I hold a PhD in Artificial Intelligence and specialize in deep learning, computer vision, and generative AI for medical imaging. I work as a Computer Vision Research Engineer at a renowned cancer research center in France, where I design and evaluate advanced neural architectures for complex medical-image analysis problems.

My doctoral research explored generative models for predicting cancer progression from multimodal data. My broader expertise includes representation learning, variational autoencoders, diffusion models, multimodal image synthesis, tumor segmentation, and learning from limited clinical datasets. I have authored multiple peer-reviewed scientific publications as a primary author, including studies on deep generative data augmentation, medical-image synthesis, and predictive modeling of brain tumor evolution. I currently collaborate with Institut Curie in Paris on the design and development of generative deep-learning approaches for harmonizing multicenter PET images.

Drawing on my experience in deep learning, Python, and NumPy, and more than six years working with PyTorch and PyTorch Lightning, I bring to you the lessons I learned from designing research-grade AI systems.