Although we have successfully created smaller, faster, and cheaper computer devices, several adoption barriers remain to realize the dream of Ubiquitous Computing (Ubicomp). By lowering these barriers, we can seamlessly embed human-computer interfaces into our home and work environments. My work focuses on developing highly integrated hardware/software sensing systems for Ubicomp applications using my expertise in embedded systems, low-energy hardware design, and sensing, in addition to integrating communications, signal processing, and machine learning. In thistalk, I will present my research on ultra-low-power indirect sensing approaches for both on- and off-body applications. First, I will discuss how the conductive properties of the human body can be leveraged to enable novel human-computer interactions. Next, I will discuss my work on using the existing infrastructure in buildings to reduce the number of sensors required and to reduce the power consumption for many Ubicomp applications. Finally, I will discuss my current work in on-body, non-invasive health sensing systems. By continually working on application-driven interdisciplinary research, we can lower the adoption barriers and enable many new high-impact application domains.
Gabe Cohn is a Ph.D. candidate in Electrical Engineering in the Ubiquitous Computing (Ubicomp) Lab at the University of Washington, advised by Shwetak Patel. His research focuses on (1) designing and implementing ultra-low-power embedded sensing systems, (2) leveraging physical phenomena to enable new sensing modalities for human-computer interaction, and (3) developing sensor systems targeted at realizing immediate change in high-impact application domains. He was awarded the Microsoft Research Ph.D. Fellowship in 2012, the National Science Foundation Graduate Research Fellowship in 2010, and 6 Best Paper awards and nominations. He is the co-founder of SNUPI Technologies (www.wallyhome.com), a sensor and services company focused on home safety, security, and loss prevention. He received his B.S. with honors in Electrical Engineering from the California Institute of Technology in 2009, where he specialized in embedded systems, computer architectures, and digital VLSI.