Daniel Runfola

Daniel Runfola is an Assistant Professor of Applied Science at the College of William & Mary, where he also serves as the Director of the Data Science Program. He is affiliated with the Faculty of Arts & Sciences and conducts interdisciplinary research at the intersection of machine learning, satellite imagery, and human development.

His research focuses on leveraging novel neural network architectures and geospatial data to measure and improve human well-being at multiple scales. He leads the geoLab, a research group dedicated to advancing data science for social good, particularly in under-resourced regions. The lab collaborates with federal agencies and international NGOs and contributes to open-source initiatives like the geoBoundaries Open Administrative Boundaries dataset to promote global data equality.

Dr. Runfola actively mentors undergraduate and Ph.D. students, supporting their research in AI-driven geospatial analysis. He is currently recruiting motivated Ph.D. students with strong Python skills and interests in computer vision and satellite data. His work involves extensive computational experimentation, including developing secure methods for analyzing large-scale remote sensing data.

He emphasizes open science and practical applications of AI in real-world development contexts, often engaging in projects that bridge technical innovation with humanitarian goals.