Since its launch in 2011, the PDF Travel Awards have helped many UBC PDFs attend conferences to present their work, enriching their PDF experience and helping anchor them within the academic world. Please read below to find out more about past award recipients.
|
Name |
Department, Faculty |
Conference - Date Attended |
Location |
|---|---|---|---|
| Quarter 1: | |||
| Dr. Huah Shin Ng | Medicine; Medicine | ACTRIMS Forum 2020 - February 2020 | Palm Spring, FL |
| Quarter 4: | |||
| Dr. Wendy Pringle | Pediatrics; Faculty of Medicine | Society for Medical Decision Making - October 2020 | Virtual |
| Dr. Timothy Sipkens | Mechanical Engineering; Applied Science | American Association of Aerosol Research 38th Annual Conference - December 2020 | Virtual |
2020 Q1
ACTRIMS Fourm 2020 - February 2020
I am very fortunate to be granted a travel award from the Faculty of Medicine-PDFO to attend the ACTRIMS Forum 2020 held in West Palm Beach, United States. The travel award has facilitated the training of my postdoctoral research in several aspects. I have gained a deeper understanding of a highly complex, chronic disease, multiple sclerosis (MS), as a wide range of topics were covered during the 3-day conference. I have made excellent use of the networking opportunities to connect with other MS researchers and met up with trainees across North America. I have also gained further insights into knowledge translation and communication. I believe the knowledge that I have learnt from various oral and poster presentations will help me in formulating relevant research questions and facilitating the translation of research findings into informing clinical practice and health policy, and ultimately making a difference to people living with MS. Finally, I am very pleased to have the opportunity to present the findings of my three studies to a broad range of audiences involving in MS research. I find the comments and advices given by other researchers are extremely valuable in helping me to refine the design of my research studies.
2020 Q4
Society for Medical Decision Making - October 2020
At this conference I presented an abstract, titled “Informing Vaccine Decisions in the Context of Informed Choice: A Qualitative Study of Canadian Midwives” drawn from our ongoing study of vaccine hesitancy and perinatal care providers. This study explores how Canadian midwives discuss universally-recommended vaccines in pregnancy with clients in the context of the evidence-based Informed Choice model of decision making. Informed Choice, a model of decision making that emphasizes collaborative and non-authoritarian information exchange, is one of the core principles of the Canadian Midwifery Model of Care. Our recommendation is that in order to support midwives in vaccine counseling, information resources should be tailored to their Informed Choice model of care, providing adequate scientific detail while using accessible and empowering language.
The meeting provided my co-authors and I the chance to share the results of our work and solicit feedback from experts in medical decision making. For me, the conference was an excellent opportunity to learn from scholars working in the area of the psychology of decision making, and I participated in two short courses, an “Introduction to the psychology of decision making” and “Shared decision making and patient decision aids.” These will be valuable assets as our project progresses towards designing implementations to improve vaccine uptake, as well as in my own professional development by broadening my methodological grounding.
American Association of Aerosol Research 38th Annual Conference - December 2020
The Annual Conference of the American Association for Aerosol Research (AAAR) is one of the premier conferences in the field of aerosol science, with discussions including health implications, climate impact, and fundamental characterization. My primary contribution considered a new tool to interpret transmission electron microscopy (TEM) images, which directly show the shape and size of the particles that make up the aerosol. Deriving quantitative particle characteristics from these images requires robust analysis techniques. Unfortunately, soot, a carbonaceous aerosol produced by combustion with significant health and climate impacts, features complex aggregated structures, low contrast images, and high amounts of noise. This work employed k-means segmentation, an unsupervised machine learning technique, to yield a fully automated segmentation of soot particles in TEM images. This both improves accuracy and increases the number of particles that can be practically characterized, thereby improving our understanding of these particles and their impact. In addition to my primary contribution, I was also a second and supporting author on a second contribution discussing the filtration of aerosols by face masks constructed of common materials, ranging from knitted fabrics to paper towel, a pertinent topic given the ongoing pandemic.