I am a final-year Ph.D. candidate at the Department of Electrical Engineering at Stanford University, co-advised by Prof. John Pauly and Prof. Lei Xing. I am currently a Stanford Bio-X Bowes Graduate Student Fellow (2019-2022). I am honored to be selected as the Rising Star in EECS by MIT and the Rising Star in Data Science by University of Chicago.

My research lies in Medical AI, which spans the interdisciplinary research areas of AI/ML, computer vision, biomedical imaging and data science. My dissertation research develops efficient AI/ML-driven computational algorithms and techniques for carrying out biomedical imaging and informatics to tackle real-world biomedicine and healthcare problems through engineering and data science. Specifically, a major line of my research focuses on investigating methods to exploit prior knowledge from the physical world - exploit what you know - in developing efficient AI/ML-driven computational algorithms for biomedical imaging and informatics. I have collborated with Prof. Fei-Fei Li, Prof. Wah Chiu, Prof. Serena Yeung, Prof. Kristen Yeom, Prof. Judy Hoffman, Prof. Liang Zheng on various research projects. [Google Scholar]

I hold a M.Sc. degree in Electrical Engineering from Stanford University. Before starting my Ph.D., I received my B.S. degree in Electronic Engineering from Tsinghua University in 2016. In Summer 2019 and Summer 2020, I worked as a research intern at Nvidia and Waymo Research in California.

Since Spring 2021, I co-organized the Woman in Machine Learning (WiML) workshop at ICML' 21, and the Machine Learning for Healthcare (ML4H) workshop at NeurIPS' 21. In MICCAI' 21, I co-taught the tutorial on Deep 2D-3D Modeling and Learning in Medical Image Computing.

I am on the 2021–2022 job market. Please feel free to connect!


Education

Sep. 2016 - Present, Department of Electrical Engineering, Stanford University

Ph.D. Candidate

Sep. 2016 - Jun. 2019, Department of Electrical Engineering, Stanford University

Master of Science

Sep. 2012 - Jul. 2016, Department of Electronic Engineering, Tsinghua University

Bachelor of Engineering


Industry

Jun. 2020 - Sep. 2020, Waymo

Research Intern

Jun. 2019 - Sep. 2019, Nvidia

Research Intern


Publications

(*equal contributions)
Yang Song*, Liyue Shen*, Lei Xing, Stefano Ermon.
Under review, 2021.
(Preliminary version accepted by NeurIPS 2021 Deep Learning and Inverse Problems Workshop)
Liyue Shen, John Pauly, Lei Xing.
IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (under revision), 2021.
(Preliminary version accepted by NeurIPS 2021 Deep Learning and Inverse Problems Workshop)
Liyue Shen, Wei Zhao, Dante Capaldi, John Pauly, Lei Xing.
Physics in Medicine and Biology (PMB) (under revision), 2021.
(Preliminary version accepted by NeurIPS 2020 Deep Learning and Inverse Problems Workshop and American Association of Physicists in Medicine (AAPM) 2021) (Oral)
Attention-Guided Deep Learning for Gestational Age Prediction using Fetal Brain MRI
Liyue Shen*, Jimmy Zheng*, Edward Lee, Michelle Han, Katie Shpanskaya, Emily McKenna, Dinko Plasto, Courtney Mitchell, Lillian Lai, Carolina Guimaraes, Hisham Dahmoush, Jane Chueh, Safwan Halabi, John Pauly, Lei Xing, Quin Lu, Ozgur Oztekin, Beth Kline-Fath, Kristen Yeom.
Scientific Reports, 2022.
Liyue Shen, Lequan Yu, Wei Zhao, John Pauly, Lei Xing.
Medical Image Analysis (MedIA), 2021.
(Preliminary version accepted by American Association of Physicists in Medicine (AAPM) and American Society for Radiation Oncology (ASTRO), 2020) (Student Presentation Award)
Shih-Cheng Huang*, Liyue Shen*, Matthew Lungren, Serena Yeung.
International Conference on Computer Vision (ICCV), 2021.
[code]
Wei Zhao, Liyue Shen, Md Tauhidul Islam, Wenjian Qin, Zhicheng Zhang, Xiaokun Liang, Gaolong Zhang, Shouping Xu, Xiaomeng Li.
Quantitative Imaging in Medicine and Surgery (QIMS), 2021.
Hyunseok Seo, Lequan Yu, Hongyi Ren, Xiaomeng Li, Liyue Shen, Lei Xing.
IEEE Transactions on Medical Imaging (TMI), 2021.
Liyue Shen, Wentao Zhu, Xiaosong Wang, Lei Xing, John Pauly, Daguang Xu.
IEEE Transactions on Medical Imaging (TMI), 2020.
Masoud Badiei Khuzani*, Liyue Shen*, Shahin Shahrampour, Lei Xing.
Journal of Machine Learning Research (JMLR) (under revision), 2019.
Liyue Shen*, Wei Zhao*, Lei Xing.
Nature Biomedical Engineering, 2019.
[code]
Wei Zhao, Liyue Shen, Bin Han, Yong Yang, Kai Cheng, Diego AS Toesca, Albert C Koong, Daniel T Chang, Lei Xing.
International Journal of Radiation Oncology Biology Physics, 2019.
Wei Zhao, Tianling Lv, Peng Gao, Liyue Shen, Xianjin Dai, Kai Cheng, Mengyu Jia, Yang Chen, Lei Xing.
International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019.
Liyue Shen, Wei Zhao, Lei Xing.
SPIE Medical Imaging, 2019. (Oral)
Wei Zhao, Liyue Shen, Yan Wu, Bin Han, Yong Yang, Lei Xing.
SPIE Medical Imaging, 2019. (Oral)
Liyue Shen, Katie Shpanskaya, Edward Lee, Emily McKenna, Maryam Maleki, Quin Lu, Safwan Halabi, John Pauly, Kristen Yeom.
Neural Information Processing Systems (NeurIPS), Machine Learning for Health (ML4H) Workshop, 2018. (Spotlight)
International Society for Magnetic Resonance in Medicine (ISMRM), 2019. (Oral)
Liyue Shen, Serena Yeung, Judy Hoffman, Greg Mori, Li Fei-Fei.
IEEE Winter Conference on Applications of Computer Vision (WACV), 2018.
Serena Yeung, Vignesh Ramanathan, Olga Russakovsky, Liyue Shen, Greg Mori, Li Fei-Fei.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
Liang Zheng*, Liyue Shen*, Lu Tian*, Shengjin Wang, Jingdong Wang, Qi Tian.
International Conference on Computer Vision (ICCV), 2015.
[project page] [code] [data]

Projects

Liyue Shen, Timothy Anderson
Stanford CS231N: Convolutional Neural Networks for Visual Recognition, 2017.
Liyue Shen, Ruiyang Song
Stanford CS229: Machine Learning, 2017.
Liyue Shen*, Ruishan Liu*
Stanford CS224N: Natural Language Processing with Deep Learning, 2018.

Honors & Awards


Grants and Fellowship


Professional Activities

Organizer: Program Committee and Conference Reviewer: Journal Editor and Reviewer:

Teaching


Patents

NeRP: Implicit Neural Representation Learning with Prior Embedding for Sparsely Sampled Image Reconstruction and Other Inverse Problems
Liyue Shen, Lei Xing.
Leland Stanford Junior University, 2021.
Prior-incorporated deep learning framework for sparse image reconstruction by using geometry and physics priors from imaging system
Liyue Shen, Lei Xing, Lianli Liu.
Leland Stanford Junior University, 2020.
Deep Learning Model for 3D Computed Tomography (CT) Image Reconstruction with Single or a Few Views
Liyue Shen, Wei Zhao, Lei Xing.
Leland Stanford Junior University, 2019.
Representational Disentanglement for Multi-Modality Image Completion Using Neural Networks
Wentao Zhu, Liyue Shen, Xiaosong Wang, Daguang Xu.
Nvidia Corporation, 2019.