师资队伍

专任教师

刘厂简介

发布人:时间:2024-08-22浏览:

证件照1

刘厂,工学博士,教授,2013年毕业于哈尔滨工程大学,获工学博士学位。美国威斯康星大学/普林斯顿大学-NOAA/GFDL访问学者、青岛市西海岸新区创新领军人才;现任青岛市海洋环境智能预报与应用技术创新中心主任、中国海洋发展学会应用海洋学分会理事。

长期从事人工智能海洋学、海洋信息智能应用领域的关键技术研究、装备研制与产业化工作,作为负责人主持省重点研发计划“数字经济”重大专项1项、重大科技专项课题1项、国家重点研发计划子课题2项、重点装备研制项目多项,科研经费累计数千万元;主持研制的多型海洋环境保障装备和技术平台已在海洋领域得到推广应用;在国内外核心期刊上发表论文30余篇;申请国家发明专利30余项,授权20项,成果转化3项;出版教材及著作3部。荣获黑龙江省技术发明奖一等奖1项、海洋科学技术进步奖二等奖1项、吴文俊人工智能科学技术进步奖二等奖1项、中国产学研合作创新与促进奖创新成果奖优秀奖1项。

主要科研方向:

1.人工智能海洋学:海洋智能分析预报、气象智能分析预报、数值预报产品智能订正;

2.海洋环境智能应用:气象海洋多维可视化、多源数据融合处理、海洋大数据分析挖掘、海洋环境特征诊断识别、海洋环境辅助决策支持;

3.海洋环境保障解决方案:海上有人/无人平台海洋环境综合保障解决方案、飞行器平台海洋环境综合保障解决方案、岸基海洋环境综合保障解决方案。


拟招生专业:海洋信息工程、水声工程、海洋科学、大气科学、地理信息系统、电子信息、自动化、计算机、人工智能等相关专业。

联系方式:liuchangheu@163.com

Dr. Chang LIU

Professor, Shandong University of Science and Technology

Education and Work Experience

2008-2013, Ph.D., Harbin Engineering University

2010-2018, Lecturer, Harbin Engineering University

2018-2024, Associated Professor, Harbin Engineering University

2024-Present, Professor, Shandong University of Science and Technology

Research Interest

Artificial Intelligence Oceanography

Intelligent Application of Marine information

Selected Publications

1. Ye, Y., Gao, F., Cheng, W., Liu, C*., Zhang, S., & Wang, S, 2024: Improved Precipitation Nowcasting through a Deep Learning Model Based on Three-Dimensional Cloud Structures. IEEE Transactions on Geoscience and Remote Sensing, 62: 1-14.

2. Feng Gao, Qilong Li, Liming Zhou, Chang Liu* 2024, Numerical Wind Speed Correction Method based on Multiple Factors. IEEE International Conference on Advanced Robotics and Mechatronics.

3. Cao, Xiaohu, Chang Liu, Shaoqing Zhang, and Feng Gao, 2024: A Method for Predicting High-Resolution 3D Variations in Temperature and Salinity Fields Using Multi-Source Ocean Data. Journal of Marine Science and Engineering, 12(8): 1396.

4. Gao, Feng, Sen Li, Yuankang Ye, and Chang Liu, 2024: PMSTD-Net: A Neural Prediction Network for Perceiving Multi-Scale Spatiotemporal Dynamics. Sensors, 24(14): 4467.

5. Xie, B., Dong, J., Liu, C. et al, 2024: MEHGNet: a multi-feature extraction and high-resolution generative network for satellite cloud image sequence prediction. Earth Sci Inform, 1-18.

6. Mao, Kai, Chang Liu*, Shaoqing Zhang, and Feng Gao, 2023: Reconstructing Ocean Subsurface Temperature and Salinity from Sea Surface Information Based on Dual Path Convolutional Neural Networks. Journal of Marine Science and Engineering, 11(5): 1030.

7. Jiang Y, Gao F, Zhang S, Cheng W, Liu C*, Wang S, 2023: MCSPF-Net: A Precipitation Forecasting Method Using Multi-Channel Cloud Observations of FY-4A Satellite by 3D Convolution Neural Network. Remote Sensing, 15(18): 4536.

8. Dong, J., Wu, K., Liu, C., Mei, X., & Wang, W, 2023: Discriminative analysis dictionary learning with adaptively ordinal locality preserving. Neural Networks, 165: 298-309.

9. Jiang, Yuhang, Wei Cheng, Feng Gao, Shaoqing Zhang, Chang Liu, and Jingzhe Sun, 2023: CSIP-Net: Convolutional Satellite Image Prediction Network for Meteorological Satellite Infrared Observation Imaging. Atmosphere, 14(1): 25.

10. Ye, Y., Gao, F., Cheng, W., Liu, C., & Zhang, S, 2022: Msstnet: A multi-scale spatiotemporal prediction neural network for precipitation nowcasting. Remote Sensing, 15(1): 137.

11. Mao, K., Gao, F., Zhang, S., & Liu, C, 2022: An Information Spatial-Temporal Extension Algorithm for Shipborne Predictions Based on Deep Neural Networks with Remote Sensing Observations—Part I: Ocean Temperature. Remote Sensing, 14(8): 1791.

12. Mao, K., Gao, F., Zhang, S., & Liu, C, 2022: An Initial Field Intelligent Correcting Algorithm for Numerical Forecasting Based on Artificial Neural Networks under the Conditions of Limited Observations: Part I—Focusing on Ocean Temperature. Journal of Marine Science and Engineering, 10(3): 311.

13. Jiang, Yuhang, Wei Cheng, Feng Gao, Shaoqing Zhang, Shudong Wang, Chang Liu, and Juanjuan Liu, 2022: A Cloud Classification Method Based on a Convolutional Neural Network for FY-4A Satellites. Remote Sensing, 14(10): 2314.

14. Dong, J., Yang, L., Liu, C., Cheng, W., & Wang, W, 2022: Support vector machine embedding discriminative dictionary pair learning for pattern classification. Neural Networks, 155: 498-511.

15. Dong, J., Yang, L., Liu, C., Luo, X., & Guan, J, 2022: Distributed analysis dictionary learning using a diffusion strategy. Neural Processing Letters, 1-15.

16. Liu, C., Liu, R., & Gao, F, 2021: Real-time AUV path planning algorithm in complex marine environment. In 2021 IEEE International Conference on Unmanned Systems (ICUS) , 110-115.


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