Camila Gonzalez: Medical Continual Learning

MICCAI Student Board Mission The MICCAI Student Board (MSB) represents student interests within the MICCAI society, and aims to stimulate the involvement of students within the MICCAI community. The MSB enhances student networking in the community, engages students in the MICCAI society, and advises the MICCAI board on matters of relevance for students. The MSB organises social and professional and student events during the MICCAI period, in collaboration with local organisers, and maintains the MICCAI Educational Initiative.

Islem Rekik is the Director of the Brain And SIgnal Research and Analysis (BASIRA) laboratory (http://basira-lab.com/) and an Associate Professor at Imperial College London (Innovation Hub I-X). Together with BASIRA members, she conducted more than 100 cutting-edge research projects cross-pollinating AI and healthcare —with a sharp focus on brain imaging and neuroscience. She is also a co/chair/organizer of more than 25 international first-class conferences /workshops /competitions (e.g., Affordable AI 2021-22, Predictive AI 2018-2024, Machine Learning in Medical Imaging 2021-24, WILL competition 2021-23). Dr Rekik has been awarded prestigious international research fellowships including the EU Marie-Curie Fellowship in 2019 and the TUBITAK 2232 for Outstanding Experienced Researchers during 2020-2022. In addition to her 150+ high-impact publications, she is a strong advocate of equity, inclusiveness and diversity in research. She is the former president of the Women in MICCAI (WiM), the co-founder of the international RISE Network to Reinforce Inclusiveness & diverSity and Empower minority researchers in Low-Middle Income Countries (LMIC) and a committee member of the AFRICAI network. She is in the organizing committee of MICCAI 2022 (Singapore), 2023 (Vancouver), 2024 (Marrakesh) and 2025 (South Korea). Graph Neural Networks in Network Neuroscience

Akshay Chaudhari is an Assistant Professor in the Integrative Biomedical Imaging Informatics at the Department of Radiology in Stanford University, USA. He leads the Machine Intelligence in Medical Imaging research group and has a primary research interest at the intersection of artificial intelligence and medical imaging. He also serves as the Associate Director of Research and Education at the Stanford AIMI Center. Adapted large language models can outperform medical experts in clinical text summarization

Prof. Rajendra Pratap Gupta is a leading public policy expert with over a decade of experience. Rajendra has worked with the World Economic Forum in the past & has served as an advisor to the Union Health Minister of India. He is focusing on designing digital health policies to make healthcare AI-ready.

Prof. Hamid Tizhoosh explores the applications of artificial intelligence (AI) in medicine, particularly in medical image analysis and cross relations to other patient data such as molecular, laboratory and textual data. His research is currently focused on search and matching in archives of patient data. Foundation Models for Histopathology—Fanfare or Flair Creating an atlas of normal tissue for pruning WSI patching through anomaly detection

Prof. Kevin Zhou is a Distinguished Professor and Founding Executive Dean of School of Biomedical Engineering, University of Science and Technology of China (USTC). Before this, Dr. Zhou was a Principal Expert and a Senior R&D Director at Siemens Healthcare Research. He has been elected as a fellow of several top societies such as AIMBE, IEEE and MICCAI. Prof. Zhou serves the MICCAI society as a board member and currently focuses on generative AI for medical imaging.

Alexander Hann is a gastroenterologist at Uniklinik Würzburg, Germany and holds a professorship for digital transformation in gastroenterology, which focuses on AI support for endoscopic imaging.

Damini Dey is a professor in Biomedical Sciences at Cedars Sinai Medical center, Los Angeles, USA. Professor Dey focuses on automated derivation of imaging measures from noninvasive cardiac image data, clinical implementation of novel automated computer processing algorithms, and the application of these tools to solve key clinical problems. Her success stories include QFAT and AutoPlaque softwares.

Enzo Ferrante is a Research Scientist at Universidad Nacional del Litoral in Santa Fe, Argentina. Enzo focuses on machine learning methods for biological and medical image analysis, including domain adaptation and segmentation with anatomical priors. Addressing fairness in artificial intelligence for medical imaging

Prof. Jochen Lennerz is the Medical Director of the Center for Integrated Diagnostics at the Massachusetts General Hospital, USA. He is a board-certified pathologist by training and has professorship appointments at Harvard medical School. Prof. Lennerz co-organized the Data4Health 2023 conference in Berlin with the health minister of Germany Prof. Karl Lauterbach. Data4Health 2023 Berlin