Hello, World!
I am

Yuhua Chen

a Ph.D. student of Bioengineering at University California, Los Angeles,
and research student of Biomedical Imaging Research Institute at Cedars-Sinai Medical Center.
My area includes deep learning, magnetic resonance imaging(MRI) and medical image analysis.

About Me

  • Name: Yuhua (Bill) Chen
  • University: UCLA
  • Laboratory: BIRI @ Cedars
  • Address:
    8700 Beverly Blvd.
    PACT, Suite 800
    Los Angeles, CA 90048
  • Email: Yuhua.Chen@cshs.org

Who I am ?

I am a researcher/developer/technology enthusiast, eager to bring latest techniques to biomedical industry, aiming to let people have easily accessible, more accurate, personalized, and affordable healthcare service.

With a strong background in both biomedical engineering and artificial intelligence, I am doing my best to crack down the most unsolved and challenging issues in magnetic resonance imaging(MRI) by translating deep artificial neural networks a.k.a deep learning into biomedical science.

I am also a coding zealot. I found my passion for programming when 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.

What I Do ?

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 application on variant platforms. And for a research student, I also have insights of scientific algorithm developing and implementation.

  • Distributed System
  • Deep Learning
  • Full Stack Web Application
  • Image Segmentation / Recognition
  • Cloud Computing
  • MRI Imaging
  • Mobile App Development
  • Natural Language Processing

Resume

Education

  • 2016

    Doctorate of Philosophy

    Bioengineering Department

    School of Engineering and Applied Science,
    University California, Los Angeles, CA, USA

  • --

    Master of Computer & information Technology

    Computer & Information Science Department

    School of Engineering and Applied Science,
    University of Pennsylvania, Philadelphia, PA, USA

  • --

    Master of Science in Bioengineering

    Bio & Biomedical Engineering Department

    School of Engineering and Applied Science,
    University of Pennsylvania, Philadelphia, PA, USA

  • --

    Bachelor of Science

    Biomedical Engineering Department

    Sino-Dutch Biomedical and Information Engineering School,
    Northeastern University, Liaoning, China

Experience

  • --

    Research Student Intern

    Massachusetts General Hospital, Boston, MA

    Implemented a fast Hough transformation algorithm in c++ program to create Brain MRI Tractography from MRI diffusion image (DWI)

  • --

    Research Scientist Intern

    Philips Research North America, Cambridge, MA

    Big data analysis on over 15 million hours data from 150 thousand ICU patients to predict comorbidities
    Designed and built neural networks with CNN and RNN (LSTM) in Keras, scikit-learn python packages
    Preliminary results had an 88.5 AUROC in predicting congestive heart failure patients, which is excellent for clinical application

  • --

    Graduate Teaching Assistant

    University of Pennsylvania, Philadelphia, PA

    2016 Spring term, Data Structure CIS Department
    2015 Fall term, Programming Languages & Techniques, CIS Department
    Jobs includes recitation, course reviews, office hour, and assignment/exam grading.

  • --

    Summer Research Intern

    Cedars-Sinai Medical Cenßßßter, Los Angeles, LA

    Developed the atlas-based image segmentation algorithm to analyze the cardiac function from MRI. Applied image registration for MOCO to improve imaging quality and cardiac function assessment
    Relevant abstracts published on SCMR 2016 and ISMRM 2016

  • --

    Research Intern

    Samsung Advanced Institute of Technology, Beijing, China

    Leading researcher in algorithm development at Whole-Heart Medical Image Segmentation group. Applied nonrigid registration and atlas-based segmentation to goal mean error distance of 0.6 mm. GPU Parallel Computing (CUDA) is used to accelerate metric computing in segmentation algorithm

Skills

Map Reducing

82%

Web App

74%

Cloud Comp.

83%

Mobile App

68%

Deep Learning

91%

Image Analysis

82%

NLP

42%

MRI techniques

77%

More skills

Creativity
Programming
Research
Entertainment
Management
Motivation

Works

Coming soon

5

Years of Exploration

651

Joyful moments

161202

Lines of code

1302

Cups of Coffee

Latest Post

Together we can build a better future

Get in touch

Send me a message
Address/Street 116 N. Robertson Blvd.
Pacific Theatres, Suite 800
Los Angeles, CA 90048
Phone Number Phone: 310-423-7766
Fax: 310-248-8682