Cameron Dufault

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I'm a first year MSc Computer Science student at the University of Toronto, researching methods of representation learning of biological data supervised by Dr. Alan Moses.

I recently helped author a review of current applications of Large-Language Models to genomic data. Building upon this, my current research project Biologically Grounded Large Language Models for Whole-Genome Representation Learning seeks to apply language models not for modeling interactions between nucleotides, but the language of repeated genomic elements common across the genomes of many species.

me

Background



I have previously worked on many different research projects utilizing ML to learn from many forms of biological data. Most recently, (May 2022 to May 2023) I worked with Dr. Kieran Campbell and Dr. Rod Bremner of the Lunenfeld-Tanenbaum Research Institute to analyze single-cell RNA sequencing data and investigate whether we can classify all cancers into binary pan-cancer classes. See my CV for more.

Beyond my research work I have interned as a Data Scientist at RBC and as Machine Learning Software Engineer at RBC's AI research institute Borealis AI. I also acted as Project Leader and Director of Projects of the McMaster AI Society, where I helped undergraduate students learn ML skills by collaborating with McMaster faculty on projects applying machine learning to their area of research.