Yongjoo Park

For More Information

• Yongjoo's personal website

Education

• Ph.D. in Computer Science and Engineering, University of Michigan, Ann Arbor, 2017
• M.S. in Computer Science, University of Michigan, Ann Arbor, 2013
• B.S. in Electrical Engineering, Seoul National University, 2009

Biography

Yongjoo Park is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. At UIUC, he is part of Data and Information Systems (DAIS) Research Lab. Also, Yongjoo is a co-founder and Chief Scientist of Keebo, Inc., a start-up company he co-founded based on his Ph.D. research. Yongjoo's research interest is in building intelligent data-intensive systems using statistical and Artificial Intelligence techniques. Yongjoo obtained a Ph.D. in Computer Science and Engineering from the University of Michigan, Ann Arbor in 2017. His dissertation received the 2018 SIGMOD Jim Gray Dissertation runner-up award.

Academic Positions

• Assistant Professor, Department of Computer Science, University of Illinois at Urbana–Champaign, Jan. 2021 - Present

Other Professional Employment

• Chief Scientist, Keebo, Inc., Sep. 2022 - Present
• Co-founder and CTO, Keebo, Inc., Aug. 2019 - Aug. 2022

Research Interests

• Systems for analytics and machine learning
• A.I. Data-intensive Systems

Articles in Conference Proceedings

• Zhaoheng Li, Xinyu Pi, Yongjoo Park. S/C: Speeding Up Data Materialization with Bounded Memory. ICDE 2023 (research): 39th International Conference on Data Engineering, Anaheim, CA, USA, 2023.
• Nikhil Sheoran, Supawit Chockchowwat, Arav Chheda, Suwen Wang, Riya Verma, Yongjoo Park. A Step Toward Deep Online Aggregation. SIGMOD 2023 (research): ACM SIGMOD/PODS International Conference on Management of Data, Seattle, WA, USA, 2023.
• Supawit Chockchowwat, Wenjie Liu, Yongjoo Park. Automatically Finding Optimal Index Structure. AIDB Workshop at VLDB 2022 (research): 4th International Workshop on Applied AI for Database Systems and Applications, Sydney, Australia, 2022.
• Sophia Yang, Yongjoo Park, and Abdussalam Alawini. The Effects of Teaching Modality on Collaborative Learning: A Controlled Study. FIE 2022 (research): The Frontiers in Education, Uppsala, Sweden, 2022.
• Supawit Chockchowwat, Chaitanya Sood, Yongjoo Park. Airphant: Cloud-oriented Document Indexing. ICDE 2022 (research): 38th International Conference on Data Engineering, Kuala Lumpur, Malaysia, 2022.
• Johes Bater, Yongjoo Park, Xi He, Xiao Wang, Jennie Rogers. SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations. PVLDB 2020 (research): 46th International Conference on Very Large Data Bases. Tokyo, Japan (Online due to COVID-19), 2020.
• Yongjoo Park, Shucheng Zhang, Barzan Mozafari. QuickSel: Quick Selectivity Learning with Mixture Models. SIGMOD’20 (research): ACM SIGMOD/PODS International Conference on Management of Data. Portland, OR, USA, 2020.
• Yongjoo Park, Jingyi Qing, Xiaoyang Shen, Barzan Mozafari. BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees. SIGMOD’19 (research): ACM SIGMOD/PODS International Conference on Management of Data. Amsterdam, The Netherlands, 2019.
• Yongjoo Park, Barzan Mozafari, Joseph Sorenson, Junhao Wang. VerdictDB: Universalizing Approximate Query Processing. SIGMOD’18 (research): ACM SIGMOD/PODS International Conference on Management of Data. Houston, TX, USA, 2018.
• Wen He, Yongjoo Park, Idris Hanafi, Jacob Yatvitskiy, Barzan Mozafari. Demonstration of VerdictDB, the Platform-Independent AQP System. SIGMOD’18 (demo): ACM SIGMOD/PODS International Conference on Management of Data. Houston, TX, USA, 2018.
• Yongjoo Park, Amhad Shahab Tajik, Michael Cafarella, Barzan Mozafari. Database Learning: Toward a Database System that Becomes Smarter Over Time. SIGMOD’17 (research): ACM SIGMOD/PODS International Conference on Management of Data. Chicago, IL, USA, 2017. SIGMOD Travel Award.
• Yongjoo Park. Active Database Learning. CIDR’17 (abstract): The biennial Conference on Innovative Data Systems Research. Chaminade, CA, USA, 2017.
• Yongjoo Park, Michael Cafarella, Barzan Mozafari. Visualization-Aware Sampling for Very Large Databases. ICDE’16 (research): IEEE 32nd International Conference on Data Engineering. Helsinki, Finland, 2016.
• Yongjoo Park, Michael Cafarella, Barzan Mozafari. Neighbor-Sensitive Hashing. PVLDB’15 (research) for VLDB’16: 42nd International Conference on Very Large Data Bases. New Delhi, India, 2016.
• Michael Anderson, Dolan Antenucci, Victor Bittorf, Matthew Burgess, Michael Cafarella, Arun Kumar, Feng Niu, Yongjoo Park, Christopher Ré, Ce Zhang. Brainwash: A Data System for Feature Engineering. CIDR’13 (vision): The biennial Conference on Innovative Data Systems Research. Asilomar, CA, USA, 2013.

Patents

• Alekh Jindal, Barzan Mozafari, Yongjoo Park, Brian Westphal, Shi Qiao, Matthew Larson, Advait Abhay Dixit. Platform Agnostic Query Acceleration (United States Patent 11567936)

Conferences Organized or Chaired

• Publicity Chair, 39th IEEE International Conference on Data Engineering (ICDE 2023)
• Co-chair, SIGMOD 2022 Student Research Competition
• Co-chair, SIGMOD 2021 Student Research Competition
• Publicity Chair, ACAIA workshop 2017 (http://dbgroup.eecs.umich.edu/acaia/)

Teaching Honors

• Teaching Excellence, Fall 2022 (2023)

Research Honors

• 2018 ACM SIGMOD Jim Gray Dissertation Award Runner-up (Jun. 2018)

Other Honors

• 2021 Engineering Council Outstanding Advising Award (February 2021 )