Since 2022, I have been a QLife PhD student in the Cayco-Gajic lab, where I investigate how the brain learns through interactions with its environment. My research combines deep reinforcement learning with experimental neural data to uncover the mechanisms underlying motor learning, adaptation, and error-driven control.

During my undergraduate studies in electrical engineering and theoretical physics, I developed a strong interest in artificial intelligence and neuroscience, and in how the two fields can mutually inform one another. This led me toward neuroscience research, first as a bachelor’s student working on spike sorting and clustering in large-scale neural recordings with Luca Berdondini at the Italian Institute of Technology. I then completed my master’s thesis on biologically inspired learning in recurrent neural networks under the supervision of Vincent Hakim at LPENS.

In recent years, I have also been actively involved in teaching practical courses in the Master for Life Sciences program at the ENS biology department, covering topics ranging from Quantitative Viral Dynamics to Advanced Data Analysis.

Outside the lab, I divide my time between climbing walls and seeking freedom on my gravel bike.