Hassan Alhajj is a research engineer and AI specialist based in France with 10 years of experience applying machine learning to healthcare. He holds a PhD in Biomedical Engineering and has progressed from developing video-based computer-assisted surgery systems in academia to leading clinical AI initiatives that improve breast cancer screening using multi-modal mammogram and ultrasound fusion. At Hera-MI he built diffusion-model pipelines to synthesize ultrasound data and boost training robustness, and his prior work spans reinforcement learning for surgical simulators and ICU mortality prediction. Always learning, he blends deep research rigor with production-minded engineering to move novel models from prototype to clinically relevant tools. Less obvious: his background in large-scale surgical video datasets (≈2M images) gives him rare expertise in handling temporally rich medical imaging for algorithmic and systems challenges.
10 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Biomedical/Medical Engineering, Doctor of Philosophy - PhD, Biomedical/Medical Engineering at Université de Bretagne Occidentale
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