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SUMMARY:Intelligent Mobile Systems for an Aging World - Justin Chan\, Carn
 egie Mellon University
DTSTART:20251021T150000Z
DTEND:20251021T160000Z
UID:TALK235933@talks.cam.ac.uk
CONTACT:Cecilia Mascolo
DESCRIPTION:By 2050\, older adults will make up about 22% of the global po
 pulation\, driving an urgent need for accessible and reliable health techn
 ologies. In this talk\, I will present our work on intelligent mobile syst
 ems designed for older adults. The first leverages compact AI-enabled radi
 os for cardiovascular monitoring\, including blood pressure. The second is
  an ambient sensing system that uses smart devices to detect emergent\, li
 fe-threatening events such as cardiac arrest. The third enables low-cost h
 ealth screening using everyday earphones and wireless earbuds. Through the
 se examples\, I will show how computational and sensing techniques that ge
 neralize across hardware and operate in real-world environments can addres
 s pressing societal challenges.\n\nBio\nJustin is an assistant professor i
 n CS and ECE at Carnegie Mellon University\, where he directs the Semantic
  Signals Lab. His work focuses on AI-enabled digital health systems with a
  focus on wireless and mobile technologies. His innovations include using 
 smartphone sensors for blood clot testing\, training smart speakers to det
 ect cardiac arrests\, wireless earbuds that screen for newborn hearing los
 s\, and detection of middle ear fluid using active sonar on smartphones an
 d a paper cone. He earned his PhD at the University of Washington and his 
 work has been recognized by CACM and SIGMOBILE Research Highlights\, SIGMO
 BILE Doctoral Dissertation Award Runner Up\, and a IEEE Pervasive Computin
 g Emerging Rockstar feature.
LOCATION:Online
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