Curriculum vitae - Projects & Research Interests - Publications - Software - Conference Calendar - Students - Misc
My personal research interests lie within the field of image informatics (in particular "bioimage informatics"), ie. the development and application of machine learning, computer vision, and software development methodologies to ease the exploitation of large images, e.g. the recognition and quantification of cells, tissues and other biological or biomedical "objects" in large-scale bioimaging datasets (e.g. in digital pathology), and on the delivery of user-friendly softwares to help scientists (biologists/pathologists/computer scientists/etc.) to exploit big imaging data, derive new knowledge, and support their findings and diagnoses.
In October 2010, I initiated the CYTOMINE research project which lead to the development of the CYTOMINE open-source software platform (Marée et al., Bioinformatics 2016), a "Google Maps"-like rich internet application for remote visualization, annotation and automated analysis of high-resolution, multi-gigapixels images.
It is now used in various domains by various entities, as illustrated below.
This research is about the design of generic methods for automatic image classification, retrieval, and semantic segmentation.
Indeed, as potential applications of image recognition technologies are multidinous, we seek to develop general-purpose methods for the recognition of various types
of images that share some visual regularities, without relying on too strong assumptions about patterns to recognize and acquisition
conditions, and without having to rely on domain experts to design specific features.
This book chapter (2013) summarizes our work where we combine ensemble of randomized decision trees with random extraction of subwindows (square patches) described by their raw pixel values.
Between January 2005 and October 2014, I was the GIGA Bioinformatics platform manager (scientific head: Prof. L. Wehenkel). In close collaboration with the Bioinformatics and Modeling research unit, this platform offers software development and data analysis services to academic (within the GIGA research center and beyond) as well as to industrial researchers. Its services include classification of biological/biomedical data (SELDI mass spectra, microarrays, clinical databases, ...) obtained from various medical instrumentation based on machine learning methods.
This activity lead to co-authorship of several journal papers (in Journal of Immunology, Proteomics, Annals of the rheumatic diseases, ...) in various application domains (inflammatory diseases, cancer, ...).
I'm very much in favor of basic principles of open science (open access, open data, open source, open hardware) although I still have much to learn about it.