Biography

Education

Stanford University

• Ph.D. candidate, Electrical Engineering (09/2015 - 07/2020)
  

  • Advisor: Prof. Brian Hargreaves
    

  • Dissertation: “Advanced reconstruction techniques for high-resolution diffusion-weighted MRI”

• M.S., Electrical Engineering (09/2015 - 06/2018)
  

  • Depth Area: Signal Processing and Optimization
    

Tsinghua University

• B.E., Biomedical Engineering (08/2011 - 07/2015)
  

• B.S., Economics and Management (09/2012 - 07/2015)
  

Experience

Summer Intern, Google Geo Group, Google Inc. (06/2019 - 09/2019)

• Proposed and developed a machine learning algorithm to remove spatially varying haze from satellite images.
  

Research Assistant, Lucas Center for Imaging, Stanford University (01/2016 - 07/2020)

• Developed new techniques to accelerate MRI reconsturction and improve image quality through model-based optimization and deep learning.
  

Visiting Student Researcher, Magnetic Resonance Systems Research Lab (MRSRL), Stanford University (07/2014 - 09/2014)

• Extended MRI virtual coil reconstruction for arbitrary sampling patterns thorough multi-layer convolution.
  

Research Assistant, Center for Biomedical Imaging Research (CBIR), Tsinghua University (09/2012 - 06/2015)

• Designed a new data acquisition strategy and a corrupted data recovery method for reducing breath-hold requirements in dynamic MRI.
  

Course Projects

Reconstruction of compressive light field data

• @EE367: Computational Imaging and Display (2019 Spring)
  

• Proposed a two-component model (e.g. low rank + sparse) to recover multiple views from compressive light field data and compared different combinations of different priors. [Report] [Poster]
  

Unrolled network for accelerated MRI reconstruction

• @CS231N: Convolutional Neural Networks for Visual Recognition (2018 Spring)
  

• Introduced unrolled network with modified U-nets as priors for multi-shot diffusion-weighted MRI reconstruction and reduced reconstruction time to 1/60. [Report] [Poster]
  

Comparison of low-rank methods in spatial and frequency domains for MRI reconstruction

• @EE369C: Medical Image Reconstruction (2017 Autumn)
  

• [Report]
  

Spatial anti-aliasing of MRI using complex independent component analysis (cICA)

• @CS229: Machine learning (2016 Autumn)
  

• Applied cICA with mutual information rate as cost function to resolve aliasing artifacts without any prior information. [Report] [Poster]
  

Professional Services

Reviewer for IEEE Transactions on Medical Imaging, Journal of Magnetic Resonance Imaging (JMRI).
Trainee Member for International Society for Magnetic Resonance in Medicine (ISMRM).