Starting Spring 2023, I will be an Assistant Professor at MIT in the Department of Mechanical Engineering and IDSS. I am accepting new PhD students and postdocs for Fall 2023. If you’re interested, please email me at sherwang [at] mit [dot] edu with your interests and CV!
My research uses novel data and computational algorithms to monitor our planet and enable sustainable development. My focus is on improving agricultural management and mitigating climate change, especially in low- or middle-income regions of the world. To this end, I frequently use satellite imagery, crowdsourced data, LiDAR, and other spatial data. Due to the scarcity of ground truth data in these regions and the noisiness of real-world data in general, my methodological work is geared toward developing machine learning methods that work well with these constraints.
Currently, I am a Ciriacy-Wantrup Postdoctoral Fellow at UC Berkeley, hosted by Solomon Hsiang and the Global Policy Lab. In 2021, I obtained my PhD in Computational and Mathematical Engineering from Stanford University, where I was advised by David Lobell and benefited from mentors at the Center on Food Security and the Environment and the Sustainability and AI Lab.
|Jan 11, 2023||I’m excited to collaborate with AgStack and the Linux Foundation to build the world’s first global dataset of agricultural field boundaries! See our recent paper for more details.|
|Dec 19, 2022||A preprint of our paper using GEDI to map tall and short crops on a global scale over 2019-2021 is now on arXiv.|
|Dec 12, 2022||I’m at AGU! I gave a talk on our work using lidar to map crop types, and my co-author Hikari Murayama presented a poster on monitoring power plant GHG emissions from space.|
- Unlocking large-scale crop field delineation in smallholder farming systems with transfer learning and weak supervisionRemote Sensing, 2022
- SustainBench: Benchmarks for monitoring the Sustainable Development Goals with machine learningNeurIPS Datasets and Benchmarks Track, 2021
- Mapping crop types in southeast India with smartphone crowdsourcing and deep learningRemote Sensing, 2020
- Meta-learning for few-shot land cover classification2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020