Yakun is interested in integrating soil and agricultural sciences with advanced artificial intelligence and data-driven methods to support sustainable management of agricultural and natural resources. Her research includes soil spectral analysis for soil health assessment and dynamic soil surveys, big-data analytics and geospatial machine learning, and modeling soil weathering and erosion under climate change and human activities. She earned her Ph.D. in Soil Science with a minor in Statistics from the University of Wisconsin-Madison, an M.S. in Renewable Resources from McGill University, and a B.S. in Environmental Science from Sun Yat-sen University. Prior to joining UW-Madison, she was an Assistant Professor at Oregon State University. 

Malithi is interested in modeling and mapping soil properties and processes using remote sensing and machine learning. Her PhD research focuses on using soil MIR spectra to predict soil properties, soil health indicators, and soil classification across the US, and on developing a web-based portal to automate the modeling process. She received her B.S. in Environmental Conservation and Management from the University of Kelaniya in Sri Lanka and her M.S. in Environmental Hazards and Risks Management from Université Côte d’Azur (UCA) in France.

Mingxuan is interested in bridging soil carbon cycling with AI/ML applications. His PhD research integrates soil survey data, soil spectroscopy, remote sensing, AI/ML models, and process-based models to understand soil carbon dynamics under climate change and land management. He holds a B.S. in Geographical Information Science from Shandong Normal University and an M.S. in Agricultural Engineering and Information Technology from Zhejiang University in China.

Alex is interested in Pedology, Andisols, and biogeochemistry. Her PhD research investigates the use of mid-infrared spectroscopy in predicting andic soil properties and studying the formation and processes of Andisols. She is the co-coach of the UW-Madison Soil Judging team. She earned a B.S. in Environmental Science with a focus on Land & Soil from the University of Missouri-Columbia.

Elliott received his B.S. in Mathematics with a minor in Computer Science from Oregon State University. He works on developing machine learning models, transfer learning methods, and an R Shiny app.