Postdoc Research Day

About Postdoc Research Day

The PDA hosts an annual research day featuring seminars, presentations, posters, and writing contests. This popular, fun and engaging day creates the opportunity for postdocs to promote collaborations and foster a sense of community.  


As one of the most popular research seminars at SFU, Postdoctoral Research Day offers postdocs the opportunity to showcase their work, promote collaborations, and foster a sense of community.

This year, PDA Research Day will feature a lively panel discussion and inspiring resource talks as well as 10 minute research presentations and poster sessions.

Research Day 2022 will be a hybrid event. While it is encouraged to participate in person, there are opportunities for remote virtual participation and presentations.


Watch the talks, explore the exhibits, be part of the community. Come and learn about how SFU Postdocs are changing the world!

All postdocs, research associates, graduate students, faculty and interested members of the community are welcome to join this free event.

Annual Research Days

Congratulations to the 2022 Award Winners

Poster Winners

1st Prize

Muhammad Zohaib Anwar, Faculty of Health Sciences
Using Genetic Diversity of SARS-CoV-2 to evaluate the effectiveness of specific travel measures in mitigating public health risks during the COVID-19 pandemic 

2nd Prize

Numaira Obaid, Mechatronic Systems Engineering
Comparing whole cord versus constituent material models in simulations of spinal cord injury (SCI)

Presentation Winners

1st Prize

Andrew Cheng, Department of Linguistics
The Prevalence of Vocal Fry in Mothers Speaking to Infants

2nd Prize

Roger Ashmus, Department of chemistry
Development of biochemical tools for the advancement of diagnosis and therapeutics for lysosomal storage diseases

3rd Prize (tie)

Noha Atef,  Faculty of Communication, Art & Technology
Health & Influencers: Doctors Who Vlog

Hansol Park, Department of Mathematics
The Watanabe-Strogatz transform and constant of motion functionals for kinetic vector models