• Write multithreaded C++ 17 code to develop the real-time, low-latency, 3D rendering-based application for the first FDA-approved dental implant surgery robotics system, Yomi:- designing an intelligent hardware recognition system to enhance surgery efficiency, by utilizing an open-source deep learning package- building a multi-threaded interface on the main application to communicate with the hardware recognition system using an open-source networking library- developing a novel surgery accessibility detection system which reduces surgery failures- integration of surgical instrument motor controls and feedback into the application so that the surgeon can directly control the instrument from the application- addition of new surgical workflows and a new class of medical device, the YomiLink Arch, to seamlessly support full-arch surgeries.• Expanded the functionality of the CT image registration algorithm to support a wider range of surgery types and more flexible combinations of hardware accessories used for imaging. The algorithm is used to transfer coordinates between the CT image and the robot for accurate positioning of the dental implant.• Developed a tool used by the hardware team to develop new hardware accessories used for registration.• Contributed to 3 major software releases.

Developed software algorithms with C++ 17, ITK and VTK to auto-detect the shape of dental arch and the occlusal planes from CT scans, enabling dental surgeons to plan a dental implant using the company’s robotic system more efficiently

Conducted mathematical modeling research which led to a publication that has received 21 citations: https://www.sciencedirect.com/science/article/pii/S1053811920308806

Brain & Mental Health Laboratory