The main research interests of my lab are:
- To integrate proximal and remote sensing and process-based models to improve the fundamental understanding of water, carbon, nutrient, and energy cycles under climate change and human disturbance
- To combine soil sensing technologies, big data analytics, and machine learning to monitor, model, and map water, carbon, nutrient, and energy fluxes across scales for sustainable natural resources management
Please send me an email if you are interested in joining my lab to explore the ideas in any of these topics as an undergraduate/graduate research assistant or postdoctoral researcher.
Currently, I work on several projects to use proximal and remote sensing, process-based models, machine learning, and big data analytics for soil moisture and water, carbon, and nutrient fluxes modeling, mapping, and management in Wisconsin, across the US, and globally.
15. 2023–2026: ML-HRSM: Machine learning high-resolution soil moisture product development in support of USDA NASS Crop Monitoring. USDA National Institute of Food and Agriculture. Principal Investigator.
14. 2023–2027: Integrating Enviromics, Genomics, and Machine Learning for Precision Breeding of Resilient Beef Cattle. USDA National Institute of Food and Agriculture. Co-Principal Investigator.
13. 2023–2024: Dairy Water Quality Research Station: A campus-wide long-term lysimeter network in Wisconsin. University of Wisconsin-Madison Dairy Innovation Hub. Co-Principal Investigator.
12. 2022–2026: SitS: Leveraging spectroscopy and in situ soil sensing for the prediction of keystone soil microbial functions. National Science Foundation. Co-Principal Investigator.
11. 2022–2024: Unraveling environmental and management effects on soil greenhouse gas emissions at fine spatial-temporal scales: integrating cost-effective sensor networks and process models. USDA Hatch Multi-State Research Formula Fund. Principal Investigator.
10. 2022–2024: Combining affordable multi-functional, multi-depth soil sensors and process models for real-time nitrate leaching, monitoring and management. USDA National Institute of Food and Agriculture. Principal Investigator.
9. 2021–2022: In situ real-time soil nitrate leaching sensing for sustainable dairy production. University of Wisconsin-Madison Dairy Innovation Hub. Principal Investigator.
8. 2021–2022: Co-Principal Investigator: A campus-wide high-throughput mid-infrared spectroscopy platform for rapid assessment of soils, feed, and dairy products. University of Wisconsin-Madison Dairy Innovation Hub.
7. 2021–2022: Principal Investigator: Data-driven groundwater depth and risk forecasting in Central Sands region of Wisconsin sustainable management. University of Wisconsin-Madison Water Resources Institute.
6. 2021–2022: Principal Investigator: Irrigation management using nationwide soil moisture maps derived from big data and machine learning. University of Wisconsin-Madison Office of the Vice Chancellor for Research and Graduate Education.
5. 2021–2021: Principal Investigator: Soil moisture monitoring at the Hancock Agricultural Research Station using novel sensor technologies. College of Agricultural and Life Sciences Summer Internship, University of Wisconsin-Madison.
4. 2020–2022: Principal Investigator: Rapid monitoring and mapping soil health across scales using mid-infrared and visible near-infrared spectra and geospatial machine learning. University of Wisconsin-Madison Office of the Vice Chancellor for Research and Graduate Education.
3. 2021–2022: Co-Principal Investigator: Nitrogen availability of fall applied manure in a sustainably intensive silage system. Wisconsin Department of Trade & Consumer Protection.
2. 2020–2022: Co-Principal Investigator: Geophysics-informed transport and shallow bedrock topography in Northeast and Southcentral Counties in Wisconsin. State of Wisconsin Department of Natural Resources Groundwater Research and Monitoring Program.
1. 2019–2021: Principal Investigator: Mapping surface soil water dynamics at fine spatial and temporal resolutions across the U.S. Climate Reference Network using Sentinel-1 and ancillary data. United States Department of Agriculture, Hatch Multi-State Research Formula Fund.