore the research further, please refer to the original authors of the respective papers. If there are any errors or omissions, your understanding is appreciated! More papers can be found in this repo .

🪐 Kind Visitors