Geospatial Innovation for Food Security
Fields of The World
Features of The World
Benchmarks of the World
About Hannah Kerner
As a Research Advisor at Taylor Geospatial, Hannah Kerner helps ensure our GeoAI research is world-class while staying grounded in what will empower innovators and communities to address complex challenges. Hannah helps us transform breakthrough science into the datasets, models, and tools that become digital public goods.
Hannah is an assistant professor at Arizona State University’s School of Computing and Augmented Intelligence. Her lab’s research topics include machine learning for remote sensing, algorithmic bias, and machine learning theory.
Through her roles as the AI/Machine Learning Lead for NASA Harvest and NASA Acres, Center Faculty for the ASU Center for Global Discovery and Conservation Science (GDCS), and Research Advisor for Taylor Geospatial, she has advanced agricultural monitoring and food security on a global scale, with projects that have directly shaped agricultural planning, disaster response, and financial relief worldwide.
Hannah has been recognized by multiple research awards including the NSF CAREER Award (2025), Schmidt Sciences AI2050 Early Career Fellowship (2025), and Forbes 30 Under 30 in Science (2021). She also was the U.S. Nominee for the 2026 APEC Science Prize for Innovation, Research and Education (ASPIRE).
What sets Hannah apart is her ability to bridge the academic-industry gap. She builds models that don’t just excel on benchmarks—they adapt to new geographies, handle operational realities, and tackle problems at global scale.
If you’re working at the frontier of open-source machine learning for Earth observation, food security, or satellite remote sensing, Hannah wants to hear from you. Reach out to share what you’re researching or building.