一、研究领域
人工智能海洋学
二、招生专业及方向
物理海洋学,海洋波动与环境预测方向和海洋遥感与数值模拟、预测方法
三、研究室及联系方式
海洋环流与波动重点实验室,联系方式:zhangxd@qdio.ac.cn、13156872263
四、承担的主要科研项目
1. 国家重点研发计划,北斗精准导航与高分辨率遥感集成技术及区域综合示范应用,子课题1项,在研,主持。
2. 崂山实验室科技创新项目,基于人工智能的孪生海洋关键技术与应用示范,子课题1项,在研,主持。
3. 中国科学院先导专项(A类),中小尺度海洋动力过程研究,子课题1项,在研,主持。
4. 国家自然科学基金项目,基于海面高度场和流速同步遥感观测的内波参数反演方法研究,已结题,主持。
五、研究成果及奖励
1. “优秀博士后”激励计划出站奖励, 中国科学院海洋研究所, 2021年度
2. 中国科学院海洋研究所重大成果奖励,2022年度
3. 中国科学院海洋研究所汇泉学者,2022年度
六、代表性论文及著作
1. Zhang, X., & Li, X.* (2024). Constructing a 22-Year Internal Wave Dataset for the Northern South China Sea: Spatiotemporal Analysis Using MODIS Imagery and Deep Learning. Earth System Science Data.(SCI, Q1, Top)
2. Zhuang, C., Li, X., Shen, D., & Zhang, X.* (2024). Internal solitary wave in the Lombok Strait: Satellite-observed spatiotemporal characteristics and their propagations modulated by the Indonesian Throughflow. Ocean Modelling, 190.(SCI, Q1)
3. Zhang, X., & Li, X.* (2024). Unveiling three-dimensional sea surface signatures caused by internal solitary waves: insights from the surface water ocean topography mission. Journal of Oceanology and Limnology, 42(3), 709-714. (SCI, 封面文章)
4. Zhang, X. & Li, X.* (2022). Satellite data-driven and knowledge-informed machine learning model for estimating global internal solitary wave speed. Remote Sensing of Environment, 283, 113328.(SCI, Q1, Top, IF=13.6)
5. Zhang, X., Wang, H., Wang, S., Liu, Y., Yu, W., Wang, J., ... & Li, X. (2022). Oceanic internal wave amplitude retrieval from satellite images based on a data-driven transfer learning model. Remote Sensing of Environment, 272, 112940. (SCI, Q1, Top)
6. Zhang, X., & Li, X. (2022). Oceanic internal waves generated by the Tongan volcano eruption [J]. Acta Oceanologica Sinica. (SCI, 封面文章)
7. Zhang, X., Li, X., & Zheng, Q. (2021). A machine-learning model for forecasting internal wave propagation in the Andaman Sea. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3095-3106. (SCI, Q1, Top)
8. Zhang, X., & Li, X. (2020). Combination of satellite observations and machine learning method for internal wave forecast in the Sulu and Celebes seas. IEEE Transactions on Geoscience and Remote Sensing, 59(4), 2822-2832.(SCI, Q1, Top, 封面文章)
9. 《Artificial Intelligence Oceanology》,主编:李晓峰,王凡。负责撰写Chapter 4: Satellite Data-Driven Internal Solitary Wave Forecast Based on Machine Learning Techniques