Tao has over 20 years of work experience in the field of digital health, surgical instrumentation, and machine vision. He is currently an R&D Director at Abbott Diabetes Care, leading an algorithm team in the development of data analytics and Machine Learning based solutions for diabetes care products using Continuous Glucose Monitoring (CGM) technology. Prior to Abbott, Tao has worked in the fields of ophthalmology (at Alcon) and cardiovascular medical devices (at Edwards Lifesciences), developing algorithms and software solutions for surgical instrumentation and digital health products. Tao has a Ph.D. degree in Mechanical Engineering from University of Maryland at College Park.

Abstract

Application of Transformative Technologies in Medical Devices

This presentation will walk through a few cases on how transformative technologies, such as wearables and Machine Learning, have been used in medical devices. As one storyline of cases, the evolution of blood glucose sensing devices will be discussed, from how fingerstick BGM are being replaced by minimally-invasive Continuous Glucose Monitoring (CGM) sensors, to the failed effort by Google X on developing glucose-sensing contact lens, to the ongoing development of non-invasive glucose-sensing wearable devices. The applications of Machine Learning in medical devices will also be discussed, including the success story of using Deep Neural Network (DNN) in diagnosis of diabetic retinopathy and an outlook on how Large Language Models (LLMs) may be used in healthcare.