WiM Presents: Conducting Health Equity Research - Presentation and Panel Discussion
Friday 10th January 2025
Women in MICCAI (WiM) is happy to announce the third invited talk in the WiM "Health Equity in the AI Era" Webinar Series
Conducting Health Equity Research
Panelists: WiM Best Health Equity Paper Award Finalists
Thursday, January 23, 2025
5:00 - 6:00 PM UTC / 9:00 - 10:00 AM PST / 12:00 – 1:00 PM EST
Conducting research on health equity is a much-needed topic in the MICCAI community. To support the MICCAI community in conducting health equity research, the Women in MICCAI (WiM) is happy to announce the third webinar in the WiM Webinar Series.
This webinar will feature three finalists of Women in MICCAI Award for the Best Health Equity Paper at MICCAI 2024, who will present their research on health equity, and share with us their experience in conducing health equity research, from identifying the research topic to building connections with collaborators to make the research impactful for the health community. So please mark your calendars for Thursday, January 23, 2025, and join us for this interactive session.
Registration (required) is free and open to everyone.
Schedule:
Research Presentation [30min]
- Nourhan Bayasi; BiasPruner: Debiased Continual Learning for Medical Image Classification
- Vien Ngoc Dang; Mitigating Overdiagnosis Bias in CNN-Based Alzheimer’s Disease Diagnosis for the Elderly
- Kaushalya Sivayogaraj; LiverUSRecon: Automatic 3D Reconstruction and Volumetry of the Liver with a Few Partial Ultrasound Scans
Panel discussion on conducting health equity research [20min]
Audience Q&A [10min]
About the Panelists:
We have three amazing panelists who are the Winner and Honourable Mentions of Women in MICCAI Award for the Best Health Equity Paper at MICCAI 2024.
Nourhan Bayasi is a PhD candidate and Vanier Scholar at the University of British Columbia in Vancouver, Canada, specializing in AI for medical imaging. Her research advances continual learning and domain generalization to enhance healthcare applications of deep learning. Nourhan holds Master’s and Bachelor’s degrees in Electrical and Computer Engineering from Khalifa University in the UAE and brings a blend of academic and industry experience, having worked as a lecturer, lab engineer, and machine learning engineer.
Kaushalya Sivayogaraj earned her B.Sc. (Hons) in Biomedical Engineering with First-Class Honors from the Department of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka, in 2021. She is currently pursuing her M.Sc. in the same department. Kaushalya joined Synergen Technology Labs (Pvt) Ltd as a Biomedical R&D Engineer, where she focuses on the design of biomedical devices and the development of related algorithms. Her research interests lie in the field of medical image and signal processing.
Vien Ngoc Dang received her M.Sc. in Data Science in 2020 at Eurecom (France). She is currently a fourth-year Ph.D. student at the department of Mathematics and Computer Science, University of Barcelona (Spain), under the supervision of Dr. Karim Lekadir and Dr. Jerónimo Hernández-González. Her Ph.D. research focuses on advancing fairness analysis in machine learning for healthcare, with specific interests in unfair bias mitigation and explainable AI.