Joaquín Rapela, Ph.D.

Joaquín Rapela received his bachelor’s degree in computer science and his doctorate in signal processing from the University of Southern California. He did postdoctoral training at University of California, San Diego, and at Brown University in statistical neuroscience topics. In his work, he develops and applies advanced statistical method to understand the function of the brain. Currently, he is a research engineer fellow at the Gatsby Computational Neuroscience Unit (GCNU), where he distributes advanced statistical methods developed at the unit and builds collaborative projects with scientists at the Sainsbury Wellcome Center (SWC).

Principal Investigator: Maneesh Sahani

Fellow: Zimo Li

Undergraduate Fellow Project: Understanding neural data with advanced statistical methods

This project will focus on a collaboration that aims to understand how mice forage in naturalistic environments. Rapela is using advanced statistical methods to infer properties of this behavior and neural activity. On a related collaboration, we are working with the author of Bonsai, an outstanding software for the control of neuroscience experiments, to incorporate into it advanced machine learning methods that will enable a new generation of neuroscience experiments.

This project will provide a SURFiN fellow broad training on beautiful experimental and computational neuroscience topics. The fellow will acquire practical experience on the application of these topics by contributing to any of the above collaborations.

The student will benefit by being part of our world-class computational and experimental institutions, and this research experience could well position them to pursue graduate studies in either field.