Elie Lucien Bienenstock

Department of Neuroscience

Division of Applied Mathematics

Brown Institute for Brain Science

Brown University

Providence RI 02912

Tel: 401 863 1195

Email: elie at brown period edu









My main research is in computational vision, natural and artificial. To interpret visual scenes, our brains rely on complex computations across a number of hierarchical levels. In particular, when interpreting images that are locally ambiguous -- as is most often the case -- our brains bring high-level knowledge to bear on low-level tasks such as image segmentation. In collaboration with neuroscientists, I investigate the neural mechanisms underlying such computations. In collaboration with applied mathematicians, I investigate generative compositional hierarchical models inspired by my work in theoretical neuroscience.


I have recently begun to work in computational linguistics, focusing on the task of unsupervised learning of part-of-speech tags.


Courses taught


APMA 0340 (Introduction to Differential Equations, Part II)

APMA 0410 (Mathematical Methods in the Brain Sciences)
APMA 1650 (Statistical Inference, Part I)

APMA 1660 (Statistical Inference, Part II)

APMA 1670 (Statistical Analysis of Time Series)

NEUR 1680 (Computational Neuroscience)


Yariv Maron

Michael Lamar

Anastasia Anishchenko

Britt Anderson

Yun Gao

Rene Doursat


(updated Jan 26, 2013)