Hi, I am Lorenzo 👋 I am a new principal investigator at the Paris Brain Institute and CNRS. I am broadly interested in how the structural and functional properties of the neural code support cognitive computation, a question I approach through data analysis, simulations, and mathematical modeling.

I received my Ph.D. in Statistical Physics from École Normale Supérieure and worked as a postdoctoral scientist at the Institut Pasteur and the Center for Theoretical Neuroscience at Columbia University.

My recent work focuses on how the geometry of neural representations provides a computational substrate for cognitive processes such as memory and abstraction (see, e.g., my work on social memory in the hippocampus and emotional states in the amygdala) and how single-neuron properties influence population coding and vice versa (see my work on the neural code along the cortical hierarchy).

Before that, I mainly worked on continuous attractor networks and statistical inference models applied to neural data, specifically to investigate how memorized cognitive maps are retrieved from sensory cues and how similar environments are pattern-separated in the hippocampus.

If you are interested in working with me, get in touch for opportunities on all levels at the Paris Brain Institute, including master’s internships, research assistant, PhD thesis (Sorbonne graduate program), and Postdoc.