Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Michele Garibbo

Postdoctoral Research Scientist

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.