Welcome to the Ricci Lab at Institut Imagine! We study biological dynamical systems in health and disease. Using tools from applied math, machine learning and physics, we aim to uncover the dynamical rules governing the behaviors of both single cells and their complex interactions in circuits and whole tissues. We are interested in both the development of new computational methods and theoretical advances as well as the concrete analysis of specific disease cases.
As a part of Institut Imagine, our lab is located in the heart of Paris and is part of a vibrant research network including the Institut Necker (INEM), the Institut Pasteur and PR[AI]RIE.
Research
Forecasting spatiotemporal dynamics in reaction-diffusion models
→ Check out our ICLR 2025 paper on learning reduced order models in PDEs!
Spatiotemporal dynamics pervade the biological sciences, from the morphogen dynamics underlying patterning in animal pigmentation to the protein waves controlling cell division. An ongoing scientific challenge lies in understanding how system parameters relate to qualitative changes in system behavior called bifurcations. This challenge is made particularly difficult in realistic settings where governing PDEs are unknown and data is limited.
The research aims of this project are both practical and theoretical. First, we wish to build computational tools to infer the bifurcation structure of real spatiotemporal data in biology. Second, we want to understand mathematically which measurements are minimally necessary for detecting different classes of bifurcations.
Other research directions:
Long-term behavior in RNA dynamics
How can we locate the long-term dynamics of high-dimensional gene expression data? [Github]
Hopf bifurcations in cell cycle data
How do we predict the emergence of gene expression oscillation in an equation-free manner? [Github]
Universal dynamical embeddings
Can we learn a universal feature dictionary for the classification and design of dynamical systems? [Github]