Academic titles
- 2022: PhD in engineering science and technology. Université Libre de Bruxelles, Belgium.. Dissertation: Impact of real-world annotations on the training and evaluation of deep learning algorithms in digital pathology (https://research.adfoucart.be/thesis/). Director: Prof. Christine Decaestecker. Thesis jury presided by Prof. Hughes Bersini.
- 2011: Master in biomedical engineering. Université Libre de Bruxelles, Belgium.. Option: medical imaging and informatics
- 2009: Bachelor in engineering science. Université Libre de Bruxelles, Belgium..
Experience
2025 - Present
Lecturer in the Department of Informatics at Haute École Léonard de Vinci, Brussels, Belgium.
Teaching in the Bachelor of Informatics program (AI, Databases, Mathematics)
2024 - 2025
Lecturer (part-time) at Brussels School of Engineering, Université Libre de Bruxelles, Belgium.
Replacement for the course: Multivariate data analysis (for Master 1 biomedical engineers).
2022 - 2025
Postdoctoral researcher at the LISA laboratory, Université Libre de Bruxelles, Belgium.
Research on preclinical in-vivo / ex-vivo multimodal image registration in the context of the Prother-Wal project. Manager of the Prother-Wal project for the ULB-LIS unit, including supervision of a doctoral researcher.
2022 - 2025
Invited teacher at Faculté de Droit, Université Libre de Bruxelles, Belgium.
Seminar on the capabilities and limitations of Large Language Models for first-year law students, in the context of the Méthodologie juridique course.
2015 - 2022
PhD researcher at the LISA laboratory, Université Libre de Bruxelles, Belgium.
Research on deep learning applied to digital pathology, with a focus on a critical analysis of training and evaluation methods used in modern AI benchmarking in image analysis.
2015 - 2022
Teaching assistant at Brussels School of Engineering, Université Libre de Bruxelles, Belgium.
Laboratories, oral examinations, seminars for the courses Image acquisition and processing (Prof. O. Debeir), Pattern recognition and image analysis (Prof. O. Debeir & C. Decaestecker), Medical information systems (Prof. D. Wikler). Tutoring for deep learning image analysis projects and master theses. Tutoring for bachelor year 2 student groups.
2013 - 2015
Software development engineer at KISANO Belgique S.A., Uccle, Belgium.
Development of a web-based teleradiology solution, deployed in hospitals and radiology centers in Belgium, France, Switzerland and Congo.
2011 - 2013
Research engineer at the LISA laboratory, Université Libre de Bruxelles, Belgium.
Research on real-time detection and classification of vehicles in videos of traffic scenes, in collaboration with Macq.
2010 - 2012
Internship, then software development and maintenance at Maison d’Accueil Socio-Sanitaire de Bruxelles (MASS), Belgium.
Developing and maintaining a scheduling and management system for a multidisciplinary health and social services institution.
2010 - 2019
Trainer of youth leaders at the Scouts et Guides Pluralistes de Belgique.
Training camps to teach new scout leaders on aspects ranging from “how to organize activities” to “how to make sure the well-being of the children is always taken care of”
Other activities
2020 - Present
Research blog: https://research.adfoucart.be
Started during my PhD thesis with articles mostly focused on digital pathology. Since 2022 with a broadened scope on our research and also more generally on trends in AI.
February 2025
Visiting scholar at the Diagnostic Image Analysis Group (DIAG), Radboud UMC in Nijmegen, The Netherlands (Host: Prof. Geert Litjens)
Starting a partnership for the analysis of results of medical image analysis challenges organized by DIAG.
September 5th, 2024
Invited expert at the Royal Meteorological Institute
Discussing the risks and opportunities of new machine learning models for weather forecasting.
June 13th, 2024
Invited expert at the “AI @ MSF Workshop”, organized by Médecins Sans Frontières Bruxelles
Panel to evaluate the ethical aspects of AI tools and discuss the potential of modern AI techniques as tools to help in their humanitarian mission (with Prof. Hughes Bersini).
2023 - 2024
Citizen conference at the Skeptics in the Pub Bruxelles (organised by the Comité Para), entitled “Comprendre et évaluer les intelligences artificielles” (September 28th, 2024). Similar presentations with the same name were previously done at events held in “Casa Nova”, Schaerbeek (February 23rd, 2024) and at the Skeptics in the Pub Liège (December 8th, 2023).
Vulgarized presentation on how to understand and evaluate AI algorithms. Slides from the Liège event are available online (https://research.adfoucart.be/preprint/SitP.pdf)
2023 - 2024
Recherche en Perspective: collaborative project with La Cambre and Ohme based on our research on Multimodal pre-clinical medical image fusion (with Arthur Elskens).
Project where graphic design students from La Cambre collaborate with researchers to present and vulgarize their research.
2021
Ma Thèse en 180 secondes (My thesis in 180 secondes). Text and link to the video of the event: https://adfoucart.be/blog/ma-these-en-180-secondes.
Participation to the ULB round, with a presentation entitled “Intelligence artificielle et histologie : un ingénieur au pays des médecins”.
2020 - 2021
Educational videos about medical information systems, image processing and deep learning for image analysis: https://youtube.com/channel/UCbBZNHYHOte25t8o2aHZRPg
The videos closely follow the laboratories for the INFO-H400: Medical Information Systems and the INFO-H500: Image acquisition and processing, but are also designed to be useful as a standalone resource on those topics.
List of publications
Note: all publications are available online at https://research.adfoucart.be/publications. Google Scholar profile: https://scholar.google.com/citations?user=lEuEbJ4AAAAJ&hl=en.
- A. Foucart, A. Elskens, C. Decaestecker. Ranking the scores of algorithms with confidence. Proc. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2025). (doi:10.14428/esann/2025.ES2025-39)
- A. Foucart, A. Elskens, O. Debeir, C. Decaestecker. Finding the best channel for tissue segmentation in whole-slide images. Proc. 19th International Symposium on Medical Information Processing and Analysis (November 2023). (doi:10.1109/SIPAIM56729.2023.10373416)
- A. Elskens, A. Foucart, E. Zindy, O. Debeir, C. Decaestecker. Assessing Local Descriptors for Feature-Based Registration of Whole-Slide Images. Proc. 19th International Symposium on Medical Information Processing and Analysis (November 2023). (doi:10.1109/SIPAIM56729.2023.10373514)
- A. Foucart, O. Debeir, C. Decaestecker.. Panoptic Quality should be avoided as a metric for assessing cell nuclei segmentation and classification in digital pathology. Scientific Reports 13 (8614), 2023. (doi:10.1038/s41598-023-35605-7)
- A. Foucart, O. Debeir, C. Decaestecker.. Evaluating participating methods in image analysis challenges: lessons from MoNuSAC 2020. Pattern Recognition (141), 2023. (doi:10.1016/j.patcog.2023.109600)
- A. Foucart, O. Debeir, C. Decaestecker.. Shortcomings and areas for improvement in digital pathology image segmentation challenges. Computerized Medical Imaging and Graphics (103), 2023. (doi:10.1016/j.compmedimag.2022.102155)
- A. Foucart, O. Debeir, C. Decaestecker.. Comments on “Monusac2020: A Multi-Organ Nuclei Segmentation and Classification Challenge”. IEEE Trans. Medical Imaging, 2022. (doi:10.1109/TMI.2022.3156023)
- A. Foucart, O. Debeir, C. Decaestecker.. Processing multi-expert annotations in digital pathology: a study of the Gleason2019 challenge.. Proc. SPIE 12088, 17th International Symposium on Medical Information Processing and Analysis, 2021. (doi:10.1117/12.2604307)
- A. Foucart, O. Debeir, C. Decaestecker.. SNOW Supervision in Digital Pathology: Managing Imperfect Annotations for Segmentation in Deep Learning.. Report, 2020. (doi:10.5281/zenodo.8354443)
- Y-R. Van Eycke, A. Foucart, C. Decaestecker. Strategies to Reduce the Expert Supervision Required for Deep Learning-Based Segmentation of Histopathological Images.. Frontiers in Medicine (6), 2019. (doi:10.3389/fmed.2019.00222)
- A. Foucart, O. Debeir, C. Decaestecker.. SNOW: Semi-Supervised, NOisy and/or Weak Data for Deep Learning in Digital Pathology.. ISBI, 2019. (doi:10.1109/ISBI.2019.8759545)
- A. Foucart, O. Debeir, C. Decaestecker.. Artifact Identification in Digital Pathology from Weak and Noisy Supervision with Deep Residual Networks.. Cloud’Tech, 2018. (doi:10.1109/CloudTech.2018.8713350)