Wednesday, January 12, 2022 - 1:00pm to 2:00pm
https://oregonstate.zoom.us/j/93591935144?pwd=YjZaSjBYS0NmNUtjQzBEdzhPeDZ5UT09

Speaker Information

Hannah Kerner
Assistant Research Professor
Department of Geographical Sciences
University of Maryland

Abstract

Satellite Earth observation (EO) data is rapidly gaining interest in the AI community due to the massive datasets involved as well as the opportunities for using AI and EO data to address urgent challenges related to climate change, the environment, agriculture and food security, and humanitarian needs. However there are currently many challenges for developing AI systems that use EO data for practical applications, namely, there are limited public labeled datasets, a lack of harmonization across labels and source data, and existing algorithms do not account for geographic context. In this talk, I'll present some of the approaches we are developing to address these challenges to create AI+EO systems that can be integrated into real-world applications for advancing global food security and other sustainable development goals.

Speaker Bio

Dr. Hannah Kerner is an Assistant Research Professor in the Department of Geographical Sciences at the University of Maryland. Her research focuses on developing new machine learning methods for geospatial and remote sensing data and applications including agricultural monitoring, food security, Earth science, and planetary science. Dr. Kerner is the Machine Learning Lead and US Co-Lead for NASA Harvest, NASA’s agriculture and food security initiative run out of the University of Maryland.