Chuang Liu

Ph.D. Student · State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University

📧 laxiojustmoveon@gmail.com / chuang.liu@whu.edu.cn

我目前聚焦于 AI + Remote Sensing 智能体、遥感多模态智能体、视觉语言/大模型驱动的遥感理解、工具调用与知识推理、图像融合/复原、变化检测,以及面向大规模地理空间数据的智能分析工作流。如果你的研究方向与我相近,或对我的工作感兴趣,欢迎交流与合作;邮箱和微信二维码见左侧栏。

My current research focuses on AI + Remote Sensing agents, multimodal Earth-observation intelligence, vision-language reasoning, tool-augmented remote-sensing analysis, image fusion/restoration, and change detection. If your research interests are related to mine, or if you are interested in my work, I am open to collaboration. My email and WeChat QR code are available in the left sidebar.

🔑 Research Interests

My research interests include AI4RS Agents, Multimodal Large Vision-Language Models for Remote Sensing, Earth-Observation Foundation Models, Spatial-Spectral Representation Learning, Remote Sensing Image Fusion/Restoration, and Change Detection.

AI4RS Agents Remote Sensing VLM Tool-augmented Intelligence Spatial-Spectral Learning Image Fusion Image Restoration Change Detection Mixture-of-Experts

🔥 Latest News

One work related to prior-guided multi-domain mixture-of-experts was accepted by ISPRS Journal of Photogrammetry and Remote Sensing.

One work related to explicit spatial-spectral closed-loop priors was accepted by Pattern Recognition.

One work related to joint representation learning and mixture-of-experts was accepted by IEEE GRSL.

One work related to role-specialized LLM agents for medical decision-making was accepted by ICLR 2026.

One work related to exemplar retrieval and in-context learning for multi-step reasoning was accepted by ICASSP 2026.

“Most Beautiful College Student” Honor; one of five graduate students selected university-wide.

🔥 Recent Works

Equal contribution Corresponding author Project Leader
ISPRSDAMoE thumbnail
[DAMoE] Prior-guided Multi-domain Mixture-of-Experts for Multimodal Earth Observation Data Gaps
AI4RSMixture-of-ExpertsMultimodal EO FusionISPRS
Chuang Liu, Jianhua Guo, Yingdong Pi, Xiao Wu, Zhiqi Zhang, Ru Chen, Xinyi Wang, and Mi Wang
ISPRS Journal of Photogrammetry and Remote Sensing, vol. 239, pp. 876-892, 2026.
PRUCLN thumbnail
[UCLN] Interpretable Pan-sharpening via Explicit Spatial-Spectral Closed-loop Priors
Interpretable FusionPan-sharpeningDeep UnfoldingPattern Recognition
Chuang Liu, Zhiqi Zhang, Zhiwei Ye, Xiao Wu, Mi Wang, and Jianhua Guo
Pattern Recognition, vol. 180, article 114301, 2026.
TGRSRAMSF thumbnail
【RAMSF】A Novel Generic Framework for Optical Remote Sensing Multimodal Spatial-Spectral Fusion Citation: 12
AI4RSMultimodal FusionSpatial-Spectral LearningJCR Q1
Chuang Liu, Zhiqi Zhang, and Mi Wang
IEEE Transactions on Geoscience and Remote Sensing, 2025.
GSISCF2N thumbnail
【CF2N】A Novel Cross Fusion Model with Fine-grained Detail Reconstruction for Remote Sensing Image Pan-sharpening Citation: 12
Pan-sharpeningFine-grained DetailFrequency-Spectral FusionJCR Q1
Chuang Liu, Zhiqi Zhang, Mi Wang, Shao Xiang, and Guangqi Xie
Geo-spatial Information Science, vol. 28, no. 4, pp. 1520–1548, 2025.
JSTARSSTDAN thumbnail
【STDAN】A Spatial-Temporal Difference Aggregation Network for Gaofen-2 Multitemporal Image Change Detection in Cropland Area Citation: 7
Change DetectionDense PredictionMulti-temporal RSJCR Q1
Chuang Liu, Liyang Bao, and Zhiqi Zhang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 3160-3172, 2025.
JSTARSMMAPP thumbnail
【MMAPP】Multi-branch and Multi-scale Adaptive Progressive Pyramid Network for Multispectral Image Pansharpening Citation: 5
Progressive PyramidMulti-scale LearningPan-sharpeningJCR Q1
Zhiqi Zhang, Chuang Liu, Lu Wei, and Shao Xiang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 20129-20149, 2024.
JSTARSRSANet thumbnail
【RSANet】Recursive Self-Attention Modules-Based Network for Panchromatic and Multispectral Image Fusion Citation: 12
Self-AttentionPan-sharpeningFeature FusionJCR Q1
Chuang Liu, Lu Wei, Zhiqi Zhang, Xiaoxiao Feng, and Shao Xiang
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 10067-10083, 2023.

🧩 Research Experience

AI + Remote Sensing Agents and Multimodal Earth-observation Intelligence

Building agentic AI systems that combine multimodal perception, vision-language reasoning, domain knowledge, and tool/data interaction for remote-sensing interpretation and geospatial decision support.

Computer Vision for Multimodal Earth-Observation Image Fusion

Developed neural frameworks for optical multimodal image fusion, including pan-sharpening, multispectral/hyperspectral image fusion, and Earth-observation data-gap recovery.

Multi-temporal Visual Change Detection and Dense Prediction

Designed spatial-temporal difference aggregation models for Gaofen-2 multitemporal cropland image change detection and pixel-level prediction.

Efficient Vision Systems for Satellite Platforms

Worked on cloud-edge-device collaborative intelligent service architecture, efficient visual perception, real-time inference, and robust processing for high-resolution satellite image streams.

🎓 Education

Wuhan University
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing | Ph.D. in Surveying and Mapping Engineering

Hubei University of Technology
School of Computer Science | M.Eng. in Computer Technology

👥 Advisor & Team

Supervisor: Prof. Mi Wang · RSONE Remote Sensing Image Precision Processing and Intelligent Service Team.

I am a Ph.D. student at LIESMARS, Wuhan University. The team focuses on precise remote-sensing image processing, quality improvement, high-precision geometric positioning and mapping, onboard processing, and real-time intelligent services for remote-sensing satellite constellations.

RSONE Team Homepage

🏆 Honors, Awards & Patents