Paul G. Allen Center, Microsoft Atrium
Jeffrey Heer, Associate Professor, UW Computer Science & Engineering
Interactive Data Analysis
Abstract
Data analysis is a complex process with frequent shifts among data formats and models, and among textual and graphical media. We are investigating how to better support this lifecycle of analysis by identifying critical bottlenecks and developing new methods at the intersection of data visualization, machine learning and computer systems. Can we empower users to transform and clean data without programming? Can we design scalable representations and systems to visualize and query big data in real-time? How might we enable domain experts to guide machine learning methods to produce better models? I will present selected projects that attempt to address these challenges and introduce new tools for interactive visual analysis.
Speaker Bio
Jeffrey Heer is an Associate Professor of Computer Science & Engineering at the University of Washington, where he works on human-computer interaction, data visualization and social computing. The visualization tools developed by his lab (D3, Protovis, Flare, Prefuse) are used by researchers, companies and thousands of data enthusiasts around the world. His group has received Best Paper and Honorable Mention awards at the premier venues in Human-Computer Interaction and Information Visualization (ACM CHI, ACM UIST, IEEE InfoVis, IEEE VAST). In 2009 Jeff was named to MIT Technology Review's TR35 and in 2012 he was named a Sloan Foundation Research Fellow. He holds BS, MS and PhD degrees in Computer Science from the University of California, Berkeley.
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