Mounir Lahlouh

Assistant professor and Head of the Artificial Intelligence Master Program
ESME

Overview of research area

Deep Learning, Machine learning, statistics and probability, Large Language Models (LLM), computer vision, medical image processing (MRI, MRA, CT scans…), healthcare data analysis, AI and RGPD, data privacy.

Short biography

With a PhD in computer science, specializing in artificial intelligence and computer vision, I focus on topics such as generative AI, ethical evaluation, machine unlearning, and data protection. I have also developed expertise in the healthcare sector, particularly in creating AI solutions for medical image analysis, specifically for vascular segmentation.

As the Head of the Artificial Intelligence Major at ESME, I supervise educational and research projects in AI, while mentoring and supporting the next generation of engineers.

Publications

• T. Waqas, M. Lahlouh, and Y. Chenoune, AI-Driven Multimodal Approach: A Comprehensive Framework for Liver Tumor Diagnosis and Prognosis Using MRI, 6th International Conference on Bio-engineering for Smart Technologies (IEEE BioSMART 2025), Paris, France, May 2025.
• W. Babonnaud, E. Delouche, and M. Lahlouh, The Bias that Lies Beneath: Qualitative Uncovering of Stereotypes in Large Language Models, 14th Scandinavian Conference on Artificial Intelligence (SCAI), Jönköping, Sweden, pp. 195-203, June 2024.
• M. Lahlouh, R. Blanc, M. Piotin, J. Szewczyk, N. Passat, and Y. Chenoune, Cerebral AVM segmentation from 3D rotational angiography images by convolutional neural networks, Neuroscience Informatics, Elsevier, Volume 3, pp. 100138, 2023.
• M. Lahlouh, Y. Chenoune, R. Blanc, M. Piotin, S. Escalard, R. Fahed, J. Szewczyk, and N. Passat, Automated Aortic Anatomy Analysis: From Image To Clinical Indicators, IEEE Engineering in Medicine and Biology Conference (EMBC 2023), Sydney, Australia, July 2023, pp. 1-5.
• M. Lahlouh, Y. Chenoune, R. Blanc, M. P. Piotin, S. Escalard, R. Fahed, J. Szewczyk, and N. Passat, Segmentation and characterization of the aorta and supra-aortic trunks for neuroradiology procedure planning, Colloque Français d’Intelligence Artificielle en Imagerie Biomédicale (IABM), Paris, France, March 2023.
• M. Lahlouh, Y. Chenoune, R. Blanc, J. Szewczyk, and N. Passat, Aortic arch anatomy characterization from MRA: a CNN-based segmentation approach, IEEE International Symposium on Biomedical Imaging (IEEE ISBI 2022), Kolkata, India, March 2022, pp. 1-5.
• A. Kedra, M. Lahlouh, E. Shotar, Y. Chenoune, L. Boistard, A. Boussac, N. Shor, J. Savatovsky, R. Hage, V. Touitou, P. Nicholson, F. Clarençon, M. Piotin, R. Blanc, and S. Lenck, Global collapse of the dural sinuses after venous stenting in idiopathic intracranial hypertension, Journal of Neurology, Neurosurgery and Psychiatry, Volume 92, pp. 1363-1364, 2021.

PhD in Computer Sciences

• 2020-2023

  PhD in Computer Sciences

  Université de Reims Champagne-Ardenne, Reims, France
• 2019-2020

  Master in Artificial Intelligence

  Université de Reims Champagne-Ardenne, Reims, France
• 2014-2019

  Computer engineering degree

  Ecole National Supérieur d’informatique ESI (ex INI), Alger, Algiers

Assistant professor and Head of the Artificial Intelligence Master Program

• Since 2024

  Associate Professor and Head of the Artificial Intelligence Master Program

  ESME, Ivry-sur-Seine, France
• 2023-2024

  R&D Engineer

  Talan, Paris, France

Awards and Prizes

• 2021

  3ème meilleur prix poster par Boehringer Ingelheim France

  Journée Rémoise des Jeunes Chercheurs en Santé