Sherrie Wang
- PhD Student, Stanford University
- sherwang (at) stanford (dot) edu
I’m a PhD student at Stanford studying applied math (ICME),
advised by Professor David Lobell
at the Center on Food Security and the Environment. I work
on developing machine learning methods for remote sensing
applications, especially in settings where ground truth labels are scarce.
These methods are then applied to problems in sustainable agriculture and development,
such as mapping where crops are grown in developing countries.
Prior to my PhD, I studied Biomedical Engineering at Harvard University (2014) and worked in New York City post-graduation. Outside of research, I enjoy hiking, cycling, sketching, and reading books.
Interests. Machine learning, remote sensing, sustainability
Prior to my PhD, I studied Biomedical Engineering at Harvard University (2014) and worked in New York City post-graduation. Outside of research, I enjoy hiking, cycling, sketching, and reading books.
Interests. Machine learning, remote sensing, sustainability
Publications
In Submission
-
Mapping crop types in southeast India with smartphone crowdsourcing and deep learning,
In submission. Sherrie Wang, Stefania Di Tommaso, Joey Faulkner, Thomas Friedel, Alexander Kennepohl, Robert Strey, David Lobell
2020
- Weakly supervised deep learning for segmentation of remote sensing imagery, Remote Sensing. Sherrie Wang, William Chen, Sang Michael Xie, George Azzari, David Lobell
2019
- Satellites reveal a small positive yield effect from conservation tillage across the US Corn Belt, Environmental Research Letters. Jillian Deines, Sherrie Wang, David Lobell
- Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data, AAAI. [code] [blog] Neal Jean, Sherrie Wang, Anshul Samar, George Azzari, David Lobell, Stefano Ermon
- Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques, Remote Sensing of Environment. Sherrie Wang, George Azzari, David Lobell