TWIMLfest 2020

Speaker

Photo: Sherrie Wang

Sherrie Wang

PhD Student
Stanford University
Connect with Sherrie

Sherrie Wang is a PhD student at Stanford studying applied math (ICME), advised by Professor David Lobell at the Center on Food Security and the Environment. Her research uses modern data science techniques to understand agricultural management and productivity, especially in developing countries where ground truth labels are scarce. Toward this end, she works with large-scale satellite imagery, develop machine learning methods for low-data regimes, and explore the use of non-traditional data sources for ground truth. Prior to her PhD, she studied Biomedical Engineering at Harvard University (2014) and worked in New York City post-graduation.

Conference Sessions

TWIMLfest  2020
Why is machine learning hard in the agricultural domain, how does addressing these challenges broaden our understanding of machine learning generally, and what challenges exist around adoption within the global agricultural community? This session will feature speakers from both academia and industry.