I am a PhD student of computer science in Johns Hopkins University. My research interests include transparent systems, medical imaging and computer vision. I have research experience about transparent deep learning systems for both 2D and 3D medical images; both radiological and pathological images; both classification and detection problems, with both PyTorch and Tensorflow.
Download my resumé.
PhD in Computer Science, 2018-present
Johns Hopkins University
M.A. in Statistics, 2016-2017
BSc in Physics, 2012-2016
3D scene style transfer with 2D style image by differential rendering:
Symmetric learning for Fracture Detection in Pelvic Trauma X-ray:
Deep Hierarchical Multi-label Classification of Chest X-ray:
Lung nodule detection in CT images:
The Need for a More Human-Centered Approach to Designing and Validating Transparent AI in Medical Image Analysis - Guidelines and Evidence from a Systematic Review.
An interpretable classification of genetic information for UM prognostication with cell composition analysis.
A two-stage hierarchical multi-label classification algorithm for chest X-ray abnormality classification.
Automatic ROI extraction for UM cytopathology images with unsupervised clustering and human interaction.