Mission and Vision
Welcome to CACEE Lab @ Texas A&M University!
Our group broadly uses data-driven and model-driven approaches to quantify the patterns of element flux and isotope behavior involved in the global carbon and biogeochemical cycles, especially under periods of climatic perturbations.
Extensive data mining, data assimilation, large-scale spatial-temporal statistical analysis, and machine learning are frequently used in our research projects We hope geo-statistics and machine learning could reveal the intrinsic patterns of nature’s processes that are sometimes extremely difficult to be captured by classical physical process models. With that being said, in areas where data is extremely limited or data-driven approaches are not suitable, numerical modeling (e.g., modeling the global carbon cycle) also serves as a critical tool in our research.
We are recruiting new Ph.D. students! Click here for more information.
Dr. Zhang contributes to a new publication in PNAS. Rattanasriampaipong, R., Zhang, Y. G., Pearson, A., Hedlund, B. P., & Zhang, S. (2022). Archaeal lipids trace ecology and evolution of marine ammonia-oxidizing archaea. Proceedings of the National Academy of Sciences, 119(31), e2123193119. https://doi.org/10.1073/pnas.2123193119
Graduate student Bailey Armos participated in the GO-SHIP cruise from June 6, 2022 to July 18, 2022. Congratulations to her!