Wednesday, November 28, 2018
11:00 am – 12:00 pm
Marvin Center, 402-404
Speaker: John Lach, University of Virginia
Networks of wireless sensors have emerged in recent years to address a significant and persistent challenge in healthcare and medical research – the continuous, non-invasive, inexpensive collection of high-quality patient data. Longer battery lifetimes, smaller form factors, and higher manufacturing volumes have contributed to making sensor data collection more continuous, non-invasive, and inexpensive, respectively, but progress towards the demonstration of useful, high-quality data is still lacking. Utility and quality are ultimately application-specific measures, requiring sensors to be deployed and evaluated in real application settings, collecting data on patients in-the-wild and tracking the application impact of that data. Only then can the true value of these sensors be evaluated – ultimately using improved patient outcomes and reduced healthcare costs as the metrics for such evaluation – and can future smart health sensor research be informed.
This presentation will discuss ongoing application-driven smart health research at UVA’s Link Lab. The overarching methodology includes an ongoing cycle of system development enabling application deployment informing advanced research leading to further development, all with the goal of providing useful, high-quality data as measured by the target applications.
John Lach received his B.S. (1996) degree in Science, Technology, and Society from Stanford University and his M.S. (1998) and Ph.D. (2000) degrees in Electrical Engineering from UCLA. Since 2000, he has been a faculty member in the Charles L. Brown Department of Electrical and Computer Engineering at the University of Virginia (UVA) and has held the rank of Professor since 2012. He served as Department Chair 2012-2017 and is currently serving as UVA Engineering Director of Cross-Cutting Initiatives.
His primary research interests are cyber-physical systems, embedded sensor systems, smart and connected health, body sensor networks, integrated circuit design methodologies, fault and defect tolerance, safety-critical system design and analysis, and application-specific and general-purpose processor design.