Assistant Professor, ECE
Mobile Health Sensing, Ubiquitous Computing, Signal Processing, Biosignals, Wearable Computing, Human Computer Interaction, User Centered Design
Wang’s multi-disciplinary research combines tools from signal processing, ubiquitous computing, machine learning, biosensors, and user-centric design to change the landscape of mobile health technologies. The goal of his research is to change the information landscape we are able to acquire to improve our ability to understand – and improve – human health. Through close collaboration with clinical collaborators and world health organizations, he works on solutions that aim to make real clinical impact. His research in developing Software as a Medical Device aims to increase access to a multitude of health monitoring to low-resource. His wearable health sensing research takes a user-centric approach in creating new sensing solutions that can expand our repertoire of continuous physiological measurements and practical for integrating into a user’s daily life.
Edward Wang received his bachelor’s degree in engineering from Harvey Mudd College in 2012 and Ph.D. in 2019 from the University of Washington, where he was advised by Professor Shwetak Patel. In his dissertation work, Wang showed that Software as a Medical Device enabled by smartphone's built-in sensors has the potential for widespread disease screening and chronic disease and health management through balancing trade-offs between optimizing the sensing solution of the biomarker and addressing practical limitations of designing on real world smartphone devices.
Wang has been a recipient of the ARCS Foundation Fellowship and the NSF Graduate Research Fellowship during his Ph.D. His research is published at top-tier conferences in the Association for Computing Machinery such as UbiComp, IMWUT, CHI, and UIST, receiving numerous Best Paper awards and nominations.