Elected to the GIPSA-Lab Conseil de laboratoire
My term as an elected member of the Conseil de laboratoire (CDL) began in October 2026.
Updates
Publications, projects, invited teaching and academic milestones.
My term as an elected member of the Conseil de laboratoire (CDL) began in October 2026.
Position paper accepted: “Localization Gains from Explanation Regularization Should Not Be Interpreted as Faithfulness Gains”, at the 3rd International Conference on Explainable AI for Neural and Symbolic Methods.
“Few-Shot Logical Anomaly Detection via Symbolic Constraint Extraction with Grounded Explanations”, by Malihe Dahmardeh, Dawood Al Chanti, Mauro Dalla Mura and Francesco Setti, has been accepted at the British Machine Vision Conference (BMVC) 2026 and will be presented at the conference.
President of the deliberation jury for the 2026 Baccalauréat professionnel.
Sub-coordinator of the Artificial Intelligence track at Unite! Research School 2026, Santuario di Oropa, Italy.
Keynote and hands-on training at the ERA4Health workshop on implementing AI tools in biomedical research and healthcare.
“Knee Injury Risk Estimation Using Deep Learning and Large Language Models (LLMs)” accepted at the 48th IEEE EMBS annual international conference.
“Denoise then Train: Improving the Performance of Unsupervised Anomaly Detection Models under Label-Level Noise” accepted at ICPR 2026.
“Trust but verify: Image-aware evaluation of radiology report generators” appears in Machine Learning with Applications, volume 23.
SAFE-Med selected for International Research Booster 2026, with UiT The Arctic University of Norway and Bio AI Lab.
Sayeh Gholipour-Picha defended her PhD at Université Grenoble Alpes, on explainable deep learning in medical imaging diagnosis.
Visiting researcher and lecturer at Aalto University through Unite!, with research discussions on explainable AI fragility and collaborative teaching.
SpinePredict awarded regional funding for a collaboration between GIPSA-Lab and SQI on decision support in spine surgery.
Awarded an ANR JCJC grant for EQUR-XSM, on evidential uncertainty and the reliability of saliency explanations.
VICCA published in Machine Learning with Applications, on visual interpretation of generated chest X-ray reports.
Published a chapter on artificial intelligence in medicine and oral potentially malignant disorders, in Critical Issues in Head and Neck Oncology.
Best Poster Award at BIOINFORMATICS 2024 for work on domain-specific semantic similarity assessment of chest X-ray reports.