Jianguo Wang

Assistant Professor

Department of Computer Science
Purdue University
West Lafayette, Indiana

Email: csjgwang@purdue.edu
Office: LWSN 2142B
Phone: (765) 496-0726




Biography

Jianguo Wang is currently a Tenure-Track Assistant Professor in the Department of Computer Science at Purdue University.

Prior to joining Purdue, he worked at Zilliz on Milvus, a purpose-built vector database system. Before that, he worked at Amazon Web Services (AWS) on Amazon Aurora, a cloud-native database system. He also interned at Microsoft Research, Oracle, and Samsung on various database systems.

He obtained his PhD degree in Computer Science from the University of California, San Diego, his MPhil degree from The Hong Kong Polytechnic University, and his Bachelor's degree from Zhengzhou University, China.


Research Interests

Currently, I'm leading a team of students working on Database Systems for the Cloud and Large Language Models, including Disaggregated Databases and Vector Databases.

  • Disaggregated Database Systems (for the Cloud)
  • Vector Database Systems (for Large Language Models)
    • Supporting Vector Data Management inside Relational Databases
    • Multi-Model Vector Databases (Vector + "X") for Advanced RAGs
    • Cost-Efficient Vector Databases
    • Auto Tuning in Vector Databases
    • Beyond Vector Databases: RAGs and Multi-Model Databases
    • [Papers: CIDR'26, SIGMOD'26d, SIGMOD'25, VLDB'24a, VLDB'24b, SIGMOD'24c, SIGMOD'24d, ICDE'24, VLDBJ'24b, SIGMOD'21, ICDT'19]
    • [Major Open-source: We built PostgreSQL-V, an integrated vector database system within PostgreSQL. It achieves performance comparable to specialized vector databases and is much faster than pgvector. Check out our CIDR'26 paper for more details. This is towards our broader vision of building scalable data infrastructure for AI.]


Working Experience


Recent Publications

  • Jiayi Liu, Yunan Zhang, Chenzhe Jin, Aditya Gupta, Shige Liu, Jianguo Wang.
    Fast Vector Search in PostgreSQL: A Decoupled Approach.
    Conference on Innovative Data Systems Research (CIDR), pages 2:1-8, 2026.

  • Chenzhe Jin, Yunan Zhang, Jiayi Liu, Jianguo Wang.
    Efficient Vector Index Merging in Vector Databases.
    Proceedings of ACM Conference on Management of Data (SIGMOD), pages 31:1-26, 2026.

  • Xi Pang, Jianguo Wang.
    Reducing Tail Latency in Storage-Disaggregated Database Systems.
    Proceedings of ACM Conference on Management of Data (SIGMOD), pages 74:1-26, 2026.

    • More publications...


    Team

    Current
    Alumni
    • Bowen Zhang (Visiting PhD from SJTU, June 2026, First Employment: Postdoc at Peking University
      • PhD Dissertation: Distributed Heterogeneous Memory Systems for Disaggregated Architectures
    • Xi Pang (PhD, May 2026, First Employment: Databricks)
      • PhD Dissertation: Cloud-Native Database Systems: Disaggregation and Multi-Tenancy
    • Ruihong Wang (PhD, Feb 2026, First Employment: Google), co-advised with Walid G. Aref
      • PhD Dissertation: Disaggregated In-Memory Database Systems
    • Chuqing Gao (MS, Dec 2025, First Employment: Pinterest)


    Hiring

    I'm always looking for highly motivated students in database systems (hiring info). Please feel free to contact me if you're interested.



    Teaching

    • CS592 (Seminar): Databases for AI: Vector Databases
      • Spring 2026
    • CS592 (Seminar): Disaggregated Database Systems
      • Spring 2023
    • CS590 (Seminar): Cloud-native Database Systems
      • Spring 2021
    • CS440: Large-scale Data Analytics
      • Fall 2025, Fall 2024, Fall 2023, Fall 2022, Fall 2021
    • CS448: Introduction to Database Systems
      • Spring 2022
    • CS541: Graduate Database Systems
      • Spring 2026


    Honors and Awards


    Services

    Professional Services

    University Services