Emmanuel Prestat is a Principal Data Scientist with 12 years of experience building and operationalizing bioinformatics and digital pathology solutions for IVD and clinical research. He has led teams at MaaT Pharma, HalioDx/Veracyte and Qiagen to deliver CE/FDA-aligned image analysis, NGS assays and data science platforms that bridge research, regulatory and QC needs. Trained as a PhD bioinformatician who applied Bayesian networks to infer gene regulatory networks in breast cancer, he later expanded into metagenomics and metaproteomics exploring soil and microbial ecology at Lawrence Berkeley Lab. Emmanuel combines deep algorithmic expertise with practical product delivery—designing pipelines, statistical analyses and data management for regulated diagnostics. He is based in Lyon and known for translating complex omics problems into robust, auditable workflows that accelerate clinical and R&D decision-making. An understated strength is his cross-domain fluency from microbe discovery to immunohistochemistry, enabling rapid integration of novel computational methods into product-ready solutions.
12 years of coding experience
12 years of employment as a software developer
Baccalauréat Sciences, Baccalauréat Sciences at Lycée de Vienne, Saint-Romain-en-Gal
Doctor of Philosophy (PhD) Bioinformatics, Doctor of Philosophy (PhD) Bioinformatics at Université Claude Bernard Lyon 1
Postdoctoral fellow Bioinformatics, Postdoctoral fellow Bioinformatics at Lawrence Berkeley National Laboratory
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