Wenqi Huang
PHD Student at Technical University of Munich
Munich, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolWenqi Huang is a PhD student at the Technical University of Munich focusing on deep learning for MRI reconstruction and medical image processing, with a decade of research and engineering experience. Her work blends model-based priors—low-rankness and sparsity—with modern neural networks to boost dynamic MRI reconstruction quality, reflecting a strong foundation from her Master's at SIAT/CAS. She has complemented academic research with industry exposure at Siemens Healthineers and an international stint as a visiting researcher at Stanford, bringing practical problem-solving to translational imaging challenges. Based in Munich, Wenqi combines rigorous pattern-recognition training with hands-on implementation, often bridging theory and application in reproducible code and prototypes.
10 years of coding experience
Master's degree, Pattern Recognition and Machine Intelligence, 3.6/4.0, Master's degree, Pattern Recognition and Machine Intelligence, 3.6/4.0 at University of Chinese Academy of SciencesBachelor of Engineering - BE, Information Engineering, 3.8/4.0, Bachelor of Engineering - BE, Information Engineering, 3.8/4.0 at Soochow University (CN)
Github Skills (48)
sparse8
python8
deep-learning8
gpu8
machine-learning8
mri7
neural-network6
tensorflow6
imaging6
self-organizing-map5
activation5
transform5
representations5
numpy5
periodic5
Programming languages (4)
Github contributions (5)
wenqihuang/LS-Net-Dynamic-MRI
Dec 2021 - Jul 2022
This the code repository for paper "Deep Low-rank plus Sparse Network for Dynamic MR Imaging".
Contributions:11 commits, 3 PRs, 6 pushes in 7 months
pytorchlow-rankdeep-learningsparseimaging
pickpig/hello-world
Apr 2016 - Jul 2016
Contributions:2 PRs, 3 pushes, 2 branches in 2 months
pythonfirst-repository
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