NASA Acres Chief Scientist Kaiyu Guan Named 2026 MacArthur Fellow

NASA Acres Chief Scientist Dr. Kaiyu Guan of the University of Illinois Urbana-Champaign has been named a 2026 MacArthur Fellow, one of the nation’s most distinguished honors recognizing exceptional creativity, significant achievement, and the promise of important future advances.

The MacArthur Fellowship celebrates individuals whose accomplishments demonstrate originality and the potential to shape their fields in consequential new ways. Each Fellow receives an $800,000 award over five years, providing the freedom to pursue ambitious ideas and continue advancing their contributions.

Guan was recognized for combining Earth observations, process models, and machine learning to understand and predict interactions among crops, environmental conditions, and agricultural practices. His research connects observable factors—including crop conditions, climate, water, and nutrient resources—with the biological and physical processes that govern agricultural ecosystems, strengthening the ability to monitor, predict, and optimize crop yields, environmental benefits, and resource use.

Empirical evaluation and recommendations for equivalent soil mass adjustment of soil organic carbon stocks

Measuring changes in fixed-depth soil organic carbon (SOC) stocks can be problematic when soils have compacted or expanded and bulk density has changed. A recent study by NASA Acres RD&E partner Dr. Eric Potash and colleagues evaluated equivalent soil mass (ESM) accuracy using 72 soil cores from six sites across the central United States. Researchers found that 0–30 cm fixed-depth measurements had systematic errors of up to 8%, while adding a 30–35 cm “correction layer” reduced error to less than 1.5% in both major soil types studied. The findings offer recommendations for more accurate and cost-effective SOC stock change estimation using ESM.

Arizona State University’s (ASU) School of Computing and Augmented Intelligence is seeking applicants for Professor (all ranks) in AI with Real-World Impact