Computer Science Colloquia
Wednesday, February 18, 2015
Jason Wiese, Carnegie Mellon University
10:45 AM, Rice Hall, Rm. 242
HOST: Jason Lawrence
Enabling an Ecosystem of Personal Behavioral Data
Smart homes, robotic assistants, intelligent agents, connected health, and the internet of things are all compelling visions for the future of computing rapidly advancing from dream to reality. To enable the full potential of these diverse computing advances, applications need a rich representation of the user – this information is essential for making systems both intelligent and intelligible. However, a holistic model of a user’s data remains elusive, significantly limiting the real-world utility of such systems. Companies like Facebook, Google, and Amazon have fragmented views of users’ behavior, extrapolated from personal data in those services (e.g., Facebook models what Facebook users do when they are using Facebook). Drawing on my experience developing research systems that generate, interpret, and employ personal data, I describe the design and implementation of Phenom, a web service that simplifies aggregation, interpretation, and access control for small data in a flexible, scalable, and privacy-sensitive way.
Bio: Jason Wiese (http://jasonwiese.net/) is a doctoral candidate at the Human-Computer Interaction Institute in the School of Computer Science at Carnegie Mellon University working with Jason Hong and John Zimmerman. He builds and studies systems that generate or leverage personal data. In 2014 Jason was named a Yahoo Fellow in recognition of this work. He earned his B.S. in Computer Science with a minor in Cognitive Science from the University of California, San Diego. During his time at Carnegie Mellon, Jason has collaborated with researchers at Microsoft Research, Fuji Xerox Palo Alto Laboratory (FXPAL), and Yahoo Labs.