Created a real-time React.js dashboard to monitor patient status, facilitating data-driven decisions and enhancing the efficiency of medical trials.

Built RESTful API services with 100% unit test coverage, ensuring reliable data and seamless business logic integration across platforms.

Built a full-stack web application with Next.js, funded by NIH, to help medical professionals visualize and understand the inner workings of machine learning models, and collect feedback on model explainability.

Established a CI/CD pipeline using Fastlane and GitHub Actions, cutting software deployment time by 50% for both mobile and web applications.

Designed a PostgreSQL database for time-series data, hosted on Google Cloud, to enhance data management across development stages.

Implemented a health monitoring system using Sentry.io, significantly reducing production downtime through rapid error detection and tracing.

Integrated an analytics funnel in front-end applications, increasing user engagement by 25% through data-driven optimizations.

Conducted a wearable device benchmark using statistical methods in Python, directly informing device selection and protocol development.

Engineered native mobile apps for Android and iOS for wearable devices, ensuring reliable data collection using various protocols.

Sourced materials and vendors for wearable IoT devices, ensuring compliance with medical standards and enhancing product safety.

Created UI wireframes and prototypes, identifying key features through user trials, optimizing user experience.

Built a mobile app for wearable devices, facilitating seamless Bluetooth data reception and local storage in collaboration with embedded engineers.

Designed and built web applications, visualizing user feedback and collected data, informing product iteration decision making.

Collected and tagged data with wearable devices, trained an LSTM neural network activity classifier, and demonstrated results on a web application.

Design of minor components to improve the production process, with CAD and 3D-printing.

Detailed documentation of a maintenance process, and analysis of the results to suggest improvements and new production line layout.