Sun Developing Machine Learning Workforce For Earth Science Studies
Ziheng Sun, Research Assistant Professor, Center for Spatial Information Science and Systems (CSISS),received $16,530 from the University of Washington on a subaward from the National Science Foundation for the project: "CyberTraining: Implementation: Medium: GeoSMART: Developing a Machine Learning workforce for earth science studies through training and curriculum development."
Sun will assist University of Washington (UW) researchers in hosting training sessions in hack weeks, co-draft the solicitation of Earth Science Information Partners (ESIP) Lab mini-grant funding opportunities, work with the UW team to organize, develop, and improve the training format and curriculum, serve as coordinator to engage the ESIP machine learning cluster with this project, help the UW team to establish the JupyterHub/Binders/Colab platform for hack weeks, teach community members how to manage their machine learning workflows using Geoweaver, and collect feedbacks from community members.
"This project aims to build the fundamental curriculum materials and train the new-era workforce who will perform the critical geospatial data analysis work in the future. The project will solve the problems caused by lack of systematic learning materials for Earth science students who wish to enrich their toolkit with modern technologies such as deep learning and cloud computing. In a long-term perspective, the project outputs will significantly contribute to relieve the workforce shortage stress against the high demand of Earth domain experts with a background on artificial intelligence," Sun said.
Funding for this award began in September 2021 and will end in late August 2022.