Cardiovascular healthcare today depends on in-clinic measurements taken just a few times a year — sparse snapshots of a patient’s overall well-being. Continuous monitoring can give us a much more complete picture, but merely tracking signals introduces too many behavioral unknowns to support clinical decisions. Fortunately, recent advances in context recognition and behavior analysis are creating an opportunity to transform our approach to many health conditions. By combining wearable physiological sensors with advanced algorithms, our group seeks to derive unprecedented levels of insight from continuous, ambulatory health data.
To make this vision a reality, we’re leveraging our key areas of technical expertise. Novel sensors and sensor technologies are essential to monitoring cardiovascular signals effectively in ambulatory settings. Signal processing and machine learning allow us to make sense of the raw signals, from determining fundamental measurements to extracting actionable insights and long term patterns. Finally, wearable design, from the embedded system development and hardware to the final fit and finish, allows us to combine all of this into an ergonomic, wearable package.
Scott has focused on sensors and analytics techniques that harness the untapped bandwidth of the human body for physiological interfaces to computing. Scott received an MIT Technology Review Young Innovators award for his work using electromyography on the upper forearm to detect detailed finger movement. Scott has a PhD in Computer Science from the University of Washington.
Greg is a 20+ year veteran of Microsoft, shipping products like Visual FoxPro and serving as software development lead for the Windows, Office, SQL Server, and Visual Studio ADO components. Greg has been a founding member of multiple groups focused on mobile and ubiquitous computing. Greg has a Masters in Computer Science from Stanford University.
Jonathan has spent his career building embedded systems for medical applications. In work with Intel Research, Jonathan built a mobile sensing platform for capturing human activities. He also led a group at Nokia Research integrating mobile applications and devices in the automotive industry. Jonathan has a PhD in Electrical Engineering from the University of Washington.
Miah combines expertise in computer, electrical, and bioengineering to analyze physiologic signals and make people healthier. In past work, he has developed a stroke rehabilitation system, worked for a biopharmaceutical, and leveraged distributed cortical signals for improved brain-computer interfaces. Miah has a PhD in Bioengineering from the University of Washington.
Becky has extensive experience in biomedical signal processing and modeling. In her past work she has developed sensing technologies for model-based estimation of respiratory parameters from capnography, which can be used for the diagnosis and monitoring of CHF and COPD with broadly available sensors. Becky has a PhD in Electrical Engineering and Computer Science from the Masachusetts Institute of Technology.
Moni is a leader in developing wearable and mobile products that embody cutting edge Design solutions. She led global experience design strategy at Motorola, and incubated the Band, HoloLens, and various Xbox headsets at Microsoft. Moni has a Diplom Designer FH from Fachhochschule fur Gestaltung Schwabisch Gmund and a M.A. in Industrial Design from Ohio State University.
Ron has core expertise in semiconductor, silicon, and RFID technologies. Prior to Microsoft, he has held technical positions at Motorola, HPL Technologies, was a Vice President at Impinj as well as SNUPI Technologies, and was President of R2P Solutions. Ron has a PhD in Electrical Engineering from Lehigh University.
Sumit focuses on developing interactive, machine-learning based power tools to assist users in analyzing complex data sets. He was co-inventor of Sho, the .NET playground for data, a popular scientific computing platform. Sumit is also an ardent artist, singer-songwriter, and clothing designer. Sumit has a PhD in Electrical Engineering and Computer Science from MIT.
Gabe has developed many new sensing modalities for human-computer interaction and medical applications. Winner of multiple Madrona Venture prizes for innovation, Gabe is co-founder of SNUPI Technologies, which sells the WallyHome sensor, built around his graduate work on ultra-low-power wireless sensor networks. Gabe has a PhD in Electrical Engineering from the U. of Washington.