Michele Garibbo
Visiting PhD student
My research interest focuses on applications of (deep) reinforcement learning (RL) methods to neuroscience. Primarily, I work on applications of policy gradients methods to understanding human motor learning. Additionally, I am interested in investigating human cognitive planning through the lenses of latent planning models in the RL literature. In the past, I also worked on purely deep RL projects on value estimation.