I'm an assistant professor in the Department of Computer Science at the University of Arizona. I work in large-scale data visualization and exploratory data analysis. Before coming to sunny, beautiful Tucson, I worked at AT&T Research in New York.

Interactive visualization is crucial in understanding, exploring, and presenting data, but data scale can present serious barriers for effectiveness and adoption. I study these barriers and design solutions to remove them. My work ranges from theoretical to practical; from designing solutions specifically for particular domains to designing general infrastructure for large-scale visualization.

Since joining UA, I have worked in a number of projects here, including support for interactive browsing of synteny data at CoGe, and building up interactive visualization infrastructure at NOAO and the ANTARES project.


I have two open, funded PhD research assistantships. First, I'm looking for a PhD student to work on the intersection of topological data analysis and interactive, large-scale data visualization. I'm also looking for a separate student to work on the visualization infrastructure for the ANTARES project.

I am generally interested in the intersection of computer science and large-data visualization, as illustrated, for example, by the IEEE VIS workshop I have co-organized. If any of the papers in that workshop seem interesting, or (even better!) if you've done similar work in the area, please contact me, and tell me about your work, and why you think you'd be a good fit for these projects.


  • Nanocubes: blazing fast large data visualization.
  • Lux: write WebGL shaders in Javascript, composably.
  • RCloud: collaborative data analysis, on the web.
  • VisTrails: a provenance-aware scientific workflow system.
  • Vector-field k-means: scalable trajectory clustering.
  • Afront: high-quality triangle meshing of surfaces.