Published multiple papers in top-tier international conferences such as ICCV, AAAI, MICCAI; served as a senior program committee member for several conferences; holds multiple US patents; authored a book on deep network design for medical image computing.
Research Experience
Before joining Amazon, worked on various medical image analysis projects, including metal artifact reduction, sparse-view artifact reduction, 2D/3D image registration, cardiac ultrasound image segmentation, vertebrae identification and localization, and skin disease characterization.
Education
Received Ph.D. in Computer Science from the University of Rochester in 2019, advised by Prof. Jiebo Luo. Ph.D. research focused on deep medical image computing.
Background
Currently a Senior Applied Scientist at Amazon AWS AI Labs. Research interests include document understanding, LLM knowledge distillation, and LMM pre-training. Takes one summer intern every year.