Founding team member that started and lead a team of 6 engineers to build driver and rider apps from scratch to 1k daily users and servicing 100,000+ trips. Worked in a fast pace sprint team environment across the entire stack including Kubernetes, Docker, Go Lang, Flutter, and React. Designed and developed significant portions of the companies backend code base, and connected them to the company dashboard, and mobile applications.

Tauopathies are hypothesized to be a primary cause of Alzheimer's disease. Labeling tau in whole slide images is a task requiring high expertise and lots of time. Project successfully developed a Deep Learning solution to segment and quantify important cells in brain scans. It will save doctors many ours of work and enable future quantitative research on the results. Utilizes PyTorch on MIT's supercomputer for preprocessing, training, and evaluating models.

Researched person re-identification in camera surveillance systems. Implemented state of the art deep neural network models and modified them to work in given environment. Used a supercomputer to train and evaluate many data set and model configurations. Developed innovative image labeling application using deep neural network which reduced the amount of time to label a dataset by five times.

Designed and developed a website to visualize metrics produced by a company product. Implemented an interface that let users set rules to predict when a device would fail, so the company could respond accordingly. Created a REST API for the backend, to provide a portable solution that could eventually be used across many platforms. Build with React stylized with Material UI for the frontend and Nodejs, Expressjs, and MongoDB for the backend on top of the Microsoft Azure environment.