Published multiple papers in journals and conferences such as CoRR, medRxiv (Cold Spring Harbor Laboratory), CVPR; developed new deep-learning-based image registration approaches like GradICON.
Research Experience
Has extensive research experience in a wide range of topics including brain, cancer, CVPR, deep learning, diffusion, foundation model, histology, ISBI, knee, LDDMM, lung, machine learning, MEDIA, MICCAI, NeurIPS, registration, regression, segmentation, shape, topology, etc.
Background
Focuses on the design of computational algorithms to extract quantitative measures from biomedical data and other data sources. Research areas include but are not limited to image processing (e.g., obtained via magnetic resonance imaging, computed tomography, or microscopy), unstructured text, tabular data, and genomics.
Miscellany
Collaborates with experts across disciplines including statistics, applied mathematics, radiology, surgery, and epidemiology.