About

I am a data scientist and machine learning engineer specializing in deep learning for medical imaging, LLM fine-tuning, and end-to-end AI deployment. I hold a Master's Degree of Data Science & Artificial Intelligence (AMU-Centrale Méditerranée) and a Computer Science bachelor's degree (AMU), consistently ranking at the top of my classes.

I have contributed to advanced projects at Neuro-Sys, deploying Mixtral LLMs on AWS and building deep learning pipelines for brain image segmentation. At Veracyte, I improved cancer diagnostics with generative models (CycleGANs, Diffusion, HistoGPT, PathLDM), boosting model performance (e.g., CLAM F1 from 0.61 to 0.80). At Airbus Helicopters, I developed predictive models for fuel consumption and anomaly detection in gearboxes and different data analysis dashboards for helicopter fleets..

I develop Python applications (Flask, Gradio, React), handle large datasets, and automate workflows. Proficient with PyTorch, Hugging Face, and cloud platforms like AWS (SageMaker, EC2, S3...) and Google Cloud, I combine domain expertise with engineering rigor.

In parallel, I experiment with AI bots for games, automation tools, and generative models. My work is marked by autonomy, cross-domain initiative, and research-level implementation in practical contexts.