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Jackie Cheung

Appointment

Canada CIFAR AI Chair

Pan-Canadian AI Strategy

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About

Jackie C. K. Cheung is a Canada CIFAR AI Chair at Mila and an associate professor in the School of Computer Science at McGill University.

Cheung conducts research in natural language processing, an area of artificial intelligence in which we build computational models of human languages such as English or French. His research group’s goal is to develop computational methods for understanding text and speech, in order to generate language that is fluent and appropriate to the context. In his lab, Cheung investigates statistical machine learning techniques for analyzing and making predictions about language. Several current projects include summarizing fiction, extracting events from text, and adapting language across genres.

Awards

  • Best Paper Award Association for Computational Linguistics, 2018
  • Facebook Fellowship, 2013
  • NSERC Alexander Graham Bell Canada Graduate Scholarship, 2012

Relevant Publications

  • Emami, A., Porada, I., Olteanu, A., Suleman, K., Trischler, A., & Cheung, J. C. K. (2021). ADEPT: An Adjective-Dependent Plausibility Task.

  • Xu, P., Kumar, D., Yang, W., Zi, W., Tang, K., Huang, C., … & Cao, Y. (2021). Optimizing deeper transformers on small datasets.

  • Wu, J., Xu, Y., Zhang, Y., Ma, C., Coates, M., & Cheung, J. C. K. (2021). TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion.

  • Porada, I., Suleman, K., Trischler, A., & Kit Cheung, J. C. (2021). Modeling Event Plausibility with Consistent Conceptual Abstraction.

  • Socolof, M., Cheung, J. C. K., Wagner, M., & O’Donnell, T. J. (2021). Characterizing Idioms: Conventionality and Contingency.

Institution

McGill University

Mila

Department

School of Computer Science

Education

  • PhD (Computer Science), University of Toronto
  • MSc (Computer Science), University of Toronto

Country

Canada

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