People

Kunxiaojia (Tammy) Yuan is an Assistant Professor in the Department of Earth and Atmospheric Sciences at the University of Houston. She previously worked as a Postdoc at Lawrence Berkeley National Lab (LBNL). She earned her Ph.D. in Geographic Information Science and B.Eng. in Remote Sensing from Wuhan University. During doctoral studies, she spent over three years at LBNL as an affiliate researcher, where she began the journey as an ecologist. She also worked at Google X as an AI Resident (intern), where she led the development of causal inference and AI algorithms for climate studies (resulting in a patent). Dr. Yuan’s research interests include land–atmosphere interactions, coastal resiliency, wildfire modeling, interpretable AI, causal inference, remote sensing, and Earth system modeling. Outside of work, she enjoys hiking scenic trails, experimenting in the kitchen, and spending quality time with family and friends.

Shuo Chen is a Ph.D. candidate in the Department of Earth, Atmospheric, and Planetary Sciences at Purdue University. In 2024, she was supervised by Dr. Yuan during the Lawrence Berkeley National Lab student internship program. During her internship, she quantified the CH4 temperature hysteresis across 25 eddy-covariance sites from FLUXNET-CH4 and compared it against the estimates from 42 CH4 emission models, including 13 biogeochemical models, 22 atmospheric inversion models, and 7 machine learning models.

Working with Dr. Yuan, she published the paper ‘Hysteretic temperature sensitivity in wetland CH4 emission modeling’ in Agricultural and Forest Meteorology, which is one of outcomes of the internship project.

Benjamin Yan is a master’s student in the Department of Computer Science at Stanford University. In 2024, he was supervised by Dr. Yuan during the Lawrence Berkeley National Lab student internship program. His research focuses on developing advanced AI models for predicting freshwater wetland CH₄ emissions and detecting the dominant drivers of CH4 dynamics across different wetland types.

His work resulted in an AGU poster entitled “Attention-Based Transformer Architectures for Multi-Site Global Wetland CH₄ Emissions Modeling and Identifying Key Ecosystem Drivers”.

Victor Chen is an undergraduate student in the Department of Computer Science at Stanford University. In 2024, he was supervised by Dr. Yuan during the Lawrence Berkeley National Lab student internship program.

During his internship, he designed and developed a spatiotemporal big data visualization web application. He also implemented and deployed a global wetland CH₄ emissions visualizer, featuring an interactive, rotatable 3D globe.