金建炳，南京信息工程大学教授，入选国家海外高层次人才计划。1990年2月出生，籍贯浙江绍兴。2013/2015本硕毕业于哈尔滨工业大学；2019博士毕业于荷兰代尔夫特理工大学（Delft University of Technology）应用数学系，导师Hai Xiang Lin, Arjo Segers, Arnold Heemink；2019年入职荷兰应用科学院（TNO），任职助理科学家；2020年加入南京信息工程大学 廖宏-大气化学与气候变化团队。

当前科研兴趣/方向致力于：

数据同化（模式与观测融合技术）理论及应用（沙尘）、人工智能大模型在大气化学/地球系统应用、大气成分卫星观测资料再处理，在Geoscientific Model Development, Journal of Advances in Modeling Earth Systems 等期刊发表论文30余篇。

科研合作与招生：

以地球科学相关的前沿科研为对象，通过数据同化、人工智能 (Transformer / Diffusion models)、数值模式、高性能计算等数据科学方法/工具，以开发创新系统/技术、发表高质量的论文为原则，探索有意义有趣的科研课题，完成有影响力的科研成果。

致力于采用国际顶尖高校的严谨学术培养模式来培养一流的科研人才，与每位学生都保持一对一的weekly meeting讨论学术进度。对于优秀的研究生，将提供极具竞争力的奖学金，进行出国短期访问。同时，对有志于继续深造读博的学生，将有机会被推荐到欧美名校。例如第一个硕士毕业生（2024届庞米杰）已获全额奖学金前往荷兰代尔夫特理工大学（QS世界排名47）应用数学系攻博。

发表一作及通信*论文：

(20) 吴星沂, 金建炳*, 夏霁, 方力, 廖宏. 中国甲烷浓度季节性变化与水稻种植关系研究. 大气科学, 2025. Accepted. 

(19) Mijie Pang, Jianbing Jin*, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han*.The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2. Geoscientific Model Development, 2025, Accepted. 

(18) Ji Xia, Yi Zhou, Li Fang, Yingfei Qi, Dehao Li, Hong Liao, and Jianbing Jin*. South Asia anthropogenic ammonia emission inversion through assimilating IASI observations. Atmospheric Chemistry and Physics. 2025, Accepted. 

(17) Li Fang, Jianbing Jin*, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao*. Observational operator for fair model evaluation with ground NO2 measurements. Geoscientific Model Development, 17, 8267-8282, 2024.

(16) Mijie Pang, Jianbing Jin*, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao. Valid time shifting Ensemble Kalman filter (VTS-EnKF) for dust storm forecasting. Geoscientific Model Development, 17, 8223-8242, 2024.

(15) Bufan Xu, Jianbing Jin*, Li Fang, Mijie Pang, Ji Xia, Baojie Li, Hong Liao*. A decadal atmospheric ammonia reanalysis product in China. Science of the Total Environment. 912, 169053, 2024.

(14) Li Fang, Jianbing Jin*, Arjo Segers, Hong Liao*, Ke Li, Bufan Xu, Wei Han, Mijie Pang, Hai Xiang Lin. A gridded air quality forecast through fusing site-available predictions from RFSML v1.0 and chemical transport model results from Geos-Chem v13.1.0 using the ensemble Kalman filter. Geoscientific Model Development, 16, 4867-4882, 2023.  文章(10): RFSML v1.0的进阶版本

(13) Mijie Pang, Jianbing Jin*, Arjo Segers, Huiya Jiang, Li Fang, Hai Xiang Lin, Hong Liao. Dust storm forecasting through coupling LOTOS-EUROS with localized ensemble Kalman filter. Atmospheric Environment, 119831, 2023.

(12) Jianbing Jin, Li Fang, Baojie Li, Hong Liao*, Ye Wang, Wei Han, Ke Li, Mijie Pang, Xingyi Wu, Hai Xiang Lin. 4DEnVar-based inversion system for ammonia emission estimation in China through assimilating IASI ammonia retrievals. Environmental Research Letters. acb835, 2023.

(11) Jianbing Jin, Bas Henzing*, Arjo Segers. How aerosol size matters in AOD assimilation and the optimization using the Ångström exponent. Atmospheric Chemistry and Physics. 23, 1641-1660, 2023.

(10) Li Fang, Jianbing Jin*, Arjo Segers, Hai Xiang Lin, Mijie Pang, Cong Xiao, Tuo Deng, and Hong Liao*. Development of a regional feature selection-based machine learning system (RFSML v1.0) for air quality forecasting over China. Geoscientific Model Development, 2022, 15, 7791–7807.

(9) Jianbing Jin, Mijie Pang, Arjo Segers, Wei Han, Li Fang, Baojie Li, Haochuan Feng, Hai Xiang Lin, and Hong Liao*. Inverse modeling of the 2021 spring super dust storms in East Asia. Atmospheric Chemistry and Physics, 2022, 22, 6393-6410.

(8) Cong Xiao, Jianbing Jin*. Model-reduced Adjoint-based Inversion using Deep Learning. Water Resources Research. 57, 2022.

(7) Jianbing Jin*; Arjo Segers; Hai Xiang Lin; Bas Henzing; Xiaohui Wang; Arnold Heemink; Hong Liao*. Position correction in dust storm forecasting using LOTOS-EUROS v2.1: grid-distorted data assimilation v1.0. Geoscientific Model Development. 14, 5607–5622, 2021.

(6) Min Xu; Jianbing Jin*; Guoqiang Wang; Arjo Segers; Hai Xiang Lin. Machine learning based bias correction for numerical chemical transport models. Atmospheric Environment, 2021, 248: 118022

(5) Jianbing Jin*; Arjo Segers; Hong Liao*; Arnold Heemink; Richard Kranenburg; Hai Xiang Lin. Source backtracking for dust storm emission inversion using an adjoint method: case study of Northeast China. Atmospheric Chemistry and Physics, 2020, 20: 15207-15225

(4) Jianbing Jin. Dust Storm Emission Inversion using Data Assimilation. Delft University of Technology, 2019. 专著

(3) Jianbing Jin*; Hai Xiang Lin; Arjo Segers; Yu Xie; Arnold Heemink. Machine learning for observation bias correction with application to dust storm data assimilation. Atmospheric Chemistry and Physics, 2019, 19(15): 10009-10026.

(2) Jianbing Jin*; Arjo Segers; Arnold Heemink; Mayumi Yoshida; Wei Han; Hai Xiang Lin. Dust Emission Inversion Using Himawari‐8 AODs Over East Asia: An Extreme Dust Event in May 2017. Journal of Advances in Modeling Earth Systems, 2019, 11(2): 446-467.

(1) Jianbing Jin*; Hai Xiang Lin; Arnold Heemink; Arjo Segers. Spatially varying parameter estimation for dust emissions using reduced-tangent-linearization 4DVar. Atmospheric Environment, 2018, 187: 358-373.

近期科研项目：

2024.12-2027.11 国家重点研发计划 政府间国际科技创新合作重点专项（2024YFE0113700），主持

2025.01-2028.12 国家自然科学基金面上项目（42475150），主持

2023.01-2025.12 国家重点研发计划 政府间国际科技创新合作重点专项（2022YFE0136100），参与

2022.07-2025.06 江苏省碳达峰碳中和科技创新专项资金项目(BK20220031)，参与

2022.01-2024.12 国家自然科学基金青年项目（42105109），主持

2021.07-2024.06 江苏省青年基金（BK20210664），主持