Rachid Youven Zeghlache

I am Rachid Youven Zeghlache, a Research Engineer & AI Researcher at IMT Atlantique, France. I hold a Ph.D. from the University of Western Brittany (UBO / LATIM), where my thesis focused on longitudinal deep learning for the prediction of diabetic retinopathy progression.

My core research sits at the intersection of medical image analysis, multi-modal learning, and longitudinal modelling — building AI systems that can track disease evolution over time from heterogeneous clinical data such as retinal fundus photographs, OCT volumes, and fluorescein angiography.

I am especially interested in:

• Longitudinal representation learning — continuous-time models (Neural ODEs, masked autoencoders) that reason over irregular patient time-series.
• Multi-modal fusion — combining complementary imaging modalities for more robust clinical predictions.
• Agentic AI for health — leveraging LLM orchestration frameworks (LangGraph, AutoGen, CrewAI) to automate and augment biomedical research workflows.

Beyond the lab, I run Augmented Scholars — a newsletter and YouTube channel dedicated to making cutting-edge AI research accessible to the broader scientific community.

I have co-organised two MICCAI challenges: MARIO 2024 (AMD progression monitoring in OCT) and DIAMOND 2024 (diabetic macular edema onset prediction), and I serve as reviewer for MICCAI, IEEE TMI, Medical Image Analysis, and Computers in Biology and Medicine.

Feel free to reach out at youven.z@gmail.com or connect via LinkedIn.

Education