Emily Gordon

I am a Stanford Data Science Postdoctoral Fellow at Stanford Data Science, working with Dr. Noah Diffenbaugh. My research interests lie at the intersection of novel data science methods, and climate variability and predictability. My doctoral research focused on adapting machine learning techniques to understand where and when we can make skillful predictions of large-scale climate variability. Using the springboard, I am interested in developing machine learning approaches to improve estimates of future likelihoods of impacts of climate change. In particular, I am interested in using explainable and interpretable AI techniques to both develop improved predictions, but also to interrogate model predictions. These methods can both increase trust in the machine learning “black box”, and lead to better understanding of our climate system.

I obtained both my B. Sc. (2018) and M. Sc. (2020) in physics from the University of Otago in Dunedin, New Zealand, and my Ph. D. in atmospheric science from Colorado State University in 2023.