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I'm a PhD student in biostatistics at the Dalla Lana School of Public Health at the University of Toronto. My current research focuses on dynamic treatment regimes (and causal inference, by extension), Bayesian methods and their intersections. I am also a core developper of PyMC, a Python library for Bayesian computation, where I primarily take interest in automatic log-probability inference, model visualization tools (via graphviz) and supporting (graduate) students to dive into the world of open-source (science). If you are interested in contributing or have any questions, please don't hesitate to ask on Discourse or/and pick an issue here!

At school, I am also part of the Health Data Working Group where we provide programming-related (mostly Git, so far) workshops to aid students in public health for their studies and research. During my free time, I enjoy skateboarding 🛹 and eating fruits 🍐. Feel free to connect with me!

Google Summer of Code (GSoC) is a great (paid!) opportunity for students to dive head first into the world of open-source by working on an appealing project under the mentorship of a more experienced developer. If you are interested in working with PyMC, please check out our 2024 project list and engage in conversation with prospective mentors (all of whom are amazing!) on our Discourse to express your interest and clarify any pre-requisite knowledge/steps. I have capacity to take 1 (maybe 2) student(s) to work on log-probability derivations for order statistics; if you are interested, do reach out!