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What are we doing?
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. |
Recent News
We are recruiting new Ph.D. students! Click here for more information.
2023-01-07
Dr. Zhang contributes to a new publication in EPSL as one of the corresponding authors. They focused on two Permian biocrises and combined the U-isotope records with LOSCAR model. Their results indicated that the response of ecosystem during the carbon cycle perturbation is sensitive to the carbon emission rates. Wang, W., Zhang, F., Zhang, S., Cui, Y., Zheng, Q., Zhang, Y., et al. (2023). Ecosystem responses of two Permian biocrises modulated by CO2 emission rates. Earth and Planetary Science Letters, 602, 117940. https://doi.org/10.1016/j.epsl.2022.117940 2022-11-30
Dr. Zhang hosts a workshop titled “Data Science Meets Carbon Cycle: Modeling rock weathering fluxes in the Gulf of Mexico region using machine learning”. This workshop was part of the Texas A&M Institute of Data Science Career Initiation Fellow Program to broaden knowledge of Data Science within Texas A&M and beyond The topics covered by the workshop include the R basics, data manipulation, data visualization, and machine learning in carbon cycle. More info can be found here: https://www.linkedin.com/feed/update/urn:li:activity:7004120752673157121/ |