Dan Runfola is an assistant professor of Applied Science at William and Mary. His research focuses on the intersection between large-scale spatial data, machine learning, and international development. He serves as the Director of the Data Science Program, and the Senior Geospatial Scientist at AidData. Additionally, he leads the GeoQuery research project, a joint Ph.D. and undergraduate lab which develops new geocomputational methods for the processing of large-scale spatial datasets in highly parallelized environments.
PhD in Geography, 2012
BA in Geography, 2008
Georgia State University
Automatically generated from google scholar, apologies for errata. See my CV for an accurate, but unlinked, list of my publications.
Undergraduates interested in working on research projects during their time at William and Mary can visit my research group’s page - www.geoquery.org - to learn more about research opportunities. You can also sign up to be a member of the lab at the bottom of http://www.geoquery.org/accolades/ ; more information is available on the sign up form.
I recommend that interested students take coursework from the Data Science Program (http://ds.wm.edu) at William and Mary to prepare them for their time in the lab. Additionally, quantitative coursework in economics and basic geospatial analysis skills taught in the Center for Geospatial Analysis can make your application more competitive.
Funded Ph.D. graduate student positions are available to participate in a research program (AidData ; http://www.aiddata.org) to assist in developing new machine learning and remote sensing techniques for estimating the impacts of international aid across the globe. Successful candidates will have a strong interest in high performance computation for the synthesis and analysis of spatial data; integration of survey- and satellite-based data; methods to account for spatial imprecision and concomitant uncertainty; and machine learning analytic techniques. Projects will have a strong, applied focus on causal identification of the impacts of spatially-referenced international aid projects on a variety of outcome measurements; students should expect and be prepared to interact directly with policymakers as a part of their Ph.D. activities.
Research assistanships include a competitive stipend, tuition and health benefits. Additional resources about the program include the Applied Science Website (http://as.wm.edu) and the William and Mary graduate admissions page (http://www.wm.edu/as/graduate/admission/index.php). As a top public research university, William and Mary offers Arts & Sciences graduate degree programs that are highly selective, involve close collaboration with faculty members, and provide opportunities for interdisciplinary study. Students in the natural and computational sciences are encouraged to take advantage of William and Mary’s strong connections with research laboratories and consortia in the area. Review of applications begins annually each year in early February.