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SUMMARY:Embracing Ubiquitous Technology to Complement\, Scale\, and Extend
  Traditional Healthcare - Alex Mariakakis\, University of Toronto
DTSTART:20240423T150000Z
DTEND:20240423T160000Z
UID:TALK204478@talks.cam.ac.uk
CONTACT:Cecilia Mascolo
DESCRIPTION:*ABSTRACT*: Traditional healthcare is centered around face-to-
 face interactions between patients and clinicians. While these human relat
 ionships are important for establishing empathetic and ethical care\, they
  limit the extent to which healthcare can be accessed and delivered. Ubiqu
 itous technologies like smartphones and wearables can augment traditional 
 healthcare workflows by increasing the access that people have to health-m
 onitoring tools. Rather than viewing healthcare as a reactive endeavor\, w
 e can work towards proactive approaches like preventative screening\, cont
 inuous disease management\, and informative visualizations that empower al
 l stakeholders to make informed and timely decisions. To achieve this visi
 on\, my research group applies signal processing and machine learning on s
 ensor data to measure vital signs and infer symptoms. Since these technolo
 gies may sometimes be intended for people without medical training\, my gr
 oup also explores how such tools should be designed to achieve clinically 
 relevant goals. In this talk\, I will highlight three projects: (1) acoust
 ic cardiac sensing with earbuds\, (2) passive speech analysis for respirat
 ory monitoring\, and (3) accurate and informative menstrual health trackin
 g.\n\n*BIO*: Alex Mariakakis is an Assistant Professor in the Department o
 f Computer Science at the University of Toronto and an Affiliate Scientist
  at Techna. He runs the Computational Health and Interaction (CHAI) lab\, 
 which leverages ubiquitous and emergent technologies to address problems r
 elated to people’s health and wellbeing. His research not only creates n
 ew sensing technologies for measuring physiological\, behavioral\, and con
 textual health indicators\, but also examines the implications of these te
 chnologies in people’s hands. Alex and his research group deliver innova
 tive solutions using expertise in multiple subareas of computer science\, 
 particularly machine learning\, signal processing\, computer vision\, and 
 human-computer interaction.\n \nAlex received his Ph.D. from the School of
  Computer Science and Engineering at the University of Washington. As a st
 udent\, he received the National Science Foundation Graduate Research Fell
 owship\, the Qualcomm Innovation Fellowship\, and the Gaetano Borriello Ou
 tstanding Student Award at UbiComp 2018. His work has garnered multiple Be
 st Paper Awards at ACM venues (CHI\, COMPASS) and significant attention fr
 om media outlets ranging from the BBC to National Geographic.
LOCATION:Online
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