Eugene Wu


Eugene Wu is broadly interested in technologies that help users play with their data. His goal is for users at all technical levels to effectively and quickly make sense of their information. He is interested in solutions that ultimately improve the interface between users and data, and uses techniques borrowed from fields such as data management, systems, crowd sourcing, visualization, and HCI. Eugene Wu received his Ph.D. from MIT, B.S. from Cal, and was a postdoc in the AMPLab. A profile, an obit.

Eugene Wu has received the VLDB 2018 10-year test of time award, best-of-conference citations at ICDE and VLDB, the SIGMOD 2016 best demo award, the NSF CAREER, and the Google, Adobe, and Amazon faculty awards.

The WuLab Blog

Research Overview (circa 2022)

Joining The Lab
PhDs + Postdocs: read a selected publication, share thoughts/extensions, include "bananas" in subject line.
Interns + UGrad + Masters: please contact and talk to the graduate students in the lab.

All Publications (Show Selected)

  1. The Fast and the Private: Task-based Dataset Search
    Zezhou Huang, Jiaxiang Liu, Haonan Wang, Eugene Wu
    CIDR 2024 Slides
  2. DIG: The Data Interface Grammar
    Yiru Chen, Jeffrey Tao, Eugene Wu
    HILDA at SIGMOD 2023
  3. PI2: Generating Visual Analysis Interfaces From Queries
    Yiru Chen, Eugene Wu
    SIGMOD 2022
  4. View Composition Algebra for Ad Hoc Comparisons
    Eugene Wu
    TVCG 2022
  5. Continuous Prefetch for Interactive Data Applications
    Haneen Mohammed, Ziyun Wei, Ravi Netravali, Eugene Wu
    VLDB 2020 Talk Video Blogpost
  6. Complaint-driven Training Data Debugging for Query 2.0
    Young Wu, Lampros Flokas, Jiannan Wang, Eugene Wu
    SIGMOD 2020 Talk Video Blogpost
  7. DeepBase: Deep Inspection of Neural Networks
    Thibault Sellam, Kevin Lin, Ian Yiran Huang, Michelle Yang, Carl Vondrick, Eugene Wu
    SIGMOD 2019
  8. Ten Years of Web Tables
    Michael Cafarella, Alon Halevy, Daisy Zhe Wang, Hongrae Lee, Jayant Madhavan, Cong Yu, Eugene Wu
    PVLDB 2018 Invited Paper,
  9. Provenance in Interactive Visualizations
    Fotis Psallidas, Eugene Wu
    HILDA 2018
  10. Smoke: Fine-grained Lineage at Interactive Speeds
    Fotis Psallidas, Eugene Wu
    VLDB 2018
  11. ActiveClean: Interactive Data Cleaning While Learning Convex Loss Models
    Sanjay Krishnan, Jiannan Wang, Eugene Wu, Michael J. Franklin, Ken Goldberg
    Arxiv 2016
  12. Explaining Data in Visual Analytic Systems
    Eugene Wu
    Doctoral Thesis 2015
  13. The Case for Data Visualization Management Systems
    Eugene Wu, Leilani Battle, Samuel Madden
    VLDB 2014
  14. Scorpion: Explaining Away Outliers in Aggregate Queries
    Eugene Wu, Samuel Madden
    VLDB 2013 (Best-of) Slides
  15. Human-powered Sorts and Joins
    Adam Marcus, Eugene Wu, David Karger, Samuel Madden, Robert Miller
    VLDB 2012
  16. High-performance complex event processing over streams
    Eugene Wu, Yanlei Diao, Shariq Rizvi
    SIGMOD 2006