• Developed software for a low-cost otoacoustic emissions (OAE) device in order to easily and accurately identify pediatric hearing loss in developing countries.

• Implemented signal processing algorithms on a Raspberry Pi through the use of Python, NumPy, SciPy, and Matplotlib in order to analyze OAEs and improve the signal-to-noise ratio.

• Developed a mobile Android application version of the device utilizing Java, Android Studio, and Firebase.

• Worked as Co-Head Course Assistant of Data Structures.

• Developed automated grading scripts, improved course programming projects, held review sessions, assigned grading to course assistants, and held office hours.

• Developed remote gait analysis tool for neurological patients in collaboration with cross-disciplinary design team.

• Utilized Swift, Firebase, and Apple's CareKit framework for iOS application. Processed motion data from iOS device hardware with Apple’s CoreMotion API.

• Recipients of the VentureWell Stage 1 E-Team Grant, Finalists in the Johns Hopkins Healthcare Design Competition.

Team: Stories Creation Core