Matthew Ricci

Our lab, Machine Learning for Predictive Omics (MLPrO), was founded in July 2025 as part of Institut Imagine and Université Paris Cité. We develop machine learning methods to decode dynamical, spatial and mechanical properties of biological systems from large-scale multiomics data. We then use these tools to propose optimal cellular control strategies for disease modeling and regenerative medicine. Current research axes include: 

1. Rational design of fine-grained transcriptomic perturbations which incorporate dosage and timing effects to optimally steer gene expression during cellular reprogramming. 
2. Decoding of cellular mechanics from spatial transcriptomic data to identify new gene targets for the treatment of genetic diseases in epithelial tissues. 
3. Generative modeling of spatial perturbations.  

Lab director Matthew Ricci got his PhD in machine learning from Brown University in 2020, where he worked with Thomas Serre. He was then a postdoc at Brown's Data Science Initiative where he was advised by Stuart Geman and a Zuckerman Postdoctoral Fellow in the lab of Mor Nitzan. His main research interests are physics-informed machine learning and computational biology.

Consult the lab wesite

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