French Institute for Research in Computer Science and Automation

Inria is the French national research institution focusing on computer science and applied mathematics. The Epione team of Inria focuses on methodological, engineering, and translational advances towards the development of novel generation data analysis methods in healthcare. The longstanding research activity of Epione revolves around the analysis and treatment of biomedical data, with a focus in machine learning, medical imaging, computational anatomy and computational physiology. Over the past twenty years the group developed innovative approaches in image processing, statistical learning and patient-specific biophysical modeling, with translation to the clinical domain, and to the creation of biotech startups. 

Role of institution in the project

Inria is involved in WP2 (tasks 2.1, 2.4, 2.5), WP5 (5.4.1 to 5.6), WP6 (T.1, 6.2, 6.3) and WP7 (7.1a, 7.1b, 7.2).

Inria contributes to EUCAIM with the expertise on the design and deployment of federated learning platforms in healthcare applications, based on the development of the open source federated learning software Fed-BioMed.

Marco Lorenzi

Marco Lorenzi is tenured research scientist (CR) in the EPIONE team of the Inria Center of Université Côte d’Azur, and chair holder of the Interdisciplinary Institute of Artificial Intelligence 3IA Côte d’Azur since 2019. Dr. Lorenzi has a longstanding research activity on the analysis and treatment of biomedical data with a focus in machine learning and medical imaging. Particular research interest is in the technology of federated learning (FL), with contributions to both research and software development.

Francesco Cremonesi

Francesco Cremonesi is a Research and Development Engineer motivated by bridging the gap between the collection of high quality datasets and their analysis through well-engineered code and robust learning models. After a PhD at the boundary between computational neuroscience and high performance computing, Francesco has gained professional experience as a data engineer as well as a project manager for EU Horizon projects with partners from the clinical, academic and engineering domains. He is now a core developer of the federated learning software Fed-BioMed. When he is not coding, Francesco likes to play basketball, learn guitar, and develop his passion for photography.

Olivier Humbert

Olivier Humbert is Professor in Nuclear Medicine & Biophysics, and Member of the 3IA Cote d'Azur. His research is within the imaging department at the Antoine Lacassagne Center and in the TIRO laboratory (UMR4320, CEA, UCA, France), with focus on PET-CT imaging and identification of predictive biomarkers in oncology. Besides “conventional” imaging biomarkers, he also conducts studies involving applications of artificial intelligence algorithms and radiomics data (PET/CT images) to predict response of metastatic lung cancer to immunotherapy and breast cancer to hormone therapy.

Survey Invitation

Join Leading Experts In Shaping AI In Cancer

EUCAIM is looking for your feedback! We have recently published a Stakeholder Survey in order to reach out to potential end-users and stakeholders. We believe that your insights could significantly contribute to understanding the expectations of potential users and identifying the essential aspects that stakeholders find crucial for future engagement and collaboration with the platform.

Therefore, we would like to invite you to participate in the Stakeholder Survey about the Cancer Image Europe platform.

Completing the survey will take approximately 10 minutes. Your participation is crucial to the success of this project, and we deeply appreciate your expertise in shaping the future of cancer imaging and treatment.