WiM Webinar- From Paper to Story: Crafting Effective Research Presentations - July 10
Monday 30th June 2025
From Paper to Story: Crafting Effective Research Presentations - Best Practices from Oral Presentation Winner and Experienced Researchers
Getting a paper accepted is only the first step in sharing your research with the scientific community. Equally important is presenting your work clearly, confidently, and effectively.
To support early-career researchers in preparing impactful oral and poster presentations, Women in MICCAI (WiM) is pleased to announce the fifth instalment of the WiM Webinar Series on “From Paper to Story: Crafting Powerful Research Presentations - Best Practices from Oral Presentation Winner and Experienced Researchers".
This session will feature a panel of experienced researchers—including faculty from Yale and UCSC—as well as past recipients of the WiM Award for Best Oral Presentation at MICCAI, who will share their insights and practical tips on crafting and delivering compelling research presentations.
Mark your calendars for Thursday, July 10, 2025 at 4:30 PM PDT / 7:30 PM EDT / 11:30 PM UTC and join us for this interactive and practical webinar!
About the Panelists
Yuyin Zhou is an Assistant Professor of Computer Science and Engineering at UC Santa Cruz. Her research interests lie at the intersection of machine learning and computer vision, with a primary focus on AI for healthcare and scientific discovery. Her contributions have been recognized with several prestigious honors, including being named a 2025 Google Research Scholar, a 2023 Hellman Fellow, a finalist for the MICCAI Young Scientist Publication Impact Award in 2022, and receiving the Best Paper Honorable Mention at DART 2022. Beyond her research, Yuyin actively contributes to the broader scientific community. She has organized over 20 workshops and tutorials at top conferences, including ICML, MICCAI, ML4H, ICCV, CVPR, and ECCV, with coverage in media outlets such as ICCV Daily and Computer Vision News. She serves as an Area Chair for CVPR, ICLR, MICCAI, CHIL, and ISBI, and is the Doctoral Consortium Chair for WACV 2025.
Nicha Dvornek is Assistant Professor of Radiology & Biomedical Imaging and of Biomedical Engineering at Yale University. Her research focuses on the development of modern machine learning methods for analysis of medical imaging data across widespread applications, including detection and diagnosis from multimodal data, processing of dynamic functional imaging data, and understanding brain-behavior relationships using neuroimaging. Nicha and her team’s work has been recognized by multiple best paper and challenger awards. She has experience shaping technical programs as co-organizer of workshops at MICCAI and ICML, area chair for MICCAI and MIDL, and reviewer for NeurIPS, CVPR, ICCV, IPMI, ISBI, and many workshops.
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.
Xinrui Yuan is a Ph.D. candidate at the Southern Medical University and a Research Assistant at the University of North Carolina at Chapel Hill. Her work focuses on analyzing cortical surface data to better understand brain structure and function. She is grateful to have been recognized with the Women in MICCAI award twice, and she remains committed to contributing to the fields of biomedical engineering and neuroscience.
Luisa Gallée is a PhD student in the Experimental Radiology Group at Ulm University Medical Center, where she develops inherently explainable computer‑vision methods for medical imaging. Her research bridges the gap between advanced AI techniques and clinical interpretability, ensuring that model reasoning aligns with expert knowledge. She investigates models that leverage diagnostic criteria for decision‑making and transparency, incorporating prototype visualization at the criteria level for fine‑grained validation. At MICCAI 2023, she was honored with the WiM Award for Best Oral Presentation.
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