Stony Brook University, Digital Radiology Imaging Lab:

My current project involves using a diffusion-based deep learning approach to improve breast image quality, particularly for digital breast tomosynthesis. This project aims to enhance denoising without degrading microcalcification features.

New York Proton Center:

 My first project involved analyzing the methods of performing in vivo dosimetry for our proton FLASH mouse experiments. This work used a strip ion chamber array (SICA) detector.

My second project involved developing a workflow and toolkit for proton Bragg peak FLASH treatment planning in Eclipse. This toolkit automatically calculates and designs field-specific range compensators, creates sparse conformal spot maps, and performs inverse optimization with minimum MU constraints to ensure high beam current. This was developed primarily in Python using PyESAPI.

Massachusetts General Hospital, Radiation Oncology Research Lab:

My previous project at MGH looked at quality assurance of the deformable image registration conducted for an adaptive proton therapy workflow. This needed to be fast and accurate in order to meet with the needs of adaptive proton therapy.