Position: Professor at EURECOM – France.

Bio: Dr. Maria Zuluaga is an assistant professor at the Data Science department at EURECOM (Sophia Antipolis, France) and a Visiting Senior Lecturer within the School of Biomedical Engineering & Imaging Sciences at King's College London. She obtained her BSc in Electronics Engineering and MSc in Computer Science degrees at Universidad del Valle and Universidad de los Andes, respectively, in Colombia, and holds a PhD in Signal and Image Processing from Universitéde Lyon (France). Her research team focuses on the development of novel machine learning methods from multi-modal data that can be safely used to improve clinical practice and advance healthcare research. From an application standpoint, her research work aims to answer questions coming from cardiovascular and neurovascular imaging, as well as cancer research. Currently, she serves as an Associate Editor to Medical Image Analysis and IEEE Transactions on Medical Imaging..

Position: Professor at Sorbonne University– France.

Bio: Dr. Daniel Racoceanu is Professor at Sorbonne University and Principal Investigator at the Paris Brain Institute, within the Center for Artificial Intelligence and Data Science. His research lies at the intersection of biomedical image analysis, pattern recognition, machine learning, deep learning and computational integrative pathology. He develops artificial intelligence methods for microscopy, histopathology, multimodal biomedical data integration and explainable decision-support systems, with a particular focus on trustworthy AI and clinically interpretable models. His current research explores how artificial intelligence can bridge tissue morphology, molecular information and clinical interpretation. This includes computational pathology, digital histopathology, multimodal representation learning, spatial omics, virtual staining, explainability, uncertainty estimation and human-in-the-loop AI for translational biomedical applications. His broader objective is to contribute to the emergence of next-generation integrative pathology and precision medicine through trustworthy multimodal AI systems.

Position: Associate Professor of Electronic Engineering at the Pontificia Universidad Católica del Perú - Peru

Bio: Dr. Roberto Lavarello is Associate Professor of Electronic Engineering at the Pontificia Universidad Católica del Perú (PUCP), he received his Bachelor of Science and Engineering degree from PUCP and his Master's and Ph.D. degrees in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign (UIUC, USA). Dr. Lavarello has been a Fulbright Fellow, a mentor for NASA's MUST program, and is currently a mentor for the IEEE Engineering in Medicine and Biology Society (IEEE EMBS). Dr. Lavarello currently serves as Head of Research at the PUCP Medical Imaging Laboratory and Director of the Master's Program in Digital Signal and Image Processing at PUCP. Dr. Lavarello has over 10 years of experience in topics related to image formation and processing for use in disease detection and diagnosis. Dr. Lavarello has served as Associate Editor of IEEE Transactions on Biomedical Engineering (2010–2013), and is currently Associate Editor of IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control (2013–present) and IEEE Transactions on Medical Imaging (2015–present). Additionally, Dr. Lavarello served as President of the Peruvian Chapter of IEEE EMBS for the 2014–2015 period, and is a member of the IEEE EMBS Technical Committee on Biomedical Imaging and Image Processing (2014–present), the IEEE SPS Technical Committee on Bio Imaging and Signal Processing (2017–present), the IEEE UFFC International Ultrasonics Symposium Technical Program Committee (2015–present), the Steering Committee of IEEE Transactions on Medical Imaging (2018–present), and the Administrative Committee of IEEE EMBS (2017–present).