My research focuses on developing cost-effective, portable, and patient-centric healthcare technologies with a goal of ultimately bringing clinical sensing out of the clinic. The next generation of healthcare needs to leave the confines of labs and solutions to be truly usable by everyone. Toward this goal, I am leveraging the ubiquity of modern computers, such as sensors on smartphones, wearables, and embedded devices, to address problems related to people’s health and well-being. By designing and developing hardware and software-defined AI systems, I focus on a wide range of applied sensing including mobile health sensing, biomedical sensing, and their applications in smart healthcare. I am actively developing new health diagnosis solutions using my expertise in mobile and embedded system development, signal processing, machine learning, and biomedical engineering. My work also spans other topics at the intersection of healthcare and ubiquitous computing, such as biomedical signal processing, Internet of Medical Things (IoMT), novel sensing modalities and devices, as well as on-device machine learning.