Co-founded and developed a website utilizing machine learning to transform playtime into collaborative writing opportunities.

Used computer vision techniques on OpenCV and Dlib to detect changes in valves in a live video feed.

I implemented AI features for ATUSA, which is a portable breast ultrasound scanner that does not require training to acquire images with the intentions that the device is more accessible and its low costs allows for more frequent monitoring of patients. I developed classification models that are part of a series of models to be used in ATUSA to improve the automated localization of lesions in 3D breast ultrasound scans as well as improve on the reproducibility of scans across different sessions for purposes of tracking changes across time. I manually annotated patient scans for regions of interest and trained models on these annotations. I evaluated and refined models to improve their accuracy and precision.

In Dr. Ho's laboratory in the Lab of Molecular Biology at the National Cancer Institute, I produced and studied second generation hYP7 CAR T-cells from four hepatocellular carcinoma patient donors from the NIH Clinical Center. Additionally, I compared 2nd and 3rd generation hYP7 and HN3 CAR T-cells to determine their cytotoxicity. I presented this project at the 2019 NIH Summer Poster Day Session.