Shay Cohen

Chancellor's Fellow / Lecturer (≈ Assistant Professor)

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

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

I am looking for a postdoctoral researcher in natural language processing. For more details, see here.

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 that originate in linguistics and formal language theory, and that have been augmented with a probabilistic interpretation. My most recent work treats the problem of predicting syntactic structures from text using spectral methods (in the supervised or unsupervised settings) and other linear algebraic methods. Most recently, we applied these ideas to machine translation, social media, semantics, multilingual parsing and to a problem in language and vision.

Click here for a bio.

The slides from my Mathematics of Language 2017 talk are available here.

A new book about Bayesian Analysis in Natural Language Processing is out (website, hardcopy on Amazon).

Marco has developed a new AMR parser called AMREager and a new set of evaluation metrics for AMR.

  • Topics in Natural Language Processing (INFR11113). Course website (Spring 2017). See also below.
  • Processing Formal and Natural Languages (INF2A). Course website (Fall 2015).
  • Lecture on linear classification at the Lisbon Machine Learning School (LxMLS), July 2015.
  • Topics in Natural Language Processing (INFR11113). Course website for 2016 (Spring 2015; Spring 2016). Course on PATH. Click here for a synopsis.
  • A tutorial about Spectral learning algorithms for NLP (NAACL, 2013). Similar tutorial with overlapping material at CMU (June, 2014).
  • Seminar at Columbia - Bayesian analysis for NLP (Spring, 2013).
  • A course at IBM about Probability and Structure in NLP (May, 2011).
Students and Post-docs
Here is a group picture from summer 2017.

Here is an older picture from summer 2016.

Here is an even older picture from summer 2015.

Here is a link to our group page that includes code, project and demo pages.

Code and Data
Contact information

scohen [strudel]

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

Phone: +44 (0) 131 650 6542