Created multi-level machine learning models which differentiate between various types of Parkinsonism using diffusion MRI and clinical data gathered from an international team of neuroscientists and neurologists.

Deployed models and output classification reports for clinicians as a tool to aid in the diagnosis and treatment of patients with Parkinsonism.

Responsible for documenting design decisions, writing testable, extendable code and automated tests, and creating pipelines for continous integration and deployment of software using tools including C#, React/Redux, SQL, Docker, and Kubernetes.

Participated in department interview process and mentor new developers through onboarding, peer programming and code reviews.

Led department's Agile Metrics initiative; an ETL pipeline for collecting, transforming and visualizing data from our project tracking, source control, and build tools in order to make data-driven decisions and to track and improve the quality, accuracy, and efficiency of our code and processes.