Meaghan Fowlie

  mfowlie [at] coli [dot] uni-saarland [dot] de

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IPA: [ˈmeɪɡən ˈfaʊli]

I am a researcher at Universität des Saarlandes in Saarbrücken, Germany, under the supervision of Alexander Koller. Currently I am focused on two projects: deep learning and s-graph grammars. Deep learning is a type of neural network training, and my ultimate goal is to understand something of what, if any, linguistic representations arise in the midst of a complex neural network analysing language. When it comes to s-graph grammars, I am working with Jonas Groschwitz to apply linguistic theory to the parsing and generating of AMRs.

My primary research interests lie in connecting mathematical and computational linguistics with mainstream syntax. Mathematical approaches can complement mainstream approaches, for example by identifying the place of human language in the Chomsky hierarchy, and can also clarify existing theories, by forcing their formulation to be completely explicit.

I focus mainly on Minimalist Grammars, Ed Stabler (1997 etc)'s formalisation of Chomsky (1995 etc)'s minimalism. MGs are of interest because they define the right general class of languages (MCFLs), they are an efficient and intuitive formalism, and as they are formalisations of the current work of a great many syntacticians, MGs are a bridge to mainstream syntax.

I am just finishing my PhD in linguistics at UCLA. My dissertation is about adjunction. I consider how best to model adjuncts in minimalism, what formal properties these models have, and how adjuncts can be learned. In terms of learnability, I consider learnability in the mathematical algorithm sense, as well as taking an experimental approach.

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