Since getting her Ph.D. in mathematics from Duke, Rachel Thomas has worked as a quant, data scientist, & backend engineer at Uber, and professor in University of San Francisco’s (USF) Masters of Analytics program. She’s currently a researcher-in-residence at USF’s Data Institute and co-founded Fast.ai, which makes practical deep learning education accessible globally. Thomas’ students have leveraged their knowledge to reduce farmer suicides in India, assist the visually impaired, and treat Parkinson’s disease.
When Thomas first started researching deep neural networks a few years ago, virtually no educational resources existed online. “It seemed like everyone in the field had done their Ph.D. with the same four advisors and nobody was sharing the practical, useful info,” she observed. As a solution, she co-produced a free Practical Deep Learning for Coders course intended to ramp anyone with reasonable coding skills up on applied neural network approaches. Thomas’ initiative has been successful in enabling more women, people of color, international students, and the economically disadvantaged to participate in AI research and engineering.
Thomas graduated from Swarthmore College in 2005 with a B.A. in mathematics. She earned her Ph.D. at Duke University.