高杨，男，中南大学计算机学院硕士生导师，澳大利亚University of Queensland 客座研究员（Honorary Fellow），2022年8月于澳大利亚昆士兰大学信息技术与电子工程学院（school of ITEE）获得博士学位，11月加入中南大学计算机学院工作。研究方向专注于人工智能赋能的新型医学成像技术，尤其是快速高分辨率定量磁共振技术(Magnetic Resonance Imaging)及前沿定量磁化率（Quantitative Susceptibility Mapping）成像, 磁粒子成像（Magnetic Particle Imaging)重建及分析技术。

主持国家自然科学基金青年项目1项，湖南省自然科学基金青年项目1项。参与国家自然科学基金国际合作项目等科研项目多项。

曾获得澳大利亚昆士兰州政府资助全额博士奖学金（2018-2022），并在领域内权威学术期刊和会议如NeuroImage, Medical Image Analysis,  IEEE TMI，Magnetic Resonance in Medicine, Advanced Science, NMR in Biomed, Medical Physics, IEEE TCYB 等共发表论文20余篇。在国际医学核磁共振学会年会ISMRM（磁共振领域最顶级国际学术会议，清华大学分类-顶尖级-国际学术会议）发表会议论文 7篇(5 Oral Presentations) 。 

【硕士招生】

每年招收3名左右硕士研究生，招收士兵计划学生，欢迎对人工智能、磁共振成像、脑/神经成像、 分子影像、医学成像等领域感兴趣的同学与我联系。（邮箱：222285@csu.edu.cn / yang.gao@csu.edu.cn / uqygao10@uq.edu.au）。

课题组与国内外多家研究单位，如南京大学、北京中日友好医院、澳大利亚昆士兰大学、加拿大卡尔加里大学，有长期合作，可以为每位同学的发展提供尽可能多的支持。

【课题组每年将选派优秀研究生赴长三角医学先进技术创新中心参与磁粒子成像（MPI）重点项目研究，并提供全方面（包括生活补贴、住宿和设备等）的发展支持】

1. 欢迎对科研非常感兴趣，自驱力强的同学，或者动手能力强的同学（EE-CS背景为佳），能够自己动手进行软硬件系统的设计与实现；   

2. 期望可以别的同学友好相处；

3. 希望你有一个自己的运动或者爱好，唱歌、dota2比较好的的优先考虑； 

【社会兼职及荣誉】

• 2024年获得国际华人磁共振协会年度青年研究员奖（OCSMRM-YIA，第二名）

• 2024年至今担任业界顶级期刊NeuroImage（大脑成像领域排名第一）关于QSM及EPT成像方法特刊编辑。

• 担任中国医学图像计算青年研讨会（MICS）委员会委员

• 湖南省数字医学会智能影像分会委员

• 北京神经科学学会神经影像工程信息学专业委员会青年委员

• 2022年在ISMRM大会上关于端到端QSM方法的报告获得 ISMRM Magna Cum Laude Merit Award

• 2025年受邀在ISMRM EMTP Virtual Meeting 做 关于深度学习驱动的定量磁化率成像主题报告（An Overview of Deep Learning Methods for Quantitative Susceptibility Mapping， https://www.ismrm.org/virtual-meetings/archive/  ）

【主要期刊论文列表（完整列表见谷歌学术主页 https://scholar.google.com/citations?user=kjmAyJ4AAAAJ&hl=en  ）】

• Jin Liu, Qing Lin, Zhuang Xiong, Shanshan Shan, Chunyi Liu, Min Li, Feng Liu, G. Bruce Pike, Hongfu Sun, Yang Gao*. Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models, IEEE Transactions on Medical Imaging, DOI: 10.1109/TMI.2026.3654585, 2026. 

• Yang Gao, et al., Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks, Medical Image Analysis (SCI, JCR 1, IF: 10.9). 2024, https://doi.org/10.1016/j.media.2024.103160. 

• Min Li, Chen Chen, ... Yang Gao*, Quantitative Susceptibility Mapping via Deep Neural Networks with Iterative Reverse Concatenations and Recurrent Modules, Medical Physics, (SCI, JCR Q1), 2025.

• Yang Gao, Martijn Cloos, Feng Liu, Stuart Crozier, G. Bruce Pike, Hongfu Sun. Accelerating Quantitative Susceptibility and R2* Mapping using Incoherent Undersampling and Deep Neural Network Reconstruction. NeuroImage, 2021, 240: 118404, (SCI, JCR 1, IF:6.556, Top1 in Neuroimaging).
  

• Yang Gao, Zhuang Xiong, Amir Fazlollahi, Peter Nestor, Vector Vegh, Fatima Nasrallah, Craig Winter, G. Bruce Pike, Stuart Crozier, Feng Liu, Hongfu Sun. Instant magnetic tissue field and susceptibility mapping from MR raw phase using Laplacian enabled deep neural networks. NeuroImage, 2022, (SCI, JCR 1, IF:6.556, Top1 in Neuroimaging).

• Yang Gao,Xuanyu Zhu,Bradford A. Moffat,Rebecca Glarin,Alan H. Wilman,G. Bruce Pike,Stuart Crozier,Feng Liu,Hongfu Sun. xQSM: quantitative susceptibility mapping with octave convolutional and noise-regularized neural networks. NMR Biomed, 2021, 34(3): p. e4461, (SCI, JCR 1, IF 4.044).

• Shanshan Shan#, Yang Gao#, Paul Z.Y. Liu, Brendan Whelan, Hongfu Sun, Feng Liu, David E.J. Waddington. Distortion-Corrected Image Reconstruction with Deep Learning on an MRI-Linac. Magnetic Resonance in Medicine, 2022. (SCI, JCR Q1). 

• Hongping Gan, Yang Gao*, Chunyi Liu, Haiwei Chen, Tao Zhang, Feng Liu. AutoBCS: Block-based Image Compressive Sensing with Data-driven Acquisition and Non-iterative Reconstruction. IEEE Transactions on Cybernetics, 2021, (SCI, JCR Q1, IF:11.448) DOI: https://doi.org/10.1109/TCYB.2021.3127657. (通讯作者)

• Shanshan, Shan, Yang Gao*, et al. Image Reconstruction with B0 Inhomogeneity using a Deep Unrolled Network on an Open-bore MRI-Linac, 2024, IEEE Transactions on Instrumentation and Measurement. (SCI, JCR, Q1, IF5.6 通讯作者) . https://ieeexplore.ieee.org/document/10720147 

【主要会议论文列表】

• Jin, R., Chen, C., Liu, Y., Sun, H., Zeng, M., Li, M. and Gao, Y*., 2025. GateFuseNet: An Adaptive 3D Multimodal Neuroimaging Fusion Network for Parkinson's Disease Diagnosis. 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Wuhan, China, 2025, pp. 2335-2340, doi: 10.1109/BIBM66473.2025.11356155.

• J. Lu, Y. Wu, Y. Li, Q. Liu, Y. Gao* and M. Zeng, "RNA3D-SSCL: Improving RNA Tertiary Structure Prediction via a Secondary Structure-Constrained Loss Function," 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Wuhan, China, 2025, pp. 45-50, doi: 10.1109/BIBM66473.2025.11356756.

• Ang Gao, ..., Yang Gao*. et al., PDDF-Net: A deep neural network for diagnosing Parkinson's Disease using QSM and T1w images. 2026, ISMRM. Captown. (presenting author)

• Tianyi Ding, ... Yang Gao*, et al., Mamba-MRF:A Deep Mamba Network for Highly Accelerated Magnetic Resonance Fingerprinting Reconstruction. 2026, ISMRM. Captown. (presenting author)

• Samiha Prima, Hongfu Sun, Yang Gao*, et al., A Self-Supervised Transformer for Myelin Water Fraction Mapping from Multi-Echo Gradient-Echo Imaging. 2026, ISMRM. Captown. (presenting author)

• Yang Gao, Zhuang Xiong, Stuart Crozier, Feng Liu, Hongfu Sun. QSM from the raw phase using an end-to-end neural network. International Society for Magnetic Resonance in Medicine 31th Scientific Meeting-ISMRM, online meeting. 2022. (Oral presentation, Magna Cum Laude Merit Award)

• Yang Gao, Xuanyu Zhu, Stuart Crozier, Feng Liu, Hongfu Sun. xQSM: a deep learning QSM network using Octave Convolution. International Society for Magnetic Resonance in Medicine 29th Scientific Meeting-ISMRM, online meeting, 08-14 August 2020. (Oral presentation)

• Yang Gao, Stuart Crozier, Feng Liu, G Bruce Pike, Hongfu Sun. Accelerating QSM using Compressed Sensing and Deep Neural Network. International Society for Magnetic Resonance in Medicine 30th Scientific Meeting-ISMRM, online meeting, 15-20 May, 2021. (Oral presentation)

• Yang Gao, Tianyi Ding, Martjn Cloos, Hongfu Sun. MRF-mixer: a self-supervised deep learning MRF framework. International Society for Magnetic Resonance in Medicine 32th Scientific Meeting-ISMRM. 2023. (Oral presentation)

• Yang Gao, et al., QSM Reconstruction of Arbitrary Dipole Orientations using an End-to-end Neural Network via Latent Feature Editing, 2024, ISMRM. Singapore, Digital Poster. 

• Chen Chen, Yang Gao*, et al., LoopNet: A New Baseline Network for QSM Dipole Inversion, 2024, ISMRM. Singapore, Digital Poster.