Fernando Diaz is a Canada CIFAR AI Chair at Mila, an adjunct professor at the School of Computer Science at McGill University, and a research scientist at Google Research Montreal.
Diaz’s primary research interest is information retrieval, the formal study of searching large collections of data for small bits of information. His research experience includes distributed information retrieval approaches to web search, interactive and faceted retrieval, mining of temporal patterns from news and query logs, cross-lingual information retrieval, graph-based retrieval methods, and exploiting information from multiple corpora.
- British Computer Society Karen Spärck Jones Award, 2017
- European Conference on Information Retrieval Best Student Paper Award, 2011
- ACM Special Interest Group on Information Retrieval Best Paper Award, 2009
Mitra, B., Diaz, F., & Craswell, N. (2017). Learning to match using local and distributed representations of text for web search. In Proceedings of the 26th International Conference on World Wide Web (pp. 1291-1299).
Diaz, F., Mitra, B., & Craswell, N. (2016). Query expansion with locally-trained word embeddings.
Imran, M., Castillo, C., Diaz, F., & Vieweg, S. (2015). Processing social media messages in mass emergency: A survey. ACM Computing Surveys (CSUR), 47(4), 1-38.
Olteanu, A., Castillo, C., Diaz, F., & Vieweg, S. (2014). Crisislex: A lexicon for collecting and filtering microblogged communications in crises. In Eighth international AAAI conference on weblogs and social media.
Imran, M., ssuoni, S., Castillo, C., Diaz, F., & Meier, P. (2013). Extracting information nuggets from disaster-Related messages in social media. In Iscram.Elba
CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.