Overview:

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 2nd CANSSI-NISS Health Data Science Workshop will be held on August 3-4, 2023 at the University of Waterloo in Waterloo, Canada. This 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. There will be two short courses held the day before the workshop at U Waterloo on August 2, 2023, details below. The two-day workshop consists of two keynote presentations, three invited sessions, a poster competition for students and new researchers, and a banquet/dinner on Day 1.

This workshop also takes place a few days before JSM 2023 in Toronto, Canada, which is only an 1h30 train commute from U Waterloo! It is also only an hour commute from the Toronto Pearson Airport. Full transportation option details below. 

The themed invited sessions will explore current approaches and new challenges in:

Statistical Methods for Precision Health 
Causal Inference for Big Health Data
AI and Health Data Science

Register on Eventbrite Here

Full Registration Price Now: ~$280 CAD/$210 USD - Visit registration details for discounted rates and NISS Affiliates Award Fund information.
Earlybird Registration Deadline was July 21st (Late Registrants get a 25% increase in registration after July 21st)
Full Registration Deadline: July 28, 2023

Workshop Links:

Registration Details

Full Agenda

• Short Courses
• Keynote Speakers
• Student and New Researcher Competition - Poster Abstract Submission Instructions

Workshop Locations 

Travel Details

Accommodation Details

Keynote speakers:

Short Courses, Wednesday, August 2nd, 2023

**Both Short Courses are held during 1-4:30pm in different rooms.

Invited sessions:

Each session 2 hours (120 minutes = four 25-min talks and 20-min Q&A)

Session 1: Statistical Methods for Precision Health 
Chair: Glen McGee, University of Waterloo 

Marzieh Mussavi Rizi,  University of Waterloo
Jeremy Taylor, University of Michigan
Eleanor Pullenayegum, U Toronto, Hospital for Sick Children
Rob Deardon, University of Calgary 

Session 2: Causal Inference for Big Health Data  
Chair: Richard Cook, University of Waterloo

Debashis Ghosh, Colorado School of Public Health
Lan Wen, University of Waterloo
Shu Yang, North Carolina State University
Mireille Schnitzer and Cong Jiang, Université de Montréal

Session 3: AI and Health Data Science 
Chair: Liqun Diao, University of Waterloo

Ali Ghodsi, University of Waterloo
Qi Long, University of Pennsylvania
Rob Strawderman, University of Rochester
Grace Yi,  Western U, Ontario
 

Organizing Committee: 

James Rosenberger, NISS / Penn State University
Lingzhou Xue, NISS / Penn State University
Yeying Zhu, University of Waterloo
Joel Dubin,  University of Waterloo