YONGJOO PARK
Assistant Professor, Illinois CS (UIUC)
yongjoo@g.illinois.edu
Co-founder / Chief Scientist,
Keebo
yongjoo@keebo.ai
Current Research: Systems for data-intensive AI
- Efficient Retrieval-Augmented Generation (RAG)
- Systems for exploratory AI
At IllinoisCS, I am a member of DAIS. You can join DAIS Slack Workspace
🎉 News (May 2025) Supawit will join CMKL University in Thailand as an Assistant Professor in 2026!
🎉 News (Apr 2025) Supawit successfully defended his PhD (A few photos). Supawit will continue his academic career as a Postdoc at Google.
🎉 News (Mar 2025) Selected for a new IBM-Illinois project on VectorDB/RAG.
🎉 News (Mar 2025) Universal SmartSSD filtering accepted to ISCA'25.
🎉 News (Feb 2025) HCI evaluation with AI-agents was accepted to CHI'25 late-breaking work.
🎉 News (Feb 2025) Kishu, the World's First Undoable Jupyter, will be presented in PyCon'25.
🎉 News (Jan 2025) Interface for data science versioning was accepted to CHI'25.
🎉 News (Dec 2024) Kishu, the Time-traveling Notebook was accepted to PVLDB'25.
🎉 News (Jun 2024) ElasticNotebook demo was presented at SIGMOD'24.
🎉 News (May 2024) DeepOLA received SIGMOD'23 Best Artifact Award Honorable Mention!
🎉 News (Sep 2023) ElasticNotebook was accepted to PVLDB'23 (or VLDB'24). Congrats Billy!
🎉 News (June 2023) Awarded $1.2M NSF grant with Hari for "system + causal inference"!
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TEACHING
SP2025 CS598YP - Hot Topics in Data Management [Course Info] [Canvas]
FA2024 CS511 - Advanced Data Management [Course Info] [Canvas]
SP2024 CS598 YP - ML and Data Systems [Course Info] [Canvas]
FA2023 CS511 - Advanced Data Management [Course Info] [Canvas]
FA2022 CS511 - Advanced Data Management [Course Info] [Canvas]
FA2021 CS411 - Database Systems [Course Info]
SP2021 CS511 - Advanced Data Management [Course Info]
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RESEARCH
I build systems for data-intensive AI. I also study a few core database topics.
Kishu: Managing Exploratory AI
Kishu achieves World’s First Undoable Jupyter with reliable/efficient checkpointing
✏️ Publications: [DEEM’23] [VLDB’24] [SIGMOD’24 demo] [VLDB’25] [CHI’25] [CHI’25 short] [SIGMOD’25 demo]
🚀 Kishu is now open-sourced on GitHub
Kishuboard: offers Git-like versioning in the code+data space.
CARE: Efficient Reasoning with (Un)structured Data
The CARE (CAusal-RElational data system) project develops a scalable system for reasoning with structured and unstructured data with end-to-end optimization:
- LLM/RAG inference
- Vector Database
- In-Storage Computing: [ISCA'25]
Core database topics
- 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]
- DeepOLA aims to offer progressive analytics (or Online Aggregation) to continuous data exploration frequently observed with Pandas-like libraries. [SIGMOD’23]
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ADVISING
These are amazing students I am working with.
PhD Students:
- Supawit Chockchowwat (2020-25 -> Postdoc@Google, 2025-26 -> Asst. Prof at CMKL in Thailand, 2026)
- Billy Li (2021-Present)
- Dohyun Park (2023-Present)
- Xinying Zheng (2023-Present, with Indy Gupta)
- Haocheng Xia (2024-Present)
- Hanjun Goo (@SNU, in collaboration with Kyuseok Shim)
MS Students:
- Hanxi Fang (2023-Present -> Amazon)
- Raunak Shah (2023-Present -> Meta)
- Shunning Zhang (2023-Present -> Meta)
- Arthur Huang (2023-Present)
- Talika Gupta (2024-Present)
Graduated:
- Nikhil Sheoran (MS 2022-23 -> Databricks)
For undergraduates, see 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:
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.