I am an Associate Professor of Computer Science at Renmin University of China. My research interest is in high-performance data systems for AI and big data analytics, particularly in cloud-native databases/data lakehouses, AI-native storage systems, and hardware-aware data processing. Before joining RUC as a faculty member, I worked at EPFL DIAS Lab as a Postdoctoral Researcher and at Tencent as a Senior Database Kernel Engineer.

I am actively looking for motivated students to work on Big Data Systems and Data for AI. 欢迎对AI系统和大数据系统感兴趣的优秀同学来研究组实习，欢迎有意攻读硕士、博士研究生的同学和我联系。 Feel free to email me.

Research

My research focuses on building efficient data systems that bridge the gap between real-world demands and system capabilities. Key areas include:

  • Cloud-native Data Lakes — disaggregated storage and compute architectures, serverless query processing, and cost-efficient elastic analytics.
  • AI-native (multimodal) Data Systems — novel storage systems designed for AI workloads, enabling efficient data access for machine learning and analytics.
  • Hardware-aware data processing — data systems optimized for modern hardware including new storage devices, accelerators, and heterogeneous architectures.
  • Automated Database Diagnosis and Optimization — fine-grained, non-intrusive performance diagnosis and tuning for database systems.

Open Source

Pixels — An efficient storage and compute engine for both on-prem and cloud-native data analytics. Pixels features an optimized columnar storage format, serverless query acceleration using cloud functions, natural-language-aided data analytics, and flexible pricing with service-level guarantees. Key columnar storage techniques from Pixels are incorporated into China's National Standard (GB/T 41818-2022) on analytical data storage. Query execution technologies have been adopted by major cloud vendors for database product prototyping.

Experience

  • Associate Professor, School of Information, Renmin University of China, 2025 – Present
  • Assistant Professor, School of Information, Renmin University of China, 2023 – 2025
  • Postdoctoral Researcher, DIAS Lab, EPFL, 2020 – 2023
  • Senior Database Kernel Engineer, TDSQL, Tencent, 2018 – 2020
  • Ph.D. in Computer Science, Renmin University of China, 2012 – 2018
  • Visiting Ph.D. Student, The Ohio State University, 2015 – 2016
  • Research Intern, Systems & Algorithms Group, Microsoft Research Asia, 2014 – 2015

Students

PhD Students: Dongyang Geng (耿东杨), Haozhe Wang (王浩哲), Yunda Guo (郭云达)

Master‘s Students: Haoyue Li (李皓月), Zinuo Li (李子诺), Qi Lei (雷琪), Zhengjin Wang (王正今), Shijie Yan (闫世杰), Boyan Sun (孙博言)

Undergraduate Students: Haoting Yan (严浩庭)

Student Competition Achievements:

  • Runner-up (2024 & 2025) in the National College Student Computer System Capability Competition — PolarDB Track
  • Third Prize (2025) in the National College Student Computer System Capability Competition - Database Kernel Track
  • 2024 Beijing Outstanding Undergraduate Thesis (全校理工学科仅4人)

Teaching

  • Introduction to Computer System II (ICS2) — Spring, 2024 and later
  • Practical Database Development — Fall, 2024–2026
  • Open Source Software Practice — Fall, 2026

Publications

Awards

  • China Patent Gold Award (24th, First Inventor) — the first Gold Award in the database field. Patent on database transaction processing, applied in Tencent TDSQL.
  • National & Beijing Overseas Talent Programs — selected for national-level and Beijing municipal-level overseas talent recruitment programs.
  • Outstanding Advisor & Special Contribution Award — 2024–2025 National Computer System Capability Competition for College Students.
  • Beijing Outstanding Undergraduate Thesis Advisor, 2024.