I am a first-year PhD student in computational neuroscience 🧠 at the Mathis lab of Adaptive Motor Control (PI Prof. Mackenzie Mathis) as part of the ELLIS PhD program. I work on understanding how the brain represents external features in its environment and constructs internal models to generalize and extract the relevant information from it 🧩. I have a strong interest in investigating the dynamics 💫 taking place during the formation of such internal representation while learning a task. To do so, I will relate motor control 💪 and vision 👀 by exploring the processes at play in active sensing.
More generally, with the development of powerful recording tools 📡 such as Neuropixels, neuroscientists can find relevant structure in the data, at the neural population level. I am interested in bringing the appropriate computational and mathematical methods to the field, by adapting theories from topological algebra, graphs or dynamical systems.
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PhD in Electrical Engineering, Present
MSc in Computational Neurosciences, 2022
BSc in Life Science Engineering, 2019
Implementation of new functionalities to CEBRA, a dimensionality reduction tool for neural data, using contrastive learning (Nature, 2023).
Semester projets in diverse laboratories of the School of Life Sciences:
PyTorch, ML libraries
Learning and decision-making
Matlab, Java, C++, SQL
Teaching assistant for first-year Bachelor’s students in the course of Prof. Jamila Sam and Barbara Jobstmann. Both in person and remotly. This included:
Teaching assistant for second-year Bachelor’s students. Both in person and remotly. This included:
Teaching assistant for first-year Bachelor’s students in the course of Prof. Ivo Furno. Both in person and remotly. This included: