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Quanfeng Xu (徐 权峰) |
I am currently a Ph.D. candidate (expected Nov 2026) in the Galaxy Cluster Group at the Shanghai Astronomical Observatory, supervised by Prof. Shiyin Shen. With a foundation in probability theory and mathematical statistics, my research focuses on AI for Science (AI4S), combining low-level computer vision with astrophysics to learn robust representations from raw astronomical images and support downstream scientific tasks. My broader research interests include 3D vision (NeRF and Gaussian Splatting), SLAM, generative AI, and GPU acceleration. I aim to keep expanding my expertise and contribute to technological advances in a dynamic R&D environment.
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Plate-YOLO: An End-to-End Object Detection Framework for Robust Astrometric Registration of Historical Plates |
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FluxFlow: Conservative Flow-Matching for Astronomical Image Super-Resolution |
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Enhancing astrometric registration of Chinese historical Astronomical Digital Plates with deep learning |
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From images to features: unbiased morphology classification via variational auto-encoders and domain adaptation |
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Denoising the Deep Sky: Physics-Based CCD Noise Formation for Astronomical Imaging |
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DeRainGS: Gaussian Splatting for Enhanced Scene Reconstruction in Rainy Environments |
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Galmoss: A package for GPU-accelerated galaxy profile fitting |
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qrpca: A package for fast principal component analysis with GPU acceleration |
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南极天目计划原型机数据查询与下载 |
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大场景变电站三维高斯重建 |
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电网系统接入本地人工智能大语言模型 |
2023.09-Present (Shanghai Astronomical Observatory):