publication.md

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My primary publication venues are computer science conferences in the areas of data management, systems, and others.

CONFERENCE PROCEEDINGS

1. Kishu: Time-Traveling for Computational Notebooks
   Zhaoheng Li, Supawit Chockchowwat, Areet Sheth, Ribhav Sahu, Yongjoo Park
   PVLDB 2025 (research)
   (pdf on arxiv)

2. Demonstration of ElasticNotebook: Migrating Live Computational Notebook States
   Zhaoheng Li, Supawit Chockchowwat, Hanxi Fang, Ribhav Sahu, Sumay Thakurdesai, Kantanat Pridaphatrakun, Yongjoo Park
   SIGMOD 2024 (demo)
   Awarded: Artifacts Available & Evaluated
   (pdf on ACM)   

3. AirIndex: Versatile Index Tuning Through Data and Storage
   Supawit Chockchowwat, Wenjie Liu, Yongjoo Park
   SIGMOD 2024 (research)
   (pdf on arxiv)    (source code on GitHub)

4. ElasticNotebook: Enabling Live Migration for Computational Notebooks
   Zhaoheng Li, Pranav Gor, Rahul Prabhu, Hui Yu, Yuzhou Mao, Yongjoo Park
   PVLDB 2023 (research)
   (PVLDB)    (pdf on arxiv)   

5. LADIO: Leakage-Aware Direct I/O for I/O-Intensive Workloads
   Ipoom Jeong, Jiaqi Lou, Yongseok Son, Yongjoo Park, Yifan Yuan, and Nam Sung Kim
   IEEE CAL 2023: IEEE Computer Architecture Letters (research)
   (IEEE page)

6. Transactional Python for Durable Machine Learning: Vision, Challenges, and Feasibility
   Supawit Chockchowwat, Zhaoheng Li, Yongjoo Park
   DEEM workshop @SIGMOD 2023 (research)
   (pdf on arxiv)    (DEEM website)

7. Making Data Clouds Smarter at Keebo: Automated Warehouse Optimization using Data Learning
   The Keebo Team
   SIGMOD 2023 (industry)
   (pdf on ACM)

8. A Step Toward Deep Online Aggregation
   Nikhil Sheoran*, Supawit Chockchowwat*, Arav Chheda, Suwen Wang, Riya Verma, Yongjoo Park
   * indicates equal contributions
   SIGMOD 2023 (research)
   Awarded: Honorable Mention for Best Artifact
   (pdf on arxiv)    (on ACM)    [(slides)]({{ site.url }}/resources/deepola-sigmod23-slides.pdf)

9. S/C: Speeding up Data Materialization with Bounded Memory
   Zhaoheng Li, Xinyu Pi, Yongjoo Park
   ICDE 2023 (research)
   (pdf on arxiv)    (on IEEE)

10. Automatically Finding Optimal Index Structure
    Supawit Chockchowwat, Wenjie Liu, Yongjoo Park
    AIDB workshop @VLDB 2022
    (pdf)    (AIDB website)

11. The Effects of Teaching Modality on Collaborative Learning: A Controlled Study
    Sophia Yang, Yongjoo Park, Abdussalam Alawini
    IEEE Frontiers in Education Conference (FIE) 2022
    (on IEEE)

12. Airphant: Cloud-oriented Document Indexing
    Supawit Chockchowwat, Chaitanya Sood, Yongjoo Park
    ICDE 2022 (research)
    (pdf on arxiv)    (on IEEE)

13. SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations
    Johes Bater, Yongjoo Park, Xi He, Xiao Wang, Jennie Rogers
    PVLDB 2020 (research)
    (pdf)

14. QuickSel: Quick Selectivity Learning with Mixture Models
    Yongjoo Park* , Shucheng Zhong*, Barzan Mozafari
    SIGMOD 2020 (research)
    [(pdf)]({{ site.url }}/resources/quicksel_sigmod20.pdf), (a longer version), (code)
    * indicates equal contributions

15. BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees
    Yongjoo Park, Jingyi Qing, Xiaoyang Shen, Barzan Mozafari
    SIGMOD 2019 (research)
    [(pdf)]({{ site.url }}/resources/blinkml_sigmod19_pdf.pdf)

16. VerdictDB: Universalizing Approximate Query Processing
    Yongjoo Park, Barzan Mozafari, Joseph Sorenson, Junhao Wang
    SIGMOD 2018 (research)
    (pdf), (technical report), [(slides)]({{ site.url }}/resources/verdictdb_sigmod18.pdf), (project website), (GitHub repo)

17. Demonstration of VerdictDB, the Platform-Independent AQP System
    Wen He, Yongjoo Park, Idris Hanafi, Jacob Yatvitskiy, Barzan Mozafari
    SIGMOD 2018 (demo)
    (pdf)

18. Database Learning: Toward a Database that Becomes Smarter Every Time
    Yongjoo Park, Amhad Shahab Tajik, Michael Cafarella, Barzan Mozafari
    SIGMOD 2017 (research)
    (pdf), (technical report), [(slides)]({{ site.url }}/resources/db-learning-slides-sigmod17.pdf)

19. [Active Database Learning]({{ site.url }}/resources/active-cidr17.pdf)
    Yongjoo Park
    CIDR 2017 (abstract)
    [(pdf)]({{ site.url }}/resources/active-cidr17.pdf)

20. [Visualization-Aware Sampling for Very Large Databases]({{ site.url }}/resources/ypark_icde16.pdf)
    Yongjoo Park, Michael Cafarella, Barzan Mozafari
    ICDE 2016 (research)
    [(pdf)]({{ site.url }}/resources/ypark_icde16.pdf), (technical report), [(slides)]({{ site.url }}/resources/vas_slides_icde16.pdf), (demo), (code)

21. Neighbor-Sensitive Hashing
    Yongjoo Park, Michael Cafarella, Barzan Mozafari
    PVLDB 2015 (research)
    (pdf), [(supplementary document)]({{ site.url }}/resources/vldb2016sup.pdf), [(slides)]({{ site.url }}/resources/nsh-slides-vldb16.pdf), (code)

22. Brainwash: A Data System for Feature Engineering
    Michael Anderson, Dolan Antenucci, Victor Bittorf, Matthew Burgess, Michael Cafarella, Arun Kumar, Feng Niu, Yongjoo Park, Christopher Ré, Ce Zhang
    CIDR 2013 (vision)
    (pdf)

TECHNICAL REPORTS

1. Yongjoo Park, Barzan Mozafari, Joseph Sorenson, Junhao Wang
   VerdictDB: Universalizing Approximate Query Processing

2. Yongjoo Park, Amhad Shahab Tajik, Michael Cafarella, Barzan Mozafari
   Database Learning: Toward a Database System that Becomes Smarter Over Time

3. Yongjoo Park, Michael Cafarella, Barzan Mozafari
   Neighbor-Sensitive Hashing

4. Yongjoo Park, Michael Cafarella, Barzan Mozafari
   Visualization-Aware Sampling for Very Large Databases

WORKSHOPS (no proceedings)

1. Yongjoo Park
   Approximation is Bliss: Approximate Computing in Database Systems
   Workshop on Approximate Computing Across the Stack (WAX) 2019, Phoenix, Arizona
   Invited Talk, [(slides)]({{ site.url }}/resources/yongjoo_wax19.pdf)

2. Yongjoo Park, Amhad Shahab Tajik, Michael Cafarella, Barzan Mozafari
   Building Databases that Become Smarter over Time
   Midwest Big Data Opportunities and Challenges (MBDOC) Workshop 2016, Chicago
   [(slides)]({{ site.url }}/resources/dbl-slides-chicago.pdf)

3. Yongjoo Park, Amhad Shahab Tajik, Michael Cafarella, Barzan Mozafari
   Database Learning: Toward a Database System that Becomes Smarter Over Time
   North East Database Day (NEDB) 2016, Oral, MIT
   [(pdf)]({{ site.url }}/resources/ypark_nedb16.pdf), [(slides)]({{ site.url }}/resources/ypark_nedb16_slides.pdf)

4. Yongjoo Park, Michael Cafarella, Barzan Mozafari
   Neighbor-Sensitive Hashing
   3rd Workshop on Web-scale Vision and Social Media (VSM) at ICCV 2015
   Extended Abstract

TALKS

1. SIGMOD, Amsterdam, June 2019
2. WAX workshop, Phoenix, June 2019
3. Criteo NABD conference, Ann Arbor, May 2019
4. University of Texas, Austin, April 2019
5. Penn State University, State College, April 2019
6. Purdue University, West Lafayette, April 2019
7. Northeastern University, Boston, March 2019
8. University of Waterloo, March 2019
9. Georgia Tech, Atlanta, March 2019
10. University of Illinois, Urbana-Champaign, March 2019
11. Microsoft Research, Redmond, February 2019
12. Northwestern University, Redmond, February 2019
13. Microsoft, Redmond, February 2019
14. IBM Research, Almaden, February 2019
15. SIGMOD, Houstin, June 2018
16. AVL (www.avl.com), Ann Arbor, April 2018
17. Oracle BI Group, Redwood City, December 2017
18. ACAIA workshop, San Jose, November 2017
19. Oracle Database Group, Redwood City, November 2017
20. Cloudera Impala Team, Palo Alto, November 2017
21. Big Data Innovation Summit, Boston, Septempber 2017
22. New Tech Meetup, Ann Arbor, July 2017
23. SIGMOD, Chicago, May 2017
24. University of Michigan Software Group, Ann Arbor, May 2017
25. Brown Database Group, Providence, March 2017
26. Stanford InfoLab, Palo Alto, February 2017
27. CIDR, Chaminade, California, January 2017
28. MBDOC, Chicago, September 2016
29. VLDB, New Delhi, India, September 2016
30. ICDE, Helsinki, Finland, May 2016
31. AVL (www.avl.com), Ann Arbor, April 2016
32. NEDB, Boston, January 2016
33. VSM@ICCV, Santiago, Chile, December 2015