Professor Aline Villavicencio

Chair in Natural Language Processing
Deputy Director of Equality Diversity & Inclusivity

Telephone: +44 (0) 114 222 1860

Member of the Natural Language Processing research group

ORCID | Google scholar


Aline Villavicencio



Aline Villavicencio received her PhD and MPhil degrees from the University of Cambridge (UK) and MSc in Computer Science from the Federal University of Rio Grande do Sul (Brazil). She was a Visiting Scholar at the Massachusetts Institute of Technology (USA) (in the Department of Linguistics and Philosophy in 2014/2015 and in the Laboratory of Information and Decision Systems in 2011/2012) at the Labo­ra­toire LaTTiCe at the École Normale Supé­rieure (France) in 2014, an Erasmus-Mundus Visiting Scholar at Saarland University (Germany) in 2012/2013, and at the University of Bath in 2006-2009. From 2007-2017 she held a Research Fellowship from the Brazilian Scientific Research Council (CNPq). She is also affiliated to the Federal University of Rio Grande do Sul (Brazil)

Some of her recent activities include being the PC co-chair of the Conference on Computational Natural Language Learning (CoNLL-2019), Area Chair for events like ACL-2019, NAACL-2018, COLING 2018, and General co-chair for the 13th International Conference on Computational Processing of Portuguese (PROPOR 2018). She is a member of the advisory board of WiNLP, of the editorial board of TACL, JNLE, Journal of Language Modelling and Linguamatica, and a reviewer for various conferences, in addition to having co-chaired numerous *ACL workshops on Cognitive Aspects of Computational Language Acquisition and on Multiword Expressions. She has also co-edited special issues and books dedicated to these topics.

She is a member of the Natural Language Processing group at the University of Sheffield and of the Neurocomputational and Language Processing Laboratory of the Federal University of Rio Grande do Sul (Brazil).


Research Interests

Her research interests are in lexical semantics, multilinguality, and cognitively motivated NLP. This work includes techniques for Multiword Expression treatment using statistical methods and distributional semantic models, and applications like Text Simplification and Question Answering, for languages like English and Portuguese.