Computer Science
Eugene Wu develops systems and algorithms for modern interactive data analysis. His research focuses on the full interactive data analysis stack: from data cleaning and preparation, to scalable systems for interactive exploration interfaces, to automatic interface generation, to explanation tools that help explain anomalies encountered during data analysis. His current project is the Data Visualization Management System, which integrates concepts from database research, such as declarative languages, query optimization, and lineage, with interactive visualizations, making it easier to design, architecture, build, and scale rich visual data exploration systems.
- Postdoctoral fellow, U.C. Berkeley, 2015
- Assistant Professor, Columbia University, 2015-
- Best Demo Award, SIGMOD 2016
- Best of Conference Citation, ICDE 2013
- Best of Conference Citation, VLDB 2013
- Eugene Wu, Fotis Psallidas, Zhengjie Miao, Haoci Zhang,Laura Rettig, Yifan Wu, Thibault Sellam Combining Design and Performance in a Data Visualization Management System CIDR 2017
- Xiaolan Wang, Alexandra Meliou, Eugene Wu QFix: Diagnosing errors through query histories SIGMOD 2017
- Sanjay Krishnan, Jiannan Wang, Eugene Wu, Michael J. Franklin, Ken Goldberg ActiveClean: interactive data cleaning for statistical modeling VLDB 2016
- Eugene Wu, Leilani Battle, Samuel Madden The Case for Data Visualization Management Systems VLDB 2014
- Eugene Wu, Samuel Madden Scorpion: Explaining Away Outliers in Aggregate Queries VLDB 2013
- Eugene Wu, Samuel Madden, Michael Stonebraker SubZero: a Fine-Grained Lineage System for Scientific Databases ICDE 2013
- Adam Marcus, Eugene Wu, David Karger, Samuel Madden, Robert Miller Human-powered Sorts and Joins VLDB 2012
- Michael Cafarella, Alon Halevy, Daisy Wang, Eugene Wu, Yang Zhang WebTables: Exploring the Power of Tables on the Web VLDB 2008
- Eugene Wu, Yanlei Diao, Shariq Rizvi High-performance complex event processing over streams SIGMOD 2006