物理海洋学
 高乐,男,博士,副研究员,硕士生导师,海洋学报中英文版青年编委,数字海洋专委会委员。2014年毕业于中国科学院遥感与数字地球研究所。主要从事人工智能海洋学、卫星海洋海洋学研究,参与构建人工智能海洋学理论框架和海洋所海洋人工智能与大数据交叉中心,对于中小尺度现象及目标的形成过程、演变机制有深入理解,在深度学习模型中融合“图像纹理特征”、“注意力机制”和“物理机制引导的目标函数构造”等,构建的“知识-数据”耦合模型性能显著提升能力,相关成果入选2022 年度中国海洋与湖沼十大科技进展。在高水平期刊发表论文30余篇,授权发明专利5项。主持和参与国家重点研发计划、国家自然科学基金重大/面上/青年项目和山东省重大科技创新工程等多项项目。

一、研究领域 

AI Oceanography(人工智能海洋学),Ocean Remote Sensing(海洋遥感),Satellite Oceanography(卫星海洋学),Earth Observation(对地观测), Synthetic Aperture Radar (合成孔径雷达),Optical remote sensing(光学遥感), Big Earth Data (地球大数据), Machine Learning (机器学习), Physical Oceanography(物理海洋学)。

二、招生专业及方向

学术型:物理海洋学-海洋遥感与数值模拟、预测方法

专业型:环境工程-海洋环境工程;

欢迎有人工智能/计算机/海洋/遥感/物理/数学背景的同学报考!

三、研究室及联系方式      

海洋动力环境观测与预报重点实验室

海洋环流与波动重点实验室

邮箱:gaole@qdio.ac.cn

电话:0532-82898505

四、承担的主要科研项目

1)国家自然基金面上项目:知识与遥感大数据耦合的黄海绿潮漂移机制与精细化智能预报研究,起止时间:2024.01-2027.12.

2)中科院A类先导专项(课题):中小尺度海洋动力过程研究,2023.10-2026.09.

3)国家自然科学基金重大项目(子课题):印太交汇区物质能量汇聚中心海洋环境与生物过程的耦合作用和生态效益,起止时间:2021.01-2025.12

五、研究成果及奖励

12022 年度中国海洋与湖沼十大科技进展“人工智能技术在海洋学研究和气候模式发展方面取得突破性进展”,主要完成人:李晓峰、王凡、张荣华、朱聿超、高乐。

22018年和2022年年度考核优秀个人。

六、代表性论文及著作

[1] Le Gao, Yuan Guo, and Xiaofeng Li. Weekly green tide mapping in the Yellow Sea with deep learning: integrating optical and synthetic aperture radar ocean imagery,Earth System Science Data, 16, 4189–4207, 2024, https://doi.org/10.5194/essd-16-4189-2024.

[2] Le Gao., Xiaofeng Li, Fanzhou Kong, Rencheng Yu, Yuan Guo, Yibin Ren., 2022. AlgaeNet: A Deep Learning Framework to Detect Floating Green Algae from Optical and SAR Imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi: 10.1109/JSTARS.2022.3162387

[3]Gao L, Yang X, Qi J, Chen W. Glacier Mass Balance Pattern and Its Variation Mechanism in the West Kunlun Mountains in Tibetan Plateau. Remote Sensing. 2022; 14(11):2634. https://doi.org/10.3390/rs14112634

[4] Gao, L., Li, X., Guo, Y., Kong, F., Yu, R. (2023). Detection and Analysis of Marine Green Algae Based on Artificial Intelligence. In: Li, X., Wang, F. (eds) Artificial Intelligence Oceanography. Springer, Singapore. https://doi.org/10.1007/978-981-19-6375-9_13

[5]Y. Guo, L. Gao and X. Li, "A Deep Learning Model for Green Algae Detection on SAR Images," in IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-14, 2022, Art no. 4210914, doi: 10.1109/TGRS.2022.3215895.

[6]Lian, P., Gao, L*. Impacts of central-Pacific El Niño and physical drivers on eastern Pacific bigeye tuna. J. Ocean. Limnol. 42, 972–987 (2024). https://doi.org/10.1007/s00343-023-3051-3.

[7]Lian, P., Gao, L*. Contrasting physical mechanisms of yellowfin tuna fluctuations between the western and eastern Indian Ocean. J. Ocean. Limnol. 42, 960–971 (2024). https://doi.org/10.1007/s00343-023-2330-3.

[8]Y. Zhou, T. Ren, K. Chen, L. Gao* and X. Li*, "Graph-Based Memory Recall Recurrent Neural Network for Mid-Term Sea-Surface Height Anomaly Forecasting," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 6642-6657, 2024, doi: 10.1109/JSTARS.2024.3368766.

[9]Xiaofeng Li, Bin Liu, Gang Zheng, Yibin Ren, Shuangshang Zhang, Yingjie Liu, Le Gao, Yuhai Liu, Bin Zhang, Fan Wang, Deep-learning-based information mining from ocean remote-sensing imagery, National Science Review, Volume 7, Issue 10, October 2020, Pages 1584–1605, https://doi.org/10.1093/nsr/nwaa047.

[10]L. Gao and X. F. Li*, "A New Indicator for Representing Different Life Phases of Floating Green Tide on the Yellow Sea," 2023 Photonics & Electromagnetics Research Symposium (PIERS), Prague, Czech Republic, 2023, pp. 272-274, doi: 10.1109/PIERS59004.2023.10221260.

[11]Y. Liu, L. Gao*, Q. Liu and X. Li, "Dual-Branch Neural Network for Mesoscale Eddy Identification Based on Multi-Variables Remote Sensing Data,"2023 Photonics & Electromagnetics Research Symposium (PIERS), Prague, Czech Republic, 2023, pp. 275-279, doi: 10.1109/PIERS59004.2023.10221436.

[12]L. Gao, Y. Yang, M. J. Wang and X. F. Li, "A Deep-learning-based Frontal Detection in the China Sea," 2024 Photonics & Electromagnetics Research Symposium (PIERS), Chengdu, China, 2024, pp. 1-5, doi: 10.1109/PIERS62282.2024.10618295.

[13]Y. Liu, L. Gao, H. Wang, F. Jiang and X. Li, "Transfer Learning-driven Retrieval of Subsurface Temperature and Salinity for Mesoscale Eddies in the Oyashio Current," 2024 Photonics & Electromagnetics Research Symposium (PIERS), Chengdu, China, 2024, pp. 1-7, doi: 10.1109/PIERS62282.2024.10618644.

[14]L. Gao, X. Li, Y. Guo, J. Qi and B. Zhang, "Quantitative Evaluation of Algae Detection Based on Deep Neural Network Multi-Source Data Fusion," 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 7561-7563, doi: 10.1109/IGARSS47720.2021.9554235.

[15]Y. Guo, L. Gao and X. Li, "Distribution Characteristics of Green Algae in Yellow Sea Using an Deep Learning Automatic Detection Procedure," 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021, pp. 3499-3501, doi: 10.1109/IGARSS47720.2021.9554727.