Hyeonwoo Lee
Research and Engineering in Deep Learning
I have expertise in research, application, and libraries of computer vision and deep learning.
My current focus is on applying machine learning/deep learning algorithms for healthcare applications.
I have developed detection, segmentation, classification, registration, and generative models for various modalities including MR, ultrasound, and microscopic images.
I am passionate about expanding my knowledge in personal healthcare and machine learning software development.
Donwload Resume
Current Position
AI Scientist
Philips
Ultrasound AI group
Philips
Ultrasound AI group
Education
Master in Biomedical Engineering, 2019
Cornell University
Bachelor in Biomedical Engineering, 2017
University of Rochester
Cornell University
Bachelor in Biomedical Engineering, 2017
University of Rochester
Professional Experiences
July 2019 - Current
AI Scientist
Philips, Ultrasound AI group
- Development and application of machine/deep learning algorithms to biomedical and physiological data.
- Developed real-time detection + segmentation model for the ultrasound exam guidance.
- Designed an automated FAST exam reporting workflow to streamline clinician quality assessment.
July 2018 - July 2019
Scientific Data Engineer
Allen Institute for Cell Science, Image-based Assay Development team
- Developed computer vision open source toolkit for microscopic cell images, Allen Cell Structural Segmenter.
- Researched & Developed deep learning based object detection, segmentation and gernative models.