My research is in theoretical neuroscience, computational vision, and computational linguistics. I study the mechanisms used by brains to create and work with complex, detailed, hierarchical representations of the external world. With colleagues in neuroscience and applied math, I investigate the hypothesis that the fine temporal structure of cortical activity, e.g. the synchronous firing of neurons, plays an important role in these representations.

COMPUTATIONAL VISION

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.

COMPUTATIONAL LINGUISTICS

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

Please see CV

Yariv Maron, Michael Lamar and Elie Bienenstock (2010). Sphere Embedding: An Application to Part-of-Speech Induction. Advances in Neural Information Processing Systems 23, edited by J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R.S. Zemel and A. Culotta, 1567–1575. link

Michael Lamar, Yariv Maron and Elie Bienenstock (2010). Latent-Descriptor Clustering for Unsupervised POS Induction. Proceedings of the 2010 Conference on Empirical Methods In Natural Language Processing, Association for Computational Linguistics, Cambridge, MA, 799–809. link

Inbal Ayzenshtat, Elhanan Meirovithz, Hadar Edelman,Uri Werner-Reiss, Elie Bienenstock, Moshe Abeles, and Hamutal Slovin (2010). Precise spatio-temporal patterns among visual cortical areas and their relation to visual-stimulus processing. The Journal of Neuroscience (2010) 30(33):11232–11245. link

Elie Bienenstock and Daniel Lehmann (1998) Regulated Criticality in the Brain? Adv. Complex Systems, 1, 361-384.

Elie Bienenstock (1996) On the Dimensionality of Cortical Graphs, Journal of Physiology, Paris, 90 251-256.

Elie Bienenstock (1995) A Model of Neocortex, Network: Computation in Neural Systems, 6 179-224.

Stuart Geman, Elie Bienenstock and René Doursat (1992) Neural Networks and the Bias/Variance Dilemma, Neural Computation, 4, 1-58.

Yves Frégnac, Daniel Shulz, and Simon Thorpe and Elie Bienenstock (1992) Cellular Analogs of Visual Cortical Epigenesis: 1. Plasticity of Orientation Selectivity, The Journal of Neuroscience, 12 (4), 1280-1300.

Elie Bienenstock and Christoph von der Malsburg (1987) A Neural Network for Invariant Pattern Recognition, Europhysics Letters, 4 (1), 121-126.

Elie Bienenstock, Leon N. Cooper, and P. Munro (1982) A Theory for the Development of Neuron Selectivity: Orientation Specificity and Binocular Interaction in Visual Cortex, The Journal of Neuroscience, 2, 32-48.

Elie Bienenstock (1977) Sets of Degrees of Computable Fields, Israel Journal of Mathematics, 27, 348-356.

Please see CV

Please see CV

Computational Neuroscience

Mathematical Methods in the Brain Sciences

Statistical Inference I (Introduction to Probability and Statistics)

Methods of Applied Mathematics II (Differential Equations)

Statistical Analysis of Time Series

Operations Research: Probabilistic Models