Amrin Akter
Machine learning for medical imaging: uncertainty quantification and explainable AI.
Supervision
Team & Supervision
Doctoral researchers, research collaborators and student projects at GIPSA-Lab and partner institutions.
Doctoral researchers
Rogerio Bombardelli
Adaptive computer vision solutions for heterogeneous quality control.
Postdoctoral collaboration
Oussama Messai
Postdoctoral researcher · DeepKneeDeep learning for the prevention, diagnosis and monitoring of knee injuries in athletes.
Master’s projects · 2025–2026
Marwa Saighi · CORAL
Automated angiography-based microvascular perfusion assessment. M2 Artificial Intelligence for Health, UGA. Collaboration with CHU Grenoble Alpes and INSERM UMR 1039; Pr. Gilles Barone Rochette.
Muhammad Fazeel · QUAMS
Automatic quantification of skeletal muscle. M2 SIGMA, Grenoble INP – Phelma / UGA. Collaboration with CHU Grenoble Alpes; Dr. Klaus Dieterich.
Mounzer El Merheb
Active learning for cardiac segmentation: reducing annotation burden with uncertainty-guided sampling. M2 Artificial Intelligence, Grenoble INP – Ensimag / UGA.
Defended doctoral research
Dr. Sayeh Gholipour-Picha
Explainable Deep Learning in Medical Imaging Diagnosis.
Current position: Postdoctoral researcher in Oncology AI and rare cancer prognosis at Gustave Roussy and CentraleSupélec (2026–present).
Earlier student projects
Student projects · 2019–2025
Amrin Akter
Quantitative evaluation of saliency-based methods for medical image analysis. M2 TSI, Phelma.
Iannis Pereuilhet
Explainable AI for medical image analysis. 2A BIOMED, Phelma.
Maria Fernandes
Guided semi-supervised learning with uncertainty measurement. Ense3.
Ali Moufid
Guided semi-supervised semantic segmentation with uncertainty measurement. Phelma.
Samer Saleh
Prior image captions for anomaly and semantic scene segmentation. Co-supervision with Kai Wang.
Sayeh Gholipour-Picha
Does GAN-based image data augmentation provide new information? Main supervisor: Alice Caplier.
Zaineb Chiha
Deep learning for lower-limb muscle segmentation and reproducible volume quantification. Co-supervision with Diana Mateus, LS2N.
Elice Roy Kanjamala
Active learning for smart sampling. École Centrale de Nantes / LS2N.
Valentin Noel, Giorgi Gelovani & Kai Huang
Brain tumour segmentation using image processing and deep learning. École Centrale de Nantes / LS2N.