A career in orbit


A portrait of Hannah Kerner.

Hannah Kerner, an assistant professor of computer science and engineering in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University, has received a 2025 National Science Foundation Faculty Early Career Development Program (CAREER) Award for her work in artificial intelligence and satellite remote sensing. Photo by Samantha Chow/ASU

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In a significant recognition of her pioneering achievements at the intersection of artificial intelligence and global sustainability, Hannah Kerner has received a 2025 National Science Foundation Faculty Early Career Development Program (CAREER) Award.

Kerner is an assistant professor of computer science and engineering in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at Arizona State University. The new award supports her efforts to revolutionize machine learning approaches for satellite remote sensing data — work that has the potential to reshape how we monitor, understand and care for our planet.

As satellites orbit the Earth, they collect tons of data, including everything from photographs of landscapes to measurements of heat, moisture and vegetation. Because this data is captured without touching the ground, it’s called remote sensing. Scientists use this information to study things like weather patterns, crop health, deforestation and disaster damage. This data can help us understand what’s happening across the planet, especially in places we can’t easily reach.

The team in the Kerner Lab is tackling one of the biggest challenges in the field: bridging a critical gap between the staggering quantity and complexity of data captured by satellites and our current ability to use that information in meaningful and socially beneficial ways.

“Satellite remote sensing data is incredibly powerful, but most machine learning models treat it like it’s no different from standard photos,” Kerner says. “That approach just doesn’t work when you’re trying to analyze a complex planet that’s constantly changing.”

With support from the National Science Foundation, Kerner and her team are developing new AI and machine learning tools to make satellite data easier to use and more accurate, even in unfamiliar or rapidly changing environments.

At the heart of the project are three advanced algorithms, which are essentially step-by-step instructions that computers follow to solve problems or make decisions based on data. These algorithms will help computers better understand and interpret the complex information collected by satellites, like images of farmland, forests and coastlines. The team will also build a testing platform to see how well their tools hold up when applied to new regions or conditions.

One of the most exciting innovations is called “zero-shot mapping.”

This novel algorithm will enable machine learning systems to be trained without the need for large quantities of manually labeled data, and will also let users ask questions in plain language. The goal is to create tools that open the door for scientists, farmers, policymakers and others around the world to put satellite insights to practical use without needing AI expertise.

A map generated by the Fields of The World research team illustrates cropland in rural Cambodia.
A map generated by the Fields of The World research team illustrates cropland in rural Cambodia. Led by Kerner, the team is using AI to map the world’s fields, combining satellite imagery and machine learning insights. The project aims to improve food security and provide better tools for supply chain management. Photo courtesy of Fields of The World

From CAREER Award to career impact

This new project marks the next step in Kerner’s rapidly growing, high-impact career.

For example, in the Fields of The World project, Kerner leads a research team through the development of AI models that analyze satellite imagery to detect croplands and draw field boundaries — an essential step for improving agricultural monitoring and planning. Supported by the Taylor Geospatial Engine and Microsoft’s AI for Good Lab, the team has already produced openly accessible data that’s in use around the world.

“Nearly every aspect of agriculture improves when we have a digital map of the world’s fields,” Kerner says. “Our goal is to fill in the gaps where no data exists, which means training AI systems to recognize what a field looks like, even in regions with little or no labeled information.”

To accomplish that, the team had to innovate. Their project compares snapshots taken during planting and harvesting seasons to detect changes over time, a method that allows their AI systems to learn how to define the shapes and borders of farmland.

Kerner’s AI-for-all philosophy has already made its way to Maui, where her team is applying similar satellite-powered AI tools to support local farmers. Through the Maui Nui Crop Monitor, her lab shares insights with growers via an easy-to-read newsletter filled with satellite data on rainfall, soil moisture and even lunar planting guidance.

Her CAREER project will expand these strong community partnerships. Through an education initiative called AI for ʻĀina, Kerner and her team will collaborate with communities in Maui County to bring culturally grounded AI education to students in Hawaiʻi. The program will provide hands-on, locally relevant learning opportunities for middle school, high school and community college students.

“This is about making AI useful to everyone, not just in the lab, but in the field and in our communities,” Kerner says.

Hannah Kerner works with fellow researchers.
Kerner works with researchers at the Centre de Suivi Ecologique in Dakar, Senegal. Last June, as part of the NASA SERVIR West Africa project, she led a presentation on how scientists can turn satellite maps into useful insights. The workshop was part of her ongoing efforts to build global relationships that can help local communities benefit from AI advancements. Photo courtesy of Kevin Horn/NASA

Global problems, local solutions

Kerner’s future-forward vision doesn’t just push boundaries. It redefines them. By developing machine learning tools that can adapt to shifting geographies, languages and environments, she’s building systems that are not only more intelligent but also more equitable and accessible.

Through her collaborations with NASA Harvest and NASA Acres, and in her role as a faculty member in ASU’s Center for Global Discovery and Conservation Science, Kerner is well positioned to translate her research into immediate real-world impact. Those collaborations span from national food security efforts to community-level agricultural support, ensuring that her lab’s innovations are not just technically sophisticated, but also deeply human.

Ross Maciejewski, director of the School of Computing and Augmented Intelligence, says that Kerner is poised to expand her impactful reach even further.

“The NSF CAREER Award is a major milestone and a strong endorsement of both Hannah’s accomplishments and her vision for the future,” he says. “She’s not only advancing AI research but doing so in a way that directly benefits people and communities. This award will amplify her ability to make a real and lasting impact.”

With the award and a growing list of impactful projects, Kerner is proving that when AI meets human needs, the results can be extraordinary.

For Kerner, it’s about more than just algorithms.

“It’s about making sure people have food on the table. It’s about giving communities the tools they need to thrive. And it’s about making technology something that works for everyone, not just the people who create it,” she says.

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