博士生导师
硕士生导师
个人信息Personal Information
学历：博士研究生毕业
学位：工学博士学位
办公地点：犀浦校区四教4227
在职信息：在岗
主要任职：扬华学者教授
学科：摄影测量与遥感
所在单位：地球科学与工程学院
联系方式Other Contact Information
邮箱 :
报考该导师研究生的方式
欢迎你报考张天文老师的研究生，报考有以下方式：
1、参加西南交通大学暑期夏令营活动，提交导师意向时，选择张天文老师，你的所有申请信息将发送给张天文老师，老师看到后将和你取得联系，点击此处参加夏令营活动
2、如果你能获得所在学校的推免生资格，欢迎通过推免方式申请张天文老师研究生，可以通过系统的推免生预报名系统提交申请，并选择意向导师为张天文老师，老师看到信息后将和你取得联系，点击此处推免生预报名
3、参加全国硕士研究生统一招生考试报考张天文老师招收的专业和方向，进入复试后提交导师意向时选择张天文老师。
4、如果你有兴趣攻读张天文老师博士研究生，可以通过申请考核或者统一招考等方式报考该导师博士研究生。
个人简介Personal Profile
【个人简介】【Personal Profile】
张天文，博士，扬华学者教授，博士生导师，全球高被引科学家（Clarivate），全球前2%顶尖科学家（Stanford）。主要从事SAR智能解译、复杂场景智能感知、雷达目标解析、遥感图像处理、计算机视觉、人工智能等教学科研工作。曾任华为雷达感知高级技术专家、华为感知能力中心主任。在Information Fusion、ISPRS、GRSM、IEEE Trans. (TCSVT、TII、TGRS、TAES、TASE)、PR等期刊发表论文50余篇，其中ESI热点论文7篇、ESI高被引论文22篇（一作/通讯）。谷歌学术引用>5800次。主持国家自然科学基金（面上&青C）、博后面上、国资博后B、中央高校基本科研业务费等项目。Remote Sensing编委、IET Radar, Sonar & Navigation编委、Frontiers in Remote Sensing副主编、《电子学报》客座编委、《现代雷达》青年编委等。
Dr. Zhang Tianwen is a Professor of SWJTU Yanghua Fellow and Doctoral Supervisor. He is recognized as a Clarivate Highly Cited Researcher and is listed among the world's top 2% scientists by Stanford University. His teaching and research focus on areas such as intelligent SAR interpretation, intelligent perception in complex scenes, radar target analysis, remote sensing image processing, computer vision, and artificial intelligence. He previously served as a Senior Technical Expert in Radar Perception and Director of the Perception Capability Center at Huawei. He has published over 50 papers in journals such as Information Fusion, ISPRS, GRSM, IEEE Trans. (TCSVT, TII, TGRS, TAES, TASE), PR, and so on; among these, 7 are ESI Hot Papers and 22 are ESI Highly Cited Papers (as first or corresponding author). He has accumulated over 5,800 citations on Google Scholar and has presided over projects funded by the National Natural Science Foundation of China (including General Program and Young Scientist projects). He serves on the editorial boards of Remote Sensing and IET Radar, Sonar & Navigation, as an Associate Editor for Frontiers in Remote Sensing, and as a guest/youth editorial board member for Acta Electronica Sinica and Modern Radar, respectively.
【谷歌学术】【Google Scholar 】
https://scholar.google.com/citations?user=aJV0kM4AAAAJ&hl=en
【所属团队】【Affiliated Team】
虚拟地理环境团队（Leader：朱庆）=> 智能遥感处理课题组（Leader：高贵）
Virtual Geographic Environment Team (Leader: Zhu Qing) => Intelligent Remote Sensing Processing Research Group (Leader: Gao Gui)
【代表论文】（*通讯作者）【Selected Publications】（*Corresponding author）
[1] T. Zhang, X. Zhang, S. Wei, and G. Gao, "SRASEF-OVSeg: Task-adaptive semantic re-alignment and scattering-evidence-guided multimodal fusion for optical–SAR open-vocabulary segmentation," Information Fusion, vol. 139, 2027, Art. no. 104788. (IF=17.4)
[2] T. Zhang, G. Gao, and X. Zhang, "Glance-Focus-Gaze: A Novel Eagle-Eye Vision-Inspired Panorama-Population-Individual Progressive Screening Paradigm to Capture Ships in SAR Images," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 235, pp. 241-260, 2026. (IF=12.9, ESI Hot, ESI Highly Cited)
[3] T. Zhang et al., "Balance Learning for Ship Detection from Synthetic Aperture Radar Remote Sensing Imagery," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 182, no. 2021, pp. 190-207, 2021. (IF=12.9, ESI Highly Cited)
[4] T. Zhang et al., "Balance Learning for Ship Detection from Synthetic Aperture Radar Remote Sensing Imagery," ISPRS Journal of Photogrammetry and Remote Sensing, vol. 182, no. 2021, pp. 190-207, 2021. (IF=12.9, ESI Hot, ESI Highly Cited)
[5] R. Deng, T. Zhang*, et al., "Language-Prompted Visual Query Learning for Ship-Sea-Land Disambiguation in Maritime Panoptic Segmentation from SAR Imagery," IEEE Transactions on Circuits and Systems for Video Technology, early access, 2026. (IF=10.8)
[6] T. Zhang, X. Zhang, and G. Gao, "Density Knowledge Mining for Quantity-Aware Marine Vessel Surveillance Using Satellite SAR Data," IEEE Transactions on Industrial Informatics, vol. 22, no. 6, pp. 5173-5184, 2026. (IF=9.8, ESI Highly Cited)
[7] T. Zhang et al., "HOG-ShipCLSNet: A Novel Deep Learning Network With HOG Feature Fusion for SAR Ship Classification," IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-22, 2022, Art. no. 5210322. (IF=9.4, ESI Highly Cited)
[8] T. Zhang and X. Zhang, "A Polarization Fusion Network with Geometric Feature Embedding for SAR Ship Classification," Pattern Recognition, vol. 123, pp. 1-15, 2022, Art. no. 108365. (IF=9.1)
[9] T. Zhang and X. Zhang, "Triple-Level Sparsity Awareness for Marine Ship Surveillance Using Satellite Synthetic Aperture Radar," IEEE Transactions on Automation Science and Engineering, vol. 23, pp. 5155-5166, 2026. (IF=7.9, ESI Highly Cited)
[10] T. Zhang, X. Zhang, and G. Gao, "Divergence to Concentration and Population to Individual: A Progressive Approaching Ship Detection Paradigm for Synthetic Aperture Radar Remote Sensing Imagery," IEEE Transactions on Aerospace and Electronic Systems, vol. 62, pp. 1325-1338, 2026. (IF=7.0, ESI Hot, ESI Highly Cited)