Hannah Kerner, an assistant professor of computer science and engineering at Arizona State University, has been selected as the U.S. nominee for the 2026 APEC Science Prize for Innovation, Research and Education (ASPIRE Prize). The nomination recognizes her work building AI systems that use satellite data to improve agriculture, speed disaster recovery, and make environmental information more accessible to communities without deep technical resources.
The international winner, chosen from nominees across APEC member economies, will be announced in August. The 2026 competition focuses on "Advancing Scientific Research in AI and Data Science to Promote Industrial Innovation and Economic Resilience."
From satellite data to food security
Kerner serves as the AI lead for NASA Harvest and NASA Acres, programs that convert vast stores of satellite imagery into practical tools for monitoring crop health, spotting drought conditions, and supporting food security efforts worldwide. Her lab designs tools that let farmers, local governments, and community organizations query the data in plain language rather than code.
One of the lab's major initiatives, Fields of The World, uses AI to create one of the most detailed open maps of agricultural fields ever assembled. The project is backed by the Taylor Geospatial Engine and Microsoft's AI for Good Lab. Kerner's approach runs counter to the commercial AI mainstream: she measures success by whether the technology helps people make better decisions, not by how many emails it can write.
Recognition for people-centered AI
"It is an incredible honor to be selected as the U.S. nominee for the APEC ASPIRE Prize," Kerner said. "I'm grateful to my students, collaborators and partners at ASU, NASA and around the world whose dedication has made this work possible. This recognition reflects our shared belief that AI can be a powerful tool for addressing critical global challenges."
The nomination adds to a string of recent honors. Kerner received a 2025 National Science Foundation CAREER Award and was named a Schmidt Sciences AI2050 Early Career Fellow. Her work sits at the intersection of AI for Science & Research and practical deployment, showing how models trained on Earth observation data can directly support economic resilience and environmental management.
Ross Maciejewski, director of the School of Computing and Augmented Intelligence at ASU, said the recognition "celebrates both her remarkable scientific achievements and her vision for using AI to improve lives."
Why this matters for science and research professionals
Kerner's work demonstrates a model for research that moves AI from lab benchmarks to field-level impact. For scientists and engineers, the key takeaway is the emphasis on open-source tools, cross-sector collaboration, and interfaces designed for non-experts. The same approach-prioritizing usability and public value over raw performance metrics-can be applied across disciplines that rely on large-scale data interpretation, from climate science to public health.
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