Hi there, I’m Alexandre. I build foundation models for pathology at Waiv (formerly Owkin Dx), where I’m research lead on foundation models. My team’s models are released openly and used as reference feature extractors across the field: Phikon, Phikon-v2 and H0-mini at Owkin, then Phaet and Mascaret at Waiv. I also maintain Histoboard, a community dashboard that pulls published benchmark results for pathology foundation models into one place.

Alongside the model research, I’m a core contributor on our AI-based diagnostic products — RlapsRisk BC and the MSIntuit Suite — from development through international clinical validation, and lead scientist on pharma partnerships.

Research interests

• Foundation models and self-supervised learning for histopathology
• Robustness and generalization across scanners, stains and centers
• Computational pathology applied to diagnostics in oncology
• Weakly-supervised learning, calibration and cell segmentation
• Machine learning and biostatistics for medical research

Education

• MSc in Machine Learning and Computer Vision (MVA), 2018-2019 - ENS Paris-Saclay
• MSc in Statistics and Machine Learning, 2017-2019 - ENSAE Paris