a Ph.D. student of Bioengineering at University California, Los Angeles
(UCLA),
and research student in Biomedical Imaging Research Institute (BIRI) at
Cedars-Sinai Medical Center.
AI, MRI, and 3D Imaging
I am a Ph.D. student of Biomedical Engineering at UCLA, supervised by Dr. Debiao Li, the director of Biomedical Imaging Research Institute (BIRI) at Cedars-Sinai Medical Center.
My research is focused on Super-Resolution in MRI, Dynamic MRI Reconstruction, and Multi-Organ MRI Segmentation. I received two degrees: Master of Science in BioEngineering and Master of Computer Information & Technology from University of Pennsylvania (UPenn). I am very lucky to have spent my summers as a research intern at Voxelcloud (with CEO: Dr. Xiaowei Ding), Philips Research (with principal: Dr. Minnan Xu), and MGH/HST A.A Martinos Center (with professor Dr. Iman Aganj).
More on my research and publications.
As a researcher, developer, and technology enthusiast, I am eager to bring latest techniques to biomedical engineering, aiming to let people have inexpensive, efficient, and affordable medical imaging services.
With a strong background in both biomedical engineering and computer science, I am doing my best to crack down the most uncharted challenges in magnetic resonance imaging(MRI) by translating deep artificial neural networks into biomedical science.
I am also a coding zealot. I found my passion for programming as early as I was in high school. Ever since then, I designed and built many cool pieces of stuff, from small and simple android apps to complicated parallel computing projects.
I have a love of clean and elegant design, not only for how the product shows apparently but also for the inner structure of codes and styling. As a computer science graduate, I have made a lot of different applications on variant platforms. And for a research student, I also have insights into scientific algorithm developing and implementation.
School of Engineering and Applied Science
University California, Los Angeles, CA, USA
School of Engineering and Applied Science
University of Pennsylvania, Philadelphia, PA, USA
School of Engineering and Applied Science
University of Pennsylvania, Philadelphia, PA, USA
Sino-Dutch Biomedical and Information Engineering School
Northeastern University, Liaoning, China
Designed and built novel and efficient 3D neural networks for lung CT projects; Innovative multitasking structure helps to achieve state-of-the-art performance; Supported engineering team for prototyping and feature release.
Worked on a fast Hough transformation algorithm for brain MRI
Designed and built neural networks (NN) independently to identify patients with congestive heart failure using 16 million time-series data over 140 thousand patients; achieved an AUROC of 88.55
2016 Spring term, Data Structure
2015 Fall term, Programming Languages & Techniques
Developed an automated LV segmentation method for free-breathing 4D MR images; Published on SCMR-6 and ISMRM-16
Lead in algorithm development; Applied multi-atlas label fusion (MALF) segmentation algorithm, improved accuracy