Feng Tao 陶鳳

Postdoc at Cornell University, PhD from Tsinghua University, BSc from Sun Yat-sen University

prof_pic.jpg

305 Rice Hall

Cornell University

Ithaca, NY 14853

I am currently a postdoc at Department of Ecology & Evolutionary Biology at Cornell University.

My research interests are to understand the global soil carbon cycle (both organic and inorganic part) and its response to climate change.

In collaboration with my brilliant colleagues, we have developed a “PROcess-guided deep learning and DAa driven modeling (PRODA)” approach that integrates big soil carbon data, process-based models, and data assimilation and machine learning techniques to gain emerging understanding of global soil organic carbon storage. You can check our methodology paper and science paper.

My postdoc project focuses on enhanced rock weathering to promote soil inorganic carbon as a scalable carbon dioxide removal method.

Selected publications

2024

  1. Convergence in simulating global soil organic carbon by structurally different models after data assimilation
    Feng Tao, Benjamin Z. Houlton, Yuanyuan Huang, and 7 more authors
    2024
  2. Size, distribution, and vulnerability of the global soil inorganic carbon
    Yuanyuan Huang, Xiaodong Song, Ying-Ping Wang, and 24 more authors
    2024

2023

  1. Microbial carbon use efficiency promotes global soil carbon storage
    Feng Tao, Yuanyuan Huang, Bruce A. Hungate, and 30 more authors
    2023

2022

  1. PROcess-guided deep learning and DAta-driven modelling (PRODA)
    Feng Tao, and Yiqi Luo
    Land carbon cycle modeling: Matrix approach, data assimilation, and ecological forecasting. Taylor and Francis, 2022

2020

  1. Deep learning optimizes data-driven representation of soil organic carbon in Earth system model over the conterminous United States
    Feng Tao, Zhenghu Zhou, Yuanyuan Huang, and 8 more authors
    Frontiers in Big Data, 2020