Neal Jean

I’m a PhD student working with Stefano Ermon in the Stanford AI Lab, where we’re using machine learning to tackle challenging problems in sustainability and healthcare. I’ve also spend some time at the Future of Humanity Institute at the University of Oxford.

I previously studied econ and math at Duke and electrical engineering at Georgia Tech. I love basketball — my senior thesis was about the NBA — but unfortunately I’m too deep in this school thing now to make it to the league.

Publications


Combining satellite imagery and machine learning to predict poverty
N. Jean, M. Burke, M. Xie, W. M. Davis, D. B. Lobell, S. Ermon
Science, 353(6301), 790-794, 2016
Video / PDF / Website / Commentary / Code

Produced district-level poverty maps in Nigeria, Tanzania, Uganda, Malawi, and Rwanda using high-resolution satellite imagery, household surveys, and deep learning. Bill Gates tweeted our research!


Transfer learning from deep features for remote sensing and poverty mapping
M. Xie, N. Jean, M. Burke, D. B. Lobell, S. Ermon
AAAI Conference on Artificial Intelligence, 2016
PDF / NYTimes

Using nighttime lights as a proxy for poverty, extracted satellite image features with CNNs to estimate poverty rates in Uganda.