Shay Cohen

Chancellor's Fellow (≈ Assistant Professor)

Institute for Language, Cognition and Computation
School of Informatics
University of Edinburgh


In my research, I aim to discover computational methods for reasoning about natural language and linguistic structure.

Prospective students who might be interested in working with me: please see the note here. Also, see the new data science Ph.D. programme.

About me

My broad interests are in the intersection of computational linguistics and statistical learning. I am interested in developing ways to computationally reason about structured objects. Such structured objects are prevalent in natural language processing, for example, in syntactic analysis.

Much of my research has relied on capturing the syntax of natural language using probabilistic grammars -- grammars which originate in linguistics and formal language theory, and which have been augmented with a probabilistic interpretation. My most recent work treats the problem of predicting syntactic structures from text using spectral methods (with or without treebanks) and other linear algebraic methods. Most recently, we applied these ideas to machine translation.

Click here for a bio.


Publications
Teaching
Code
  • dageem - code for unsupervised grammar induction using logistic normal prior. Link on github.com. Download zip. New version (1.01) is out on August 19, 2014.
Contact information

scohen [strudel] inf.ed.ac.uk

10 Crichton Street
Informatics Forum 4.26
Edinburgh EH8 9AB
United Kingdom

Phone: +44 (0) 131 650 6542