博士后研究员Postdoctoral Researcher · 浙江大学Zhejiang University
关于我About Me
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面向地球物理的机器学习、DAS 与地震基础模型Machine learning for geophysics, DAS, and seismic foundation models
我目前在浙江大学从事博士后研究，与李伟昌教授合作。我于 2025 年在中国科学技术大学获得地球物理学博士学位，师从伍新明教授；此前于 2020 年在中国科大获得地球物理学学士学位。I am currently a postdoctoral researcher at Zhejiang University, working with Prof. Weichang Li. I received my PhD in Geophysics from the University of Science and Technology of China in 2025 under the supervision of Prof. Xinming Wu, after earning my BS in Geophysics from USTC in 2020.
我目前是浙江大学博士后研究员，研究方向交叉于机器学习与地球物理，关注地震数据处理、解释、反演、DAS 数据分析、地球物理基础模型和高效三维地球物理软件。I am a postdoctoral researcher at Zhejiang University. My research lies at the intersection of machine learning and geophysics, including seismic processing, interpretation, inversion, DAS data analysis, geophysical foundation models, and efficient 3D geophysical software.
01地球科学人工智能与基础模型AI and Foundation Models for Geoscience
02地震数据处理、解释与反演Seismic Processing, Interpretation, and Inversion
03DAS、光纤感知、多传感器融合与地球物理监测DAS, Fiber-Optic Sensing, Multi-Sensor Fusion, and Geophysical Monitoring
04地球科学智能基础设施与开源软件Geoscience AI Infrastructure and Open-Source Software
02
最新动态Updates
新闻News
Jintao 获得国家自然科学基金委员会（NSFC）青年科学基金项目（C类）资助。Jintao received funding from the National Natural Science Foundation of China (NSFC) through the Young Scientists Fund (Category C).
Yuting Wang 关于地震反射系数估计的论文被 Geophysical Journal International 接收，我担任通讯作者。祝贺 Yuting！Yuting Wang's paper on seismic reflectivity estimation was accepted by Geophysical Journal International. I served as a corresponding author. Congratulations to Yuting!
先后获得中国博士后科学基金第 79 批面上资助（2026M790497）和国家资助博士后研究人员计划 B 档资助（GZB20260111）。I received support from the China Postdoctoral Science Foundation 79th General Program (2026M790497) and the Postdoctoral Fellowship Program (Grade B) of China Postdoctoral Science Foundation (GZB20260111).
高保真地震超分辨率论文被 IEEE Transactions on Image Processing 接收。Our high-fidelity seismic super-resolution paper was accepted by IEEE Transactions on Image Processing.
大规模三维数据全体积推理工作被 Bioengineer.org 和 GeneOnline 报道。Our work on full-volume inference for large-scale 3D data was featured by Bioengineer.org and GeneOnline.
内存高效三维推理论文被 Nature Portfolio 旗下 Communications Engineering 接收。Our memory-efficient 3D inference paper was accepted by Communications Engineering, part of Nature Portfolio.
加入浙江大学开展博士后研究。I joined Zhejiang University as a postdoctoral researcher.
在中国科学技术大学通过地球物理学博士学位答辩。I successfully defended my PhD in Geophysics at the University of Science and Technology of China.
Jintao Li, Xinming Wu, Xianwen Zhang, Xin Du, Xiaoming Sun, Bao Deng, and Guangyu Wang
"High-Fidelity Seismic Super-Resolution Using Prior-Informed Deep Learning With 3D Awareness." IEEE Transactions on Image Processing (IEEE TIP) 35 (2026): 2152-2166.
Li, Jintao, Xinming Wu, Xianwen Zhang, Xin Du, Xiaoming Sun, Bao Deng, and Guangyu Wang. "High-Fidelity Seismic Super-Resolution Using Prior-Informed Deep Learning With 3D Awareness." IEEE Transactions on Image Processing 35 (2026): 2152-2166.
@article{li2026sr_tip,
title = {High-Fidelity Seismic Super-Resolution Using Prior-Informed Deep Learning with 3D Awareness},
author = {Jintao Li and Xinming Wu and Xianwen Zhang and Xin Du and Xiaoming Sun and Bao Deng and Guangyu Wang},
journal = {IEEE Transactions on Image Processing},
year = {2026},
volume = {35},
pages = {2152-2166},
url = {https://ieeexplore.ieee.org/document/11399639}
}
期刊论文Journal Article
代表性成果Featured
IF 7.0.IF 7.0.Nature Portfolio.Nature Portfolio.This paper was unanimously recognized by all three reviewers.This paper was unanimously recognized by all three reviewers.
Jintao Li and Xinming Wu
"Memory-Efficient Full-Volume Inference for Large-Scale 3D Dense Prediction without Performance Degradation." Communications Engineering 5, 20 (2026).
Li, Jintao, and Xinming Wu. "Memory-Efficient Full-Volume Inference for Large-Scale 3D Dense Prediction without Performance Degradation." Communications Engineering 5, 20 (2026).
@article{li2026memory,
title = {Memory-Efficient Full-Volume Inference for Large-Scale 3D Dense Prediction without Performance Degradation},
author = {Jintao Li and Xinming Wu},
journal = {Communications Engineering},
year = {2026},
volume = {5},
pages = {20},
doi = {10.1038/s44172-025-00576-2},
url = {https://doi.org/10.1038/s44172-025-00576-2}
}
期刊论文Journal Article
代表性成果Featured
Jintao Li, Yunzhi Shi, and Xinming Wu
"CIGVis: An open-source Python tool for the real-time interactive visualization of multidimensional geophysical data." Geophysics 90, no. 1 (2025): F1-F10.
Li, Jintao, Yunzhi Shi, and Xinming Wu. "CIGVis: An open-source Python tool for the real-time interactive visualization of multidimensional geophysical data." Geophysics 90, no. 1 (2025): F1-F10.
@article{li2025cigvis,
title = {CIGVis: An Open-Source Python Tool for Real-Time Interactive Visualization of Multidimensional Geophysical Data},
author = {Jintao Li and Yunzhi Shi and Xinming Wu},
journal = {Geophysics},
year = {2025},
volume = {90},
number = {1},
pages = {F1-F10},
doi = {10.1190/geo2024-0041.1},
url = {https://library.seg.org/doi/abs/10.1190/geo2024-0041.1}
}
期刊论文Journal Article
代表性成果Featured
Jintao Li, Xinming Wu, Yueming Ye, Cun Yang, Zhanxuan Hu, Xiaoming Sun, and Tao Zhao
Li, Jintao, Xinming Wu, Yueming Ye, Cun Yang, Zhanxuan Hu, Xiaoming Sun, and Tao Zhao. "Unsupervised Contrastive Learning for Seismic Facies Characterization." Geophysics 88, no. 1 (2023): WA81-WA89.
@article{li2023facies,
title = {Unsupervised Contrastive Learning for Seismic Facies Characterization},
author = {Jintao Li and Xinming Wu and Yueming Ye and Cun Yang and Zhanxuan Hu and Xiaoming Sun and Tao Zhao},
journal = {Geophysics},
year = {2023},
volume = {88},
number = {1},
pages = {WA81-WA89},
doi = {10.1190/geo2022-0148.1},
url = {https://library.seg.org/doi/10.1190/geo2022-0148.1}
}
期刊论文Journal Article
代表性成果Featured
IF 9.4.IF 9.4.ESI Highly Cited Paper.ESI Highly Cited Paper.
Jintao Li, Xinming Wu, and Zhanxuan Hu
"Deep Learning for Simultaneous Seismic Image Super-Resolution and Denoising." IEEE Transactions on Geoscience and Remote Sensing (IEEE TGRS) 60 (2022): 1-11.
Li, Jintao, Xinming Wu, and Zhanxuan Hu. "Deep Learning for Simultaneous Seismic Image Super-Resolution and Denoising." IEEE Transactions on Geoscience and Remote Sensing 60 (2022): 1-11.
@article{li2022sr_tgrs,
title = {Deep Learning for Simultaneous Seismic Image Super-Resolution and Denoising},
author = {Jintao Li and Xinming Wu and Zhanxuan Hu},
journal = {IEEE Transactions on Geoscience and Remote Sensing},
year = {2022},
volume = {60},
pages = {1-11},
url = {https://ieeexplore.ieee.org/document/9364884/}
}
