• Hello & Welcome :)
  • I'm Christine Wu

    Software Engineer

  • Download CV

ABOUT ME

  • I am a Master student in Electrical Computer Engineering. My research interest is to interweave fundamental concepts of Machine Learning with interdisciplinary knowledge, design intelligent algorithms and systems, and develop scalable optimization tools. Through improvements in computation, I wish to apply them in healthcare and medicine to create portable and accessible products that can assist working medical professionals.
  • EDUCATION

  • University of Washington - Seattle Sep 2022 - Present
  • University of Illinois at Urbana-Champaign Aug 2017 - May 2021
  • RESEARCH

    UIUC Undergraduate Thesis Research

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    • Overcoming optical scattering in photoacoustic imaging with intensity-recovering deep learning model
    • Kevin Huang, Christine Wu, Chen Yun-Sheng, Zhao Yang (UIUC USR'21)
    • PowerNet strives to improve the portability and affordability of deep tissue imaging with a conditional Generative Adversarial Network that extracts structural information in ultrasound images to recover the optical scattered intensities in photoacoustic deep-tissue imaging.
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      PPTX
      VIDEO
      UIUC YSChen Lab
      Google Research

    NCKU Summer 2020 - 2021 Research Internship

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    • Cytoplasm Segmentation in Microscopy Images Using Statistical Pressure Snake
    • Gwo Giun Lee, Yi-Hsuan Chou, Wei-Hung Weng, Yi-Hua Liao, Chi-Kuang Sun, Christine Wu
    • This project is a portable melanoma skin cancer detector that classifies melasma dendritic level through mobile devices, implemented in C. Utilizing calculus gradient through statistical pressure snake active contour, cytoplasmic membrane is segmented to automate the diagnostic process.
    • NCKU Media SoC Lab

    NCKU Summer 2022 AI-Food Internship

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    • Food Image Recognition and Nutrition Estimation via Deep Learning
    • Jia-Hong Chen, Christine Wu, Gwo Giun Lee
    • AIFood is a modified 50-layer Residual Convolution Neural Network (ResNet50). The model is trained with a self-crafted AIFood database consisting of 299,143 eastern food images and 85,412 western food images. Each image is labeled with 24 ingredient categories. CogniNU is the mobile app that allows users to track nutrition intake and make suggestions to improve dietary habbits. The mobile app estimates the nutrition intake from an image uploaded by the user through the deep learning AIFood model.
    • NCKU Media SoC Lab

    Projects

    Some projects to share. Click on them Learn More!

    Programming Languages

    Application Software & Tools

    Coursework