Rate My Professor Amy Kaleita

Amy Kaleita is the Larry and Bunita Buss Department Chair and Professor of Agricultural and Biosystems Engineering at Iowa State University of Science and Technology. She earned a B.S. in 1997 from Pennsylvania State University, an M.S. in 1999, and a Ph.D. in 2003 from the University of Illinois. Kaleita was appointed department chair in 2021 and named to the inaugural Larry and Bunita Buss endowed chair position in 2025. Her research program focuses on information technology for precision conservation, with primary interests in remote sensing, crop and hydrologic modeling, precision farming, and advanced analytical methods for understanding spatiotemporally variable soil and hydrologic properties. She contributes to initiatives such as the Iowa Nutrient Research Center projects on reducing phosphorus export through farmed pothole surface inlets with P filters and blind inlets.

In her teaching role, Kaleita delivers courses on soil and water conservation management and engineering, as well as analytical techniques for data and modeling. She initiated online instructional resources in 2007 in preparation for maternity leave and later supported her department's transition to remote learning during the COVID-19 pandemic. Kaleita has received numerous accolades for her educational and leadership contributions, including the James R. and Karen A. Gilley Academic Leadership Award from the American Society of Agricultural and Biological Engineers in 2025, the Massey-Fergusson Educational Gold Medal in 2023, Fellow of ASABE in 2020, the Gilbreth Award for Young Engineers from the National Academy of Engineering in 2013, the Superior Engineering Teacher Award from Iowa State University College of Engineering in 2010, the A. W. Farrall Young Educator Award from ASABE in 2008, and the Award for Early Achievement in Teaching from Iowa State University in 2006. Key publications include "Methodology for the use of DSSAT models for precision agriculture decision support" (Thorp et al., 2008), "Relationship between soil moisture content and soil surface reflectance" (Kaleita et al., 2005), "Development of an android app to estimate chlorophyll content of corn leaves based on contact imaging" (Vesali et al., 2015), and "Exploring multiscale object-based convolutional neural network (multi-OCNN) for remote sensing image classification at high spatial resolution" (Martins et al., 2020). Her scholarly impact supports the department's top-ranked graduate program in agricultural and biosystems engineering.