Invited Speakers

Aurélie Herbelot, Possible Worlds

Aurelie Herbelot is a researcher in the field of computational semantics, working at the junction of linguistics, cognitive science and AI. She is particularly interested in models of semantics that bridge across formal and distributional representations of meaning. Over he years, she has worked at various academic institutions across Europe, including Cambridge, Potsdam, Pompeu Fabra, and most recently Trento, where she held a faculty position at the Center for Mind and Brain/Sciences. She is now CTO at Possible Worlds, a start-up dedicated to building small and energy-efficient NLP systems with strong symbolic capabilities.

Tal Linzen, New York University & Google

Tal Linzen is an Assistant Professor of Linguistics and Data Science at New York University and a Research Scientist at Google. Before moving to NYU in 2020, he was a faculty member at Johns Hopkins University, a postdoctoral researcher at the École Normale Supérieure in Paris, and a PhD student at NYU. At NYU, he directs the Computation and Psycholinguistics Lab, which studies the connections between machine learning and human language comprehension and acquisition. He has received a Google Faculty Award and a National Science Foundation CAREER award.

Danielle Matthews, University of Sheffield

Danielle Matthews is Professor of Psychology at the University of Sheffield. Her research focuses on early language development, primarily in socially-diverse, typically-developing children but also in deaf children. Danielle edited the 2014 volume Pragmatic Development in First Language Acquisition and is currently completing a book for Cambridge University Press on Pragmatic Development following a British Academy Mid-Career Fellowship. She uses experimental and individual differences methods to understand mechanisms of developmental change from birth to 10 years.