September 2023: I have made the decision to return to academia and am actively searching for a PhD position! I am primarily focused on fairness in multimodal foundational models for clinical medicine. I am also interested in general training dynamics of multimodal LLMs as well as their applied use cases (debiasing, ECG classification, etc.). Please e-mail me at johnc dot cs dot toronto dot edu to collaborate!
Hi! My name is John Chen and I am a second year medical student at McGill University, currently on leave. Previously, I completed my Master's and Bachelor's degree in Computer Science at University of Toronto, St. George Campus and Vector Institute under the supervision of Frank Rudzicz. During my time at U of T, I focused on a variety of topics in NLP, speech and fairness. Here are some of my selected publications:
Implemented vanilla recurrent neural network to perform language modelling and text classification. Coded the entire project end-to-end, implementing the DataSet, architecture, training loop and evaluation (using Pytorch). Modified network as necessary to deal with gradient exploding (implemented manual gradient clipping) and conversion between unsupervised and supervised use cases.
Performed logistic regression on a dataset provided by the Canadian Basketball Association and delivered data insights.
Architected and implemented the hardware system for an E2E house-plant IoT VoIP monitoring system. Talk to Plant allows you to call in from a mobile device to check on the status of your household plant, as monitored by various sensors hooked up to an ESP8266 Micro-controller.
GithubI've been lucky enough to attend the following hackathons! I am a big fan of hackathons as I feel they are great opportunities to sit down and build not only software, but build connections too!