YONGJOO PARK

Assistant Professor, Illinois CS (UIUC)
yongjoo@g.illinois.edu

Co-founder / Chief Scientist, Keebo
yongjoo@keebo.ai

[CV]    [Publication]    [CreateLab]    [orcid]

Research   I'm interested in big data systems. Specifically, I am investigating how we should build systems and frameworks that can offer more interactive, adaptive, and scalable data management in modern computing environments.

At IllinoisCS, I am a member of DAIS. You can join DAIS Slack Workspace

News (Jun 2024)   Billy presents the "ElasticNotebook" demo at SIGMOD'24. Billy will also present the research paper at VLDB'24.

News (May 2024)   The DeepOLA team receives SIGMOD'23 Best Artifact Award Honorable Mention!

News (Sep 2023)   "ElasticNotebook" is accepted to PVLDB'23 (or VLDB'24). Congrats Billy!

News (June 2023)   Awarded $1.2M NSF grant with Hari for "system + causal inference"!

  • TEACHING

    FA 2024. CS 511 - Advanced Data Management     [Course Info]   [Canvas]  

    SP 2024. CS 598 YP - ML and Data Systems     [Course Info]   [Canvas]  

    FA 2023. CS 511 - Advanced Data Management     [Course Info]   [Canvas]  

    FA 2022. CS 511 - Advanced Data Management     [Course Info]   [Canvas]

    FA 2021. CS 411 - Database Systems     [Course Info]

    SP 2021. CS 511 - Advanced Data Management     [Course Info]

  • PROJECTS

    Currently, my primary research focus is to develop innovative Systems for Data Science.

    • CARE (CAusal-RElational data system) aims to develop a system for end-to-end causal inference with an emphasis on efficiency and ease of use. Causal inference is a principled approach to understanding why.
    • Kishu aims to bring durability, atomicity, replicability, and time versoning to Jupyter-like interactive data science systems. This project will address fundamental limitations that make those systems brittle.
      [Transactional Python, DEEM@SIGMOD’23]
      [ElasticNotebook, VLDB’24]
    • DeepOLA aims to offer progressive analytics (or Online Aggregation) to continuous data exploration frequently observed with Pandas-like libraries.   [SIGMOD’23]

    I am also investigating how data systems (such as key-value stores) should look like for emerging ad-hoc workloads.

    • AirDB aims to allow transactions directly on storage layer (without servers).
    • AirIndex optimizes the structures of indexes automatically, considering system performance like latency, bandwidth, etc.   [SIGMOD’24]

  • ADVISING

    I am fortunate to work with these smart and motivated students.

    1. Supawit Chockchowwat (PhD student, from 2020)
    2. Billy Li (PhD student, from 2021)
    3. Dohyun Park (PhD student, from 2023)
    4. Xinying Zheng (PhD student, from 2023, with Indy Gupta)
    5. Haocheng Xia (PhD student, from 2024)
    6. Hanxi Fang (MS student, from 2023)
    7. Raunak Shah (MS student, from 2023)
    8. Shunning Zhang (MS student, from 2023)
    9. Arthur Huang (MS student, from 2023)
    10. Talika Gupta (MS student, from 2024)
    11. Hanjun Goo (PhD student @SNU, in collaboration with Kyuseok Shim)

    You can also find undergraduate student and past members on this research group website.

    Prospective PhD Students: Every year, I recruit one or two new PhD students. If you are interested in working with me, please indicate in your application or send me an email (to my Illinois address).

    These are some helpful articles I wrote:

    1. TOEFL score requirements for CS@UIUC
    2. Information about Illinois’ PhD admission process (2020)

    UIUC Undergrads: Every semester, I plan to advise a few students (and more during summer). If you are interested, please send me an email.

    Prospective Master’s Students: In general, I prioritize supporting PhD students. However, I may support a few exceptional MS students with RA. (Almost all) MS students are supported with TA by the department.