Maneesh Sahani is a Professor of Theoretical Neuroscience and Machine Learning at the Gatsby Computational Unit the University College London.

He works at the intersection of machine learning and neuroscience where he focusses on the types of computation achieved within the sensory and motor cortical systems. Sahani has helped to pioneer analytic methods which seek to characterize and visualize the dynamical computational processes that underlie the measured joint activity of populations of neurons.

He has also worked on the link between the statistics of the environment and neural computation, machine-learning based signal processing, and neural implementations of Bayesian and approximate inference.

Sahani received a BS in physics and his PhD in computation and neural systems from Caltech, and he completed postdoctoral work at the Gatsby Unit and the University of California, San Francisco.