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.

I am looking for a post-doc to work on a project about unsupervised learning: see ad here. Feel free to contact me if interested.

About me

My broad interests are in the intersection of computational linguistics and machine learning. I am interested in developing ways for reasoning about compositional structures such as parse trees through the use of formalisms such as probabilistic grammars.

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. I have worked with various grammars, such as probabilistic context-free grammars (PCFGs), latent-variable PCFGs, dependency grammars, adaptor grammars, tree substitution grammars, shift-reduce grammars and others.

Click here for a bio.


Publications
Teaching
Code
  • dageem - code for unsupervised grammar induction using logistic normal prior
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