MSB Webinar: Panel Discussion - Navigating Reviews & Rebuttals

Wednesday 2nd April 2025

Hear best practices from outstanding reviewers

Ae you curious about the secret behind high-rated MICCAI papers? Ever wondered why some papers consistently receive great reviews while others struggle? How can you transform reviewer feedback into a stronger submission?

The MICCAI Student Board is excited to invite you to the first Panel Discussion of the MSB Webinar Series 2025. Join us on Tuesday, April 8th, 2025, for an interactive session featuring valuable insights into the MICCAI paper review process, firsthand experiences from expert reviewers, and practical tips for crafting powerful rebuttals.

This webinar is especially tailored for students and early-career researchers aiming for successful submissions to MICCAI. Don’t miss your chance to learn directly from our experienced panelists and elevate your research submission strategy!

Tuesday, April 8th, 5:00 PM UTC / 10:00 AM PDT / 1:00 PM EDT

Register

About the Panelists

Ajibola Oladokun, PhD Candidate, University of Cape Town - Ajibola Oladokun was recognized as an Outstanding Reviewer for MICCAI 2024. Furthermore, his paper titled “SpeChrOmics: A Biomarker Characterization Framework for Medical Hyperspectral Imaging” was accepted for oral presentation at MICCAI 2024. He is a final year PhD candidate in Biomedical Engineering at the University of Cape Town, South Africa. He holds an MSc in Microprocessor and Control Engineering from the University of Ibadan, Nigeria, and a B.Eng. in Electronics and Electrical Engineering from Osun State University, Nigeria. His PhD thesis focuses on the Quantitative Characterization of Tuberculin Skin Test Indurations using Hyperspectral Imaging to Enable Automated Latent Tuberculosis Screening. Additionally, he works as a research engineer at IMT Atlantique.

Benjamin Billot, Assistant Professor, Inria - Benjamin Billot obtained a degree in electrical and computer science engineering from CentraleSupélec, France and an MSc in neurotechnology from Imperial College London in 2016. He then pursued a PhD at University College London under the supervision of Dr. Juan Eugenio Iglesias in computer vision, where he developed a domain-randomization strategy for the automated segmentation of brain MRI of any domain (SynthSeg). He later joined Prof. Polina Golland at MIT to work as a postdoctoral researcher on the use of equivariant networks for motion tracking in fetal MRI time-series. Benjamin is now a researcher at Inria, Sophia-Antipolis, France, where he works on data representation and generative models for robust analysis of medical images with a special focus on robustness and interpretability to ensure reliable translation of modern algorithms to the clinic.

Finn Behrendt, PhD Candidate, Hamburg University of Technology - Finn Behrendt is a researcher specializing in medical image analysis and generative AI. He is currently completing his PhD at the Institute of Medical Technology and Intelligent Systems at TU Hamburg. His research focuses on medical imaging with deep learning and spans areas such as image synthesis and analysis, with a particular focus on anomaly detection. Finn has contributed to several research collaborations and clinical projects and is passionate about developing practical tools that support clinicians. He has published in top-tier conferences and journals, successfully participated in international challenges, and was recognized as an Outstanding Reviewer for MICCAI 2024. In addition to his academic work, Finn is currently exploring the applications of LLMs in medical AI while actively contributing to open-source projects.

Yixuan Wu, Postdoctoral Fellow, Johns Hopkins University - Yixuan Wu is currently a postdoctoral fellow in the Laboratory for Computational Sensing and Robotics (LCSR) at Johns Hopkins University (JHU), and a special volunteer at the National Institutes of Health (NIH). He received Ph.D. in Computer Science and M.S. in Robotics from JHU. Yixuan’s research interest in engineering led him to venture into the biomedical field, where he received training in robotics and medical imaging. His research focuses on advanced computational ultrasound and photoacoustic imaging, with an emphasis on image processing, image analysis, and instrumentation. By unlocking ultrasound imaging’s potential and promoting its widespread adoption in real-world clinical applications, he aims to improve patient outcomes and save lives. Throughout his academic journey so far, Yixuan has been honored with multiple awards, including the Outstanding Reviewer Award for MICCAI 2024, the Early Investigator Award from the Department of Defense’s Prostate Cancer Research Program, and the Graduate Partnerships Program (GPP) fellowship from the NIH.

Hannah Eichhorn, Doctoral Researcher, Helmholtz Munich and Technical University of Munich - Hannah Eichhorn’s research focuses on advancing reconstruction and motion correction techniques for brain magnetic resonance imaging (MRI). She completed her MSc thesis at the Copenhagen University Hospital, where she worked on prospective motion correction for a comprehensive clinical brain MRI protocol. Now, as part of her doctoral research, she explores physics-informed deep learning methods for a motion-robust reconstruction of quantitative brain MRI data. Additionally, she investigates the performance and reliability of quantitative metrics for image quality evaluation. She received the MICCAI Outstanding Reviewer Award in 2024.

Egor Panfilov, Doctoral Researcher, University of Oulu - Egor Panfilov is a Doctoral Candidate and Researcher in Medical Imaging and Technology at the University of Oulu, Finland. He holds M.Sc. and B.Sc. degrees in Sensing Technology from State University of Aerospace Instrumentation in Saint-Petersburg, Russia. His research focuses on developing multimodal deep learning methods for diagnostics and disease progression modelling, with a particular emphasis on knee osteoarthritis. His work has resulted in 12 peer-reviewed articles and has been recognized by ISMRM, OARSI, and IEEE EMBS Societies. Beyond academia, Egor has over 6 years of industrial R&D experience is an active open-source contributor, serving as a core team member of scikit-image. As a reviewer, he regularly contributes to IEEE TPAMI, the MAGMA journal, and MICCAI. His dedication to peer review for MICCAI has been acknowledged with an Honorable Mention for Reviewing in 2021 and 2022, as well as the Outstanding Reviewer Award in 2024.