
About
Tal Arbel is a Professor in the Department of Electrical & Computer Engineering at McGill University, affiliated with the Centre for Intelligent Machines (CIM). Their research focuses on advancing AI-driven solutions in medical imaging, particularly in computer vision and neurology applications such as MRI analysis for multiple sclerosis and brain tumor studies.
Key areas include developing robust algorithms for lesion segmentation, predictive modeling using multimodal data, and improving fairness and uncertainty quantification in medical AI systems. They are also involved in optimizing deep learning techniques for clinical workflows and addressing challenges in biomedical image analysis validation.
Recent work emphasizes generative models (e.g., diffusion-based synthesis), reinforcement learning for medical image generation, and counterfactual explanations for interpretable AI. Their contributions span improving diagnostic accuracy, treatment prediction, and personalized medicine through computational imaging biomarkers.
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