College of Agriculture & Natural Resources Department of Fisheries and Wildlife

Xin is an interdisciplinary researcher who studies freshwater ecosystems using machine learning, remote sensing, and process-based modeling. Broadly, his research interests include harmful algal blooms, lake and reservoir dynamics, physics-informed deep learning, and coupled human and natural systems. Xin holds a B.S. in Marine Sciences from China University of Geosciences (Beijing) and master's degrees in Earth and Environmental Engineering from Columbia University and in Computer and Information Technology from the University of Pennsylvania. He received his Ph.D. in Geography, Environment, and Spatial Sciences from Michigan State University, where his doctoral research developed process-guided ensemble deep learning models for lake water temperature prediction.

As a postdoctoral scholar at the Center for Systems Integration and Sustainability, Xin works with Dr. Jianguo "Jack" Liu and is supported by a Cooperative Institute for Great Lakes Research (CIGLR) Postdoctoral Fellowship. His mentoring team spans Michigan State University, CIGLR at the University of Michigan, and NOAA's Great Lakes Environmental Research Laboratory (GLERL). Xin's current research applies the metacoupling framework to harmful algal blooms in Lake Erie, examining how stressors within and beyond the watershed interact to drive extreme bloom events. Overall, his work aims to understand and predict how freshwater systems respond to environmental change