Élie Lucien
Bienenstock
Division of Applied Mathematics
Brown Institute for Brain Science
Tel: 401 863 1195
Email: elie at brown period edu
Research
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.
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)
Yun Gao
(updated Feb 1, 2012)