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DESCRIPTION:Dynamic Health Policy Modeling in the Age of Big Data\n\nNathan
 iel Osgood\n\nProfessor\, Dept of Computer Science & Associate Faculty\, D
 ept of Community Health & Epidemiology at University of Saskatchewan\n\nAm
 ong his many data science contributions\, Dr. Osgood is the co-creator of 
 two novel mobile sensor-based epidemiological monitoring systems.\n\nAbstr
 act\n\nTraditional health science methods have secured great advances in t
 he duration and quality of life. Unfortunately\, a troubling crop of compl
 ex health challenges confront Canada and the world\, and threaten to stop 
 – and even reverse the – rise in length and quality of life that many take
  for granted. Within this talk\, I provide a glimpse of the promise afford
 ed by combining Data Science\, Systems Science and Computational Science\,
  particularly by using machine learning to cross-link dynamic decision-ori
 ented models with “big data” offering high volume\, velocity\, variety and
  veracity. We particularly highlight the increasing accessibility of insig
 hts secured from mobile devices to study health behavior of consenting ind
 ividuals via cross-linked sensor data and on-device self-reporting\, absen
 t the need for custom programming. Contemporary tools in this area offer s
 trong advantages for population sciences\, in supporting understanding of 
 behaviour where accurate self-reporting is difficult\, exposures to enviro
 nments and contact patterns\, in providing a mean of in-situ assessment of
  knowledge\, attitudes\, beliefs\, and perceptions\, and in understanding 
 the effects of interventions across multiple pathways. Machine learning te
 chniques can be used to link such high-velocity data with decision-oriente
 d models in a fashion that permits recurrent model regrounding\, thereby a
 llowing the models to knit together an evolving holistic portrait of even 
 latent areas of the system\, project forward likely system evolution\, and
  to be used for grounded investigation of tradeoffs between intervention s
 trategies.\n\nAbout the speaker\n\nNathaniel Osgood serves as Professor in
  the Department of Computer Science and Associate Faculty in the Departmen
 t of Community Health & Epidemiology at the University of Saskatchewan. Hi
 s research as director of the Computational Epidemiology and Public Health
  Informatics Laboratory is focused on providing cross-linked simulation\, 
 data science\, and machine learning tools to inform understanding of popul
 ation health trends and health policy tradeoffs. Among his many data scien
 ce contributions\, Dr. Osgood is the co-creator of two novel mobile sensor
 -based epidemiological monitoring systems\, most recently the 4th generati
 on Google Android- and iPhone-based iEpi (now Ethica Health) platform\, wh
 ich has been used in over 100 studies worldwide and is available in 9 lang
 uages. Dr. Osgood serves as Chief Research Advisor on the Saskatchewan Cen
 tre for Patient Oriented Research\, is the lead technical architect for th
 e cross-sectoral Saskatchewan Police Policing Analytics Laboratory\, and h
 as guided analytics that have shaped important policy and investment decis
 ions at the Saskatchewan at the Ministry of Health. Dr. Osgood has led doz
 ens of international courses in simulation modeling and health around the 
 world\, and his online videos on the subject have garnered hundreds of tho
 usands of views\, and thousands of followers. Prior to joining the U of S 
 faculty\, he graduated from MIT with a PhD in Computer Science in 1999\, s
 erved as a Senior Lecturer and Research Associate at MIT and worked for a 
 number of years in a variety of academic\, consulting and industry positio
 ns.\n
DTSTART:20190411T150000Z
DTEND:20190411T163000Z
SUMMARY:BRIDGE Webinar with Nathaniel Osgood
URL:/desautels/channels/event/bridge-webinar-nathaniel
 -osgood-295910
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