Teaching
I teach at the intersection of computational neuroscience, biophysics, and data analysis. My courses are built around a simple principle: students learn by building and debugging models, not by listening. Below are materials from courses and lectures I have given.
Courses & Lectures
Advanced Neuroscience — Computational Track
NeuroTech track, Master in Biomedical Engineering, Paris Cité · September 2025
An introductory module to computational neuroscience for M2 students with mixed backgrounds (biology, medicine, biotechnology). Students use the JuliaSNN library to simulate biophysical neuron models and reproduce results from research papers.
The course relies on CompNeuro.jl, a Julia package developed for the course. It provides interactive phase-plane visualizations of 2D biophysical neuron models — AdEx, FitzHugh–Nagumo, Morris–Lecar — letting students explore how parameters shape excitability, bifurcations, and spiking dynamics in real time.
Dendrites — A Research Lecture
Donders Institute for Brain, Cognition and Behaviour · 2025
A research seminar on dendritic computation: how the nonlinear integration of inputs in dendritic compartments shapes single-neuron dynamics and enables network-level sequence memory. Covers the Tripod neuron model and its application to spoken word recognition.
Population Dynamics — Interactive Simulation
Science outreach · The Science Zone
An interactive browser simulation of predator-prey dynamics (foxes, rabbits, grass) built with p5.js. Designed to let students explore how reproduction rates and initial population sizes shape the long-term dynamics of an ecosystem.