Dan Runfola

AidData, William and Mary, Williamsburg, VA, USA

Who is this guy?

Hi! I’m Dan Runfola, a geographer based out of the College of William and Mary.  This website exists to expose my research to a broader audience, and let me provide some brief commentary in “non-academicese” on a variety of academic papers I’ve published.

Right now, most of my time is dedicated to my responsibilities as the Senior Geospatial Scientist for a project called AidData – an organization dedicated to collecting information on where (spatially) international aid goes, and then using that data to understand if it worked or not.  Most of my research is an interdisciplinary mix of Computational Geography and Statistics – figuring out how to use lots of computers to integrate and analyze satellite data (ranging from visual to hyper-spectral data) and then develop new  approaches to understand if aid really caused positive change – or not.  My particular interests lay in climate-related outcomes (i.e., forest cover and carbon sequestration), but the methods are applicable to a wide set of possible outcomes – I find myself talking with scholars and practitioners interested in everything from health to conflict.

I received my Ph.D. from Clark University, and conducted my postdoctoral work at the National Center for Atmospheric Research, where I was able to contribute a few maps to the most recent United Nations IPCC report.  Nowadays I work with organizations like the World Bank, MacArthur Foundation, and USAID – a wide set of research enabled by some awesome students.


Most of my articles are published alongside students working with me in the AidData Research and Evaluation Unit. Students interested in joining us should consider Data Science, Computer Science, Geography, or Math coursework.  Undergraduate, Masters, and Ph.D. students interested in working in highly interdisciplinary research environments are encouraged to apply to work with us!


You can see all student co-authored publications on my CV, denoted with a *!

With Seth Goodman (Ph.D. Student), Rob Marty (MS Student)
A Top-Down Approach to Estimating Spatially Heterogeneous Impacts of Development Aid on Vegetative Carbon Sequestration. Sustainability.

With Rob Marty (W&M Undergraduate Thesis)
Taking the Health Aid Debate to the Sub-National Level: The Impact and Allocation of Foreign Health Aid in Malawi. BMJ Global Health. 

With Raphael Nawrotzki (Ph.D. Student) 
The Influence of Migration on Exposure to Extreme Weather Events: A Case Study in Mexico.” 2015, Society and Natural Resources.

With Tom Hamill (MS Student) and Albert Decatur (Undergraduate Student):
Exploring hybrid remote sensing and interpolative approaches for rapidly mapping discrete units of interest.  International Journal of Geospatial and Environmental Research.


Students at all stages of their career are welcome to join the lab, so long as they bring an interest in understanding the impact of international aid using computational techniques.  

W&M Undergraduates
Most semesters I take on undergraduate research assistant as a part of either capstone research experiences or independent / directed studies.  If you're interested in working in the lab, I recommend you:
(1) Enroll in Data Science or Computer Science coursework (programming and basic modeling skills are a necessity).
(2) Make sure you've taken and passed DS 140 OR CS 141.  DS 146 and DS 201 are also recommended.
(3) Email me to set up a meeting (danr@wm.edu). I may direct you to meet with another member of the lab first depending on your interests.

Prospective Masters Graduate Students
If you are interested in a Masters degree, I recommend looking into the Masters in Public Policy (MPP) program here at William and Mary.  Many MPP Students have worked with a variety of researchers at AidData, including myself.

Prospective Ph.D. Graduate Students
Annually, I accept a small number of Ph.D. students as a part of the Computational Geography program in Applied Science at William and Mary.  If you're interested in high performance computation with spatial data and are considering a Ph.D., feel free to contact me at danr@wm.edu for more information.

Data Science @
William and Mary

I serve as the inaugural Director of the Data Science Program at William and Mary.

  • Data Science is the study and application of methods that extract knowledge from frequently large, diverse sets of data. Data can come from anywhere: newspaper articles, satellite images, or genomes for example.
  • Data Science pairs with any other major offered at William & Mary.
  • You can learn more at ds.wm.edu.