ZHANG Wei, 张巍

Professor, post-graduate Supervisor
College of Computer Science and Technology
Faculty of Information Science and Engineering
Ocean Unversity of China


Short Bio

🧔‍ I am currently a Professor in Institute of Aritificial Intelligence, Ocean University of China. I am also member of the State Key Laboratory of Physical Oceanography (POL), Ocean University of China; member of the OUC-China Mobile Shandong-Qingdao Guoshi Group Ocean AI Joint Laboratory.

🏛️ I received my B.S. and MSc degrees from the College of Sciences, Northeastern University. I received my Ph. D. degree from the School of Computer Science and Technology, University of Science and Technology of China. Then I do a postdoctoral research joint with the iflytek.com and the School of Information Science and Technology, University of Science and Technology of China. Also, I was a one-year academic visitor in the Centre for Speech Technology Research, and the School of Informatics, University of Endiburgh.

🎯 I focus on the cutting-edge research fields of Artificial Intelligent Meteorology, Aritificial Intelligent Oceanography and Domain Large Language Model (domain LLM). I have published over 50 academic papers in leading journals and conferences, such as ISPRS J PHOTOGRAMM, IEEE TGRS, IEEE JSTARS, IEEE GRSL, JGR-Atmospheres, Computer Speech & Language, Interspeech, IEEE bigdata, etc.

🏅 I am the founder and co-leader of the Langyapo[琅琊泊] AI Meteorology and Marine Environment Forecasting Model (Langyapo-AIMM@OUC) at Ocean University of China. Langyapo-AIMM@OUC was developed on the Qingdao Artificial Intelligence Computing Center (AICC) platform—a 100-petaflop computing environment featuring Ascend hardware and the MindSpore framework. Langyapo-AIMM has officially been granted Huawei Technical Certification (No. E202212825).

✉️ Contact me via weizhang [at] ouc.edu.cn .

[Updated on Oct. 3, 2025]



Selected Publications [ ORCID ][ Google Scholar ]

  1. W Zhang*, X Zhang, J Dong, X Song, R Pang, CIDM: A comprehensive inpainting diffusion model for missing weather radar data with knowledge guidance, ISPRS Journal of Photogrammetry and Remote Sensing 221, 299-309, 2025.
    (SCI-1, TOP) [PDF] [Code@Github]

  2. W Zhang*, Y Wu, K Fan, X Song, R Pang, B Guoan, A Multi-Scale Fusion Deep Learning Approach for Wind Field Retrieval Based on Geostationary Satellite Imagery, Remote Sensing, 17 (4), 610, 2025.
    (SCI-2 at the time of publication) [PDF]

  3. W Zhang*, X Zhang, Z Jin*, Y Wen, J Liu, Inpainting radar missing data via denoising iterative restoration, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17: 10715-10725, 2024
    (SCI-2, TOP at the time of publication) [PDF]

  4. W Zhang, Y Sun, Y Wu, J Dong*, X Song*, Z Gao, R Pang, B Guoan, A deep-learning real-time bias correction method for significant wave height forecasts in the Western North Pacific, Ocean Modelling, 187, 102289, 2024.
    (SCI-2 at the time of publication) [PDF]

  5. W Zhang, H Chen, L Han*, R Zhang, Y Ge, Pixel-CRN: A new machine learning approach for convective storm nowcasting, IEEE Transactions on Geoscience and Remote Sensing 61, 1-12, 2023.
    (SCI-1, Top at the time of publication and CCF-b) [PDF]

  6. W Zhang, Y Jiang, J Dong*, X Song*, R Pang, B Guoan, H Yu, A deep learning method for real-time bias correction of wind field forecasts in the Western North Pacific, Atmospheric Research 284, 106586, 2023.
    (SCI-1, Top at the time of publication) [PDF]

  7. W Zhang, Y Jiang, X Song, B Guoan, R Pang, A Multi-objective Residual TrajGRU Model for Wind Field Forecasting, 2022 IEEE International Conference on Big Data, 4893-4900.
    (CCF-c) [PDF]

  8. L Han, J Zhang, H Chen, W Zhang*, S Yao, Toward the predictability of a radar-based nowcasting system for different precipitation systems, IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2023.
    (SCI-2 at the time of publication) [PDF]

  9. L Han, H Liang, H Chen, W Zhang*, Y Ge, Convective precipitation nowcasting using U-Net model, IEEE Transactions on Geoscience and Remote Sensing 60, 1-8, 2021.
    (SCI-1, TOP at the time of publication and CCF-b) [PDF]

  10. W Zhang, L Han, J Sun, H Guo, J Dai, Application of multi-channel 3D-cube successive convolution network for convective storm nowcasting, 2019 IEEE international conference on big data, 1705-1710.
    (CCF-c) [PDF]

  11. L Han, J Sun, W Zhang*, Convolutional neural network for convective storm nowcasting using 3-D Doppler weather radar data, IEEE Transactions on Geoscience and Remote Sensing 58 (2), 1487-1495, 2019.
    (SCI-1, TOP at the time of publication and CCF-b) [PDF]

  12. L Han, J Sun*, W Zhang*, Y Xiu, H Feng, Y Lin, A machine learning nowcasting method based on real‐time reanalysis data, Journal of Geophysical Research: Atmospheres 122 (7), 4038-4051, 2017.
    (SCI-2, TOP at the time of publication) [PDF]

  13. W Zhang*, RAJ Clark*, Y Wang, W Li, Unsupervised language identification based on Latent Dirichlet Allocation, Computer Speech & Language 39, 47-66, 2016.
    (SCI-3, CCF-c) [PDF]

  14. H Lu, W Zhang, X Shao, Q Zhou, W Lei, H Zhou, AP Breen, Pruning redundant synthesis units based on static and delta unit appearance frequency, INTERSPEECH, 269-273, 2015.
    (CCF-c) [PDF]

  15. W Zhang, RAJ Clark, Y Wang, Unsupervised language filtering using the latent dirichlet allocation, INTERSPEECH, 1268-1272, 2014.
    (CCF-c) [PDF]


Main Fundings

Courses Taught

Professional Service