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SUMMARY:Balancing Performance and Acceptability in Real-World Automated Di
 etary Monitoring - Edison Thomaz (UT Austin)
DTSTART:20210517T140000Z
DTEND:20210517T150000Z
UID:TALK157234@talks.cam.ac.uk
CONTACT:Lorena Qendro
DESCRIPTION:*Abstract:* Over the last decade\, smartphones and wearable de
 vices have become a powerful source of sensor data driving numerous mobile
  health applications. An active area of research in this space has been au
 tomated dietary monitoring (ADM)\, which addresses the problem of tracking
  what a person eats using passive and continuous sensing. A significant ch
 allenge in realizing a practical ADM system\, however\, has been striking 
 a balance between acceptability and performance in real-world environments
 . In this talk\, I will present several research efforts from my group aim
 ed at creating an eating detection system that is high-performing in natur
 alistic setting while also being acceptable from a human-centered perspect
 ive. The trajectory of our research is characterized by the design of incr
 easingly smaller and more compact ADM sensing systems\, combining novel se
 nsing and computational methods. Our approach has emphasized on-body preci
 sion sensing and targeted remote sensing\, allowing us to explore ADM in v
 arious form-factors and configurations\, including as facial stick-on sens
 ors and intra-orally.\n\n\n*Bio:* Edison Thomaz is an Assistant Professor 
 in the Department of Electrical and Computer Engineering at The University
  of Texas at Austin\, where he directs the Human Signals Laboratory. His r
 esearch focuses on human-centered machine perception\, the study of how to
  combine sensing and computation to build systems that can reason about\, 
 and make sense of humans and the human experience. A core area of interest
  is studying systems and methods for recognizing and modeling health-relat
 ed activities and context. This work intersects with several disciplines\,
  from ubiquitous computing and HCI to human-centered machine learning and 
 signal processing. At UT Austin\, he is a member of the DICE and BioECE tr
 acks and belongs to the Wireless Networking and Communications Group (WNCG
 )\, an industry affiliates program. He is an Associate Editor of the ACM P
 roceedings on Interactive\, Mobile\, Wearable and Ubiquitous Technologies 
 (PACM IMWUT) and has served on numerous program and organizing committees 
 for both ACM and IEEE conferences (e.g.\, Pervasive Health\, CHI\, ISWC). 
 He presently co-directs the Life Sensing Consortium (LSC)\, a multi-discip
 linary\, multi-university collaborative network of researchers who use sen
 sing technologies to conduct interdisciplinary sensing research to promote
  positive life outcomes. Prior to his Ph.D.\, Edison held industry positio
 ns at Microsoft and France Telecom. He holds a bachelor's degree in Comput
 er Science from UT Austin\, a master's from the MIT Media Lab and a Ph.D. 
 in Human-Centered Computing from Georgia Tech.\n 
LOCATION:Virtual (see abstract for Zoom link)
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