Health-AI

Stéphanie Bricq

Medical Imaging

Stéphanie Bricq (PhD) is Assistant Professor at ImViA laboratory (Université Bourgogne Franche-Comté). She defended her PhD in medical image analysis in 2008 at the University of Strasbourg. Her main research topics concern image processing, machine learning and artificial intelligence for medical applications

Ouassila Labbani

Distributed Knowledge and Artificial Intelligence

Ouassila Labbani-Narsis is a Lecturer in Computer Science at the University of Burgundy since 2008. She received her PhD degree in 2006 from the University of Science and Technology of Lille, and then worked as post-doctorate at the Higher Normal School of Lyon between 2006 and 2008. In 2014, she joined the project team CheckSem and since 2019 member of CIAD laboratory (Distributed Knowledge and Artificial Intelligence). Her research interests include Model Driven Engineering technologies, Knowledge Engineering, and constraints modeling and verification.

Alain Lalande

Medical Imaging

Alain Lalande, Assistant Professor is in the Medical Imaging Group of the ImViA laboratory (University of Bourgogne-Franche Comté) since 2000. His research interests concern medical image post-processing and MRI, especially of the cardiovascular system. He is currently the principal investigator of one project in post-processing of cardiovascular MRI and the main investigator of a collaborative contract with the CASIS company. His main publications have been published in Nature Genet, IEEE Trans Med Imaging and Investigative Radiology.

Sarah Leclerc

Medical Imaging

Sarah Leclerc has recently joined the University of Burgundy and the ImVia Laboratory as Associate Professor after obtaining her PhD in medical image processing. During her thesis, she established on a new large open dataset of echocardiographic images of the heart called CAMUS that deep learning approaches involving multi-task objectives were more efficient than both traditional machine learning approaches (such as random decision trees and active shape models) and classical convolutional neural networks (such as U-Net) in segmenting several structures of the heart. Her research is now focused on multi-modality and multi-task learning on several medical applications, and on incorporating interpretability in neural networks. She also has a strong interest in data augmentation and compression using deep learning.

Fabrice Mériaudeau

Medical Imaging

Fabrice Meriaudeau received both the master degree in physics at Dijon University, France as well as an Engineering Degree (FIRST) in material sciences in 1994. He also obtained a Ph.D. in image processing at the same University in 1997. He was a postdoc for a year at The Oak Ridge National Laboratory. He is currently Professeur des Universites at the University of Burgundy. He was the director of the Institute Health and Analytics (2017/2018) at the Universiti Teknologi PETRONAS Malaysia and was the Director of the Le2i (UMR CNRS) France, from 2011 to 2016. His research interests were focused on image processing for non-conventional imaging systems (UV, IR, polarization) and more recently on medical/biomedical imaging.

Ana Roxin

Cloud Computing & Cybersecurity

Ana is an Associate Professor in Computer Science at the University of Burgundy. Her research interests address specifying formal descriptions that allow computers to simulate human understanding, reasoning, and problem-solving. She has proven experience across Semantic Web, Linked Data, rule-based reasoning, semantic interoperability, and explainable AI. Her main contributions address the specification, integration, and exploitation of business knowledge in intelligent environments.