- Community Outreach
- May 6-8, 2021 from 10:00am to 5:00pm
May 6-8, 2021
Nowadays, statisticians and health data scientists actively work together on the frontier of biological, medical, and public health research. The transdisciplinary collaboration not only develops the modern foundations of Health Data Science but also accelerates the pace of scientific discovery and innovation.
The First CANSSI-NISS Health Data Science Workshop will be held virtually on May 7-8, 2021, with pre-workshop short courses on May 6th. The workshop brings statisticians and health data scientists from the U.S. and Canada together to explore current approaches and new challenges for learning Big Data in Health Data Science.
The two-day workshop consists of two keynote presentations, four invited sessions, a poster competition for students and new researchers, a late-breaking session on AI and Health Data Science, and a networking happy hour. The themed invited sessions will explore current approaches and new challenges in
(i) Statistical Issues with COVID-19,
(ii) Statistical Problems in Imaging and Genetics,
(iii) Causal Inference for Big Health Data, and
(iv) Methods for Electronic Health Data.
Conference Registration (all prices in US $)
$50 registration, $25 for students. Select the registration options on the right hand side of the page, check the box ‘I am not a Robot” and then “Register for this Event”.
Short Course Registration (all prices in US $)
$35 registration per short course. Select the registration options on the right hand side of the page, check the box ‘I am not a Robot” and then “Register for this Event”. Do this for each course you are interested in attending, (maximum one short course per AM or PM session).
Students from NISS Affiliates – this event is Affiliate Award Fund Eligible. (Is your institution a NISS Affiliate? Check the List of NISS Affiliates.)
Students from CANSSI Partners or Institutional Members – please send Randy Freret an email at email@example.com to request free short course registration. (Is your institution a CANSSI Partner or Institutional Member? Check the CANSSI list.)
Joel A. Dubin (University of Waterloo)
James L. Rosenberger (Penn State University and National Institute of Statistical Sciences)
Lingzhou Xue (Penn State University and National Institute of Statistical Sciences)
Yeying Zhu (University of Waterloo)