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I am ML research scientist at Abridge working on training language models that aid and assist doctors in various clinical documentation tasks. I obtained a computer science Ph.D. at the University of Toronto and was a graduate student researcher at the Donnelly Centre for Cellular and Biomolecular Research and the Vector Institute for Artificial Intelligence, where my work centred on natural language processing (NLP) and natural language understanding (NLU) of scientific text, particularly biomedical literature. I previously interned at Ai2 (on the Semantic Scholar team) and at Semantic Health. I completed an undergraduate degree at the University of Ottawa, graduating with a B.Sc in biochemistry. I completed an M.Sc. in computer science at the University of Toronto. When I am not 💻 I like to 🚵♂️, 🏂 and 🏋️♂️.
The corresponding code from our paper "DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations". Do not hesitate to open an issue if you run into any trouble!
The corresponding code for our paper: "Exploring the Challenges of Open Domain Multi-Document Summarization". Do not hesitate to open an issue if you run into any trouble!
This repository contains supplementary data, and links to the model and corpora used for the paper: Transfer learning for biomedical named entity recognition with neural networks.
A set of notes, in the form of a simple Github Pages site, which will serve as a complete crash course on the various areas of mathematics essential to understanding machine learning.
