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Dan Runfola

Associate Professor, Applied Science; Director of Graduate Studies

Office: Integrated Science Center 1269
Email: [[w|dsmillerrunfol]]
Areas of Interest: Computational Geography, Human-Environment Relations, Geospatial Analysis
Webpage: {{http://www.danrunfola.com, Personal Website}}

Background

I am an associate professor of Data Science and Applied Science at William & Mary, currently working at the nexus of deep learning and satellite imagery analysis. I work with federal agencies and international NGOs to develop new and secure ways to measure, predict, and improve human wellbeing at micro to macro scales. In collaboration with my wonderful students in the geoLab, I also help to provision critical baseline data to the opensource community to improve data equality around the world.

Things that I spend my time on today include:

  • Supporting my undergraduate and Ph.D. students' research through the geoLab.
  • Coding for the geoBoundaries Open Administrative Boundaries dataset
  • Publishing some good ideas, burning cycles on bad ones.
  • A range of projects exploring how novel neural network architectures can aid us in extracting data from satellites. I.e., "playing with fancy videocards".
  • Forgetting to update my CV

If you are reading this page, please note that I am always looking for exceptional Ph.D. students! Good at Python, interested in computer vision and satellite data? Like Williamsburg when you came as an elementary school student? Email me!

Education
  • B.A., Georgia State University
  • Ph.D., Clark University