Taylor Bernt

Led architecture design and implementation of Rust-based haptic surgeon console, which was used in multiple surgeries and surpassed the current system in key metrics. Collaborated to architect a next-generation surgical robotic system built on NVIDIA IGX that performed the first pre-clinical remote surgery using Holoscan Sensor Bridge.

Proposed and independently developed a novel IMU-based pose estimation algorithm, including simulation and embedded deployment for an early-stage surgical robot prototype. Designed and implemented a novel high-speed comms protocol for the M487 and ATSAMG55 microcontrollers.

Designed machine learning models to aid in surgical procedures. This involved understanding the specific needs of surgical applications and translating them into effective model designs.

Designed machine learning models to cluster and classify client data. This role focused on leveraging data science techniques to extract insights from large datasets.

Designed and maintained production code, ensuring high quality and adherence to strict coding standards. Followed strict code linting, coverage, and testing guidelines to ensure robust and reliable software.

Worked on a small team to create an app and website from scratch that assists families in finding free resources around their city. The developed application achieved over 20,000 app downloads.

Completed a Bachelor of Science in Computer Science with a minor in Mathematics. Gained a strong foundation in computer science principles and mathematical concepts.