教育经历

2011.8 – 2016.5 美国普渡大学，地球与大气科学，博士

2007.9 – 2011.7 北京大学，生态学，学士

工作经历

2024.9 – 至今  北京大学城市与环境学院、生态研究中心，长聘副教授、研究员

2024.5 – 2024.8  美国明尼苏达大学，长聘副教授

2019.1 – 2024.5  美国明尼苏达大学，助理教授

2018.7 – 2019.1  美国Atlas AI公司，Lead Scientist

2016.7 – 2018.6  美国斯坦福大学，博士后

欢迎对农业生态学、农业遥感、人工智能感兴趣的本科生、研究生和博士后加入研究组！

科学问题

如何在保障粮食安全的同时实现生态环境的可持续发展？

如何利用人工智能提升数值模型的预测精度和可迁移性？

研究工作以生态学理论为基础，综合运用机理模型、遥感观测、人工智能等大数据技术手段，研究农业生态系统对全球变化的响应机制，及其与其他环境系统之间的交互过程，为科学监测和管理农田生态系统的复杂过程提供理论依据和技术支撑，最终实现农业生产和生态环境保护的协同、可持续发展。相关论文发表在Science, 多个Nature子刊，Global Change Biology, Remote Sensing of Environment 等顶级期刊。曾获美国国家科学基金会职业生涯发展奖(NSF CAREER Award)。

全部论文

https://scholar.google.com/citations?user=DghN-sAAAAAJ&hl=en

近5年代表性论文

#: 通讯作者，下划线: 指导学生

[1] Yang, Y., Tilman, D.#, Jin, Z.#, Smith, P., Barrett, C.B.#, Zhu, Y.G., ... & Lobell, D.B.# (2024). Climate change exacerbates the environmental impacts of agriculture. Science, 385(6713), eadn3747.

[2] Zhou, J., Zhu, P., Kluger, D. M., Lobell, D. B., & Jin, Z.# (2024). Changes in the Yield Effect of the Preceding Crop in the US Corn Belt Under a Warming Climate. Global Change Biology, 30(11), e17556.

[3] Liu, L., Zhou, W., Guan, K.#, Peng, B., Xu, S., Tang, J., Zhu, Q., Till, J., Jia, X., Jiang, C., Wang, S., ..., Kumar, V. & Jin, Z.# (2024) Knowledge-guided machine learning can improve carbon cycle quantification in agroecosystems. Nature Communications, 15, 357.

[4] Yang, Q., Liu, L., Zhou, J., Ghosh, R., Peng, B., Guan, K., Tang, J., Zhou, W., Kumar, V., & Jin, Z.# (2023) A flexible and efficient knowledge-guided machine learning data assimilation (KGML-DA) framework for agroecosystem prediction in the US Midwest. Remote Sensing of Environment, 299, 113880.

[5] Yang, Y., Jin, Z.#, Muller, N.D.#, Driscoll, A., Hernandez, R.R., Grodsky, S., Sloat, L., …, Zhu, Y.G., & Lobell, D.B. (2023) Sustainable irrigation and climate feedbacks. Nature Food, 4, 654–663.

[6] Yin, L., Ghosh, R., Lin, C., Hale, D., Weigl, C., Obrowski, J., Zhou, J., Till, J., Jia, X., You, N., Mao, T., Kumar, V., & Jin, Z.# (2023) Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin. Remote Sensing of Environment, 295, 113695.

[7] Liu, L., Xu, S., Tang, J., Guan, K., Griffis, T.J., Erickson, M.D., Frie, A.L., Jia, X., Kim, T., Miller, L.T., Peng, B., ..., Kumar, V., & Jin, Z.# (2022) KGML-ag: A Modeling Framework of Knowledge- Guided Machine Learning to Simulate Agroecosystems: A Case Study of Estimating N2O Emission using Data from Mesocosm Experiments. Geoscientific Model Development, 15, 2839–2858.

[8] Lin, C., Zhong, L., Song, X., Dong, J., Lobell, D.B., & Jin, Z.# (2022) Early- and in-season crop type mapping without current-year ground truth: Generating labels from historical information via a topology-based approach. Remote Sensing of Environment, 274, 112994.

[9] Zhu, P., Kim, T., Jin, Z.#, Lin, C., Wang, X., Ciais, P., Mueller, N.D., AghaKouchak, A., Huang, J., Mulla, D., & Makowski, D. (2022) The critical benefits of snowpack insulation and snowmelt for winter wheat productivity. Nature Climate Change, 12, 485–490.

[10] Benami, E.#, Jin, Z.#, Carter, M., Lobell, D.B., Kenduiywo, B., Ghosh, A., & Hijmans, R. (2021) Uniting remote sensing, crop modelling and economics for agricultural risk management. Nature Review Earth & Environment, 2, 140-159.