HistoGraph

ICube brings together expertise in image processing, image information extraction, data mining, and knowledge management. Its SDC research team has extensive experience in unsupervised learning, image segmentation, medical data analysis with deep learning, and multi-modal data analysis. HistoGraph's principal investigator is Prof. Thomas Lampert, who held the Chair of Data Science and AI at ICube and has since been appointed Professor of Computer Science. His work focuses on machine learning for image and time-series analysis, in particular semi-supervised clustering and unsupervised/semi-supervised deep learning approaches for learning domain-invariant, generalisable representations. He is an alumnus of the US State Department's International Visitor Leadership Program for AI, and an expert on AI for the Council of Europe. Alongside his academic career, he has experience managing industrial research projects and consultancy engagements.

The DaSciM team, led by Prof. Michalis Vazirgiannis, develops machine learning and deep learning approaches to solve real-world problems, with a focus on graph analysis and text mining. The group has a track record of successful academic and industrial collaborations, attracting funding from partners such as LVMH, BNP, Airbus, Google, and Microsoft, as well as the French government. J. Lutzeyer plays a key role in the DaSciM team's contributions to the state of the art in graph representation learning.

IHU has experts in machine learning and deep learning applied to medical image analysis and surgical video analysis, feature engineering, explainable ML approaches, multi-modal data fusion, and the exploitation of eye-tracking information. Its work is published in leading ML and medical image analysis venues, and the team has extensive experience with ANR-funded and European research projects.