Dr. Paola Merlo

Associate Professor

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Biography

Paola Merlo is an Associate Professor at the University of Geneva, leading the interdisciplinary research group on Computational Learning and Computational Linguistics (CLCL). Her research focuses on the intersection of linguistic modeling and machine learning techniques, addressing fundamental issues such as the statistical nature of language and empirical evaluations of linguistic proposals, particularly in lexical semantics and language universals. She emphasizes developing statistical models for syntactic and semantic parsing. Merlo's collaborators utilize an approach known as Quantitative Computational Syntax. She is also the deputy director of the National Centre of Competence in Research on the Evolution of Language, where she conducts research on compositionality and computational methods. Previously, Merlo served as an editor for the journal of the Association for Computational Linguistics and held positions in various committees, including as general chair for EMNLP 2011 and EACL 2021. An ACL Fellow in 2019, she has studied theoretical linguistics at the University of Venice and earned her doctorate in Computational Linguistics from the University of Maryland. Additionally, she has been an associate research fellow at the Institute for Cognitive Science at the University of Pennsylvania and has had visiting scholar appointments at the University of Edinburgh and Stanford University. Merlo has been awarded an SNSF Advanced Grant to research the automatic generalization of the structure of meaning across languages.

Research Interests

Requirements for University of Geneva

Master Program
Requirements
IELTS
Overall
Required:7
TOEFL
Total
Required:92
Prerequisites
Bachelor degree from a recognized university Minimum 60 ECTS in management or related field for direct admission
Application Checklist
  • Cover letter
  • CV
  • Diplomas
  • Transcripts
  • Proof of English proficiency
Specialization Notes

Includes Department of Management, Finance, Economics, and Statistics programs. GMAT is strongly encouraged but not mandatory for most GSEM masters.