Jeff directs the Interactive Data Lab at the University of Washington. Jeff’s research investigates the perceptual, cognitive and social factors involved in making sense of large data sets, resulting in new interactive systems for visual analysis and communication. He applies methods from computer science, psychology and data analysis to problems in visualization and human-computer interaction. His lab seeks to develop tools that increase the efficiency and effectiveness of data analysts.
Jeff's research has led to new techniques for working with and understanding data, as well as new insights for improving visualization design. The visualization tools developed by his lab (D3.js, Protovis and Vega) are used by researchers, companies and thousands of data enthusiasts around the world, with use cases ranging across academic research, industrial data science and data-driven journalism (for example at the New York Times). Jeff's students have also gone on to found start-up companies based on their research on interactive data transformation (Trifacta) and human language translation (Lilt).
Jeff’s research group has received awards at the premier venues in Human-Computer Interaction and Information Visualization. Jeff was named one of MIT Technology Review's Top 35 Innovators Under 35 and he is a co-founder of Trifacta, a provider of interactive tools for scalable data transformation. Jeff earned his PhD from the University of California, Berkeley.
Google Scholar Profile
UW Interactive Data Lab on GitHub
Vega Project on GitHub
University of Washington, Department of Computer Science & Engineering