Kai Zhu has a strong interest in global change biology, ecological modeling, and environmental data science. He enjoys exploring the intersection between ecological theory and advanced tools in statistics and computer science, including Bayesian inference and machine learning. Currently, Kai’s research is focused on studying plant and soil responses to environmental changes within coupled natural and human systems. His work encompasses meter-scale experiments to global-scale analyses. In recent projects, Kai has quantified the impacts of climate change on forest geographic distribution and growth in North America, synthesized a multi-factor global change experiment in California grassland, investigated soil fungi and tree mutualisms across geographical gradients in the United States, and detected land surface phenology change in the Northern Hemisphere.
Research AreasAI; ML and Statistical Inference
Data Processing; Integration; Mining and Visualization
Energy; Environment and Natural Resources