I’m a PhD student in the Reasoning and Learning Lab at McGill University. I’m interested in a range of learning paradigms - imitation, reinforcement, deep, transfer - especially insofar as they apply to natural language processing. I’m supervised by Joelle Pineau.
In 2014 I completed a Masters degree in Computer Science in the Computational Neuroscience Research Group at the University of Waterloo. I was supervised by Chris Eliasmith, and worked on a biologically plausible model of human knowledge representation. I also wrote an MPI implementation of the nengo neural simulator. In 2012 I obtained a BMATH(CS) degree, also from Waterloo, and spent my co-op terms working on a GPU implementation of nengo.
You can download my CV here.
Kroger, B., Crawford, E., Bekolay, T., and Eliasmith, C. (2016). Modeling interactions between speech production and perception: speech error detection at semantic and phonological levels and the inner speech loop. Frontiers in Computational Neuroscience. doi: 10.3389/fncom.2016.00051.
Crawford, E., Gingerich, M., and Eliasmith, C. (2015). Biologically plausible, human-scale knowledge representation. Cognitive Science. doi: 10.1111/cogs.12261.
Voelker, A., Crawford, E., and Eliasmith, C. Learning large-scale heteroassociative memories in spiking neurons. In Unconventional Computation and Natural Computation. London, Ontario, 07/2014 2014.
Crawford, E., Gingerich, M., and Eliasmith, C. (2013). Biologically plausible, human-scale knowledge representation. In 35th Annual Conference of the Cognitive Science Society, 412-417.