8th Training Course (Hybrid Virtual + in Person) on

New Advances in Land Carbon Cycle Modeling

June 2-13, 2025

(Eastern Daylight Time (EDT), with weekend on June 7 and 8 off)

Who should attend?

Graduate students, post-docs and young scientists who want to learn modeling, data assimilation, machine learning, deep learning, and ecological forecasting

Modelers who want to gain simplicity in structure, computational efficiency for your models

Empiricists who want to use your data to constrain models toward ecological forecasting

What are you going to learn?

New theory on land carbon storage dynamics

Matrix approach to land carbon, nitrogen, and phosphorus modeling

Data assimilation system with both flux- and pool-based observations

Deep learning and machine learning to enhance process-based research

Ecological forecasting

Who is going to teach?

Lecturers and instructors

Ye Chen, Northern Arizona U, USA

Julia Green, U of Arizona, USA

Toby Hocking, Northern Arizona U, USA

Forrest Hoffman, ORNL, USA

Enqing Hou, South China Bot. Garden, China

Xin Huang, NCAR, USA

Yuanyuan Huang, IGSNRR, CAS, China

Jiang Jiang, Nanjing Forestry U, China

Lifen Jiang, Cornell U, USA

Junyi Liang, China Agricultural U, China

Xingjie Lu, Sun Yat-sen U, China

Yiqi Luo, Cornell U, USA

Shuang Ma, UCLA/JPL, USA

Daniel Ricciuto, ORNL, USA

Zheng Shi, U of Oklahoma, USA

Carlos Sierra, MPI-BGC, Germany

Ben Smith, Western Sydney U, Australia

Feng Tao, Cornell U, USA

Ying Wang, U of Oklahoma, USA

Matthew Williams, Edinburg U, UK

Jianyang Xia, East China Normal U, China

Yao Zhang, Peking U, China

Jian Zhou, Cornell U, USA

Yu Zhou, ETH Zurich, Switzerland

Invited speakers

Bettina Gier, University of Bremen, Germany

Yuanyuan Huang, CAS, China

Jiameng Lai, Cornell University, USA

Yanlan Liu, Ohio State University, USA

Shushi Peng, Peking University, China

Melinda Smith, Colorado State University, USA

Pete Smith, Aberdeen University, UK

Cesar Terrer, MIT, USA

Ning Zeng, University of Maryland, USA

What is your commitment?

You will go through 10 units of online training, one unit per day. For each unit, you will read three chapters or other training materials, listen to corresponding pre-recorded lectures, take quizzes, do exercises according to one pre-recorded instruction, and attend one synchronized virtual meeting.

You will get feedback from instructors on your answers to quizzes and exercises.