L. Amber Wilcox-O'Hearn


Greetings. I recently completed an M.Sc. in Computer Science here at the University of Toronto in the Computational Linguistics Research Group, under the direction of Graeme Hirst.

My primary research interest is in the properties that emerge from the way information is structured. For example, different languages (formal or natural) vary in robustness to error, potential for ambiguity, expressiveness, and susceptibility to inference.

My publications so far have explored this from the perspectives of coding theory, human memory, and natural language error correction:

Error-Detecting Properties of Languages Stavros Konstantinidis and Amber O'Hearn. 2002. Theoretical Computer Science 276 (1), 355-375

On a Simple Method for Detecting Synchronization Errors in Coded Messages Stravros Konstantinidis, Steven Perron, and L. Amber Wilcox-O'Hearn. 2003. Information Theory, IEEE Transactions on 49 (5), 1355-1363

Fragment memories mark the end of childhood amnesia Darryl Bruce, L. Amber Wilcox-O'Hearn, John A. Robinson, Kimberly Phillips-Grant, Lori Francis, and Marilyn C. Smith. 2005. Memory & cognition 33 (4), 567-576

Memory fragments as components of autobiographical knowledge Darryl Bruce, Kimberly Phillips-Grant, L. Amber Wilcox-O'Hearn, John A. Robinson, Lori Francis. 2007. Applied cognitive psychology 21 (3), 307-324

Real-word spelling correction with trigrams: A reconsideration of the Mays, Damerau, and Mercer model L. Amber Wilcox-O'Hearn and Graeme Hirst and Alexander Budanitsky. 2008. Computational Linguistics and Intelligent Text Processing, 605-616

A Noisy Channel Model Framework for Grammatical Correction L. Amber Wilcox-O'Hearn. 2013. CoNLL-2013, 109

I have also studied machine learning algorithms, and a variety of topics in linguistics and neuroscience.

I attended Hacker School for the summer, pursuing some interests in functional and concatenative programming languages, databases and filesystems, and topic modelling.