Led development of Adrich’s IoT-enabled "Smart Tags" that capture product consumption data, integrating embedded firmware, backend pipelines, predictive models, and client-facing applications into a unified system.

Designed and implemented embedded firmware on MCUs with on-device compression and optimized BLE transmission, enabling over 10× more data capture while reducing Smart Tag cost.

Built and deployed backend data pipelines (Node.js, MongoDB), Python ML models, and React/React Native applications to deliver real-time consumption tracking, predictive analytics, and actionable insights for clients.

Developed and executed functional test protocols and risk reduction evaluation plans to evaluate material and design changes.

Explored and assessed a new validation method quantifying multi-fluid behavior using a camera integrated with computer vision and signal processing software.

Analyzed, reported, and conveyed results to all stakeholders: including project leads, internal departments, and external manufacturers to assess compliance to verification and validation standards.

Participated in an innovation Hack-A-Thon focused on bringing value to new markets and customers through brainstorming novel solutions to industry problems. Had the opportunity to collaborate with a small, very diverse team to develop a novel solution to a current challenge in the radiology field.

Performed computational fluid dynamics (CFD) of Fontan Blood Pump flow fields using Particle Image Velocimetry (PIV).

Conducted experiments to calculate the rotor speed required to achieve optimal flow performance and minimal cavitation.