A Geographer @ William and Mary
- Office: ISC 1269 (Labs: ISC 1109, ISC 1252)
- Office Hours: Tuesday and Thursday 1530 - 1700
- Office Phone: 1-757-221-1970
- Email: firstname.lastname@example.org
- Web: http://DanRunfola.github.io
- Mailing Address:
- Department of Applied Science
- College of William and Mary
- Williamsburg, VA 23187-8795, USA
Dan Runfola is an assistant professor of Applied Science at William and Mary. Dan has served as PI on over $2 million dollars of funded research at the nexus of machine learning, imagery analysis, and climate change. His core expertise is in the applied use of machine learning to analyze spatial data - both for imagery classification and for causal attribution. In addition to 35+ peer reviewed academic publications in high profile outlets including Nature, Dan has published numerous policy-oriented reports with the US Army Corps of Engineers, Global Environment Facility, World Bank, and as a contributor to the United Nation's Intergovernmental Panel on Climate Change. At William and Mary, Dan served as the inaugural director of the Data Science Program, and is currently the PI of the Geospatial Evaluation and Observation Lab (geoLab).
- Data Science:
- DATA 146 - Introduction to Data Science (Reasoning Under Uncertainty) (syllabus)
- DATA 201 - Data Driven Decisionmaking (syllabus)
- DATA 100 - Breaking Intuition (syllabus)
- DATA 490 - Independent Research in Data Science (syllabus)
- Applied Science:
- APSCI 691 - Applied Machine Learning (syllabus)
Student Advising and Research
- Undergraduates interested in working on research projects involving spatial data retrieval, simulation and analysis during their time at William and Mary can visit my research group’s website to learn more about research opportunities.
- Students interested in pursuing a degree in Data Science are encouraged to reach out to me via email to setup an appointment to discuss their options and career pathways.
- Students interested in pursuing a Ph.D. degree in Computational Geography or Geospatial Analytics are encouraged to reach out to me - I recruit new Ph.D. students frequently to support new research projects, and select students based on fit with ongoing activities. Email is encouraged, but you can also find me at a number of academic and professional conferences.