Awarded an NIH NIBIB R21 Trailblazer grant on 'Interpretable Deep Learning Models for Analysis of Longitudinal 3D Mammography Screenings'.
Served as Area Chair for MICCAI 2024 and MIDL 2024.
Joined editorial boards of Computerized Medical Imaging and Graphics (CMIG) and SPIE Journal of Medical Imaging (JMI).
Appointed Honorary Elections Officer for the 2023 Women in MICCAI Board.
Mentored students to publish and win awards at top conferences including MICCAI, IPMI, ISBI, and MIDL (e.g., 1st and 3rd places at CXR-LT Challenge MICCAI 2024, Runner-up Best Oral Paper at IPMI 2025).
Published in high-impact journals such as Medical Image Analysis and IEEE Transactions on Medical Imaging.
Background
Assistant Professor in the Department of Radiology & Biomedical Imaging at Yale School of Medicine, with a secondary appointment in the Department of Biomedical Engineering at Yale School of Engineering and Applied Sciences.
Develops algorithms for medical image processing and analysis.
Current research focuses on deep learning applications for functional MRI analysis, motion correction in dynamic PET imaging, and digital breast tomosynthesis (3D mammography) for breast cancer detection.
Trained as a biomedical engineer; research spans techniques from Bayesian inference to modern machine learning.
Biomedical applications include brain image registration, particle reconstruction for cryo-electron microscopy, functional neuroimage analysis, and neuroprediction.