Larry Dong

I am a fourth year PhD student in biostatistics at the Dalla Lana School of Public Health at the University of Toronto. My research interests revolve around dynamic treatment regimes (DTRs) and Bayesian methods and, on the software side, I take interest in making Bayesian software “better”. For my PhD, I am jointly supervised by Dr. Olli Saarela and Dr. Eleanor Pullenayegum and my thesis focuses on Bayesian estimation of optimal DTRs using irregularly observed data. I also contribute regularly to open-source packages, notably in the PyMC and Aesara ecosystem and, as of November 2022, I became a core developper of PyMC. I am also a GitHub Campus Expert and a co-founder of the Health Data Working Group.

Prior to my PhD studies, I have pursued a dual Master’s program: one MSc in biostatistics at McGill University and the other in Public Health Data Science at the University of Bordeaux. I was jointly supervised by Dr. Erica Moodie and Dr. Rodolphe Thiébaut, both of whom I look up to greatly and attribute a lot of my personal and professional growth.

In my free time, I enjoy coding in Python, skateboarding and eating copious amounts of fruit (especially grapes, bananas, oranges and watermelon). Feel free to connect with me! Tu peux aussi m’écrire en français <p>:)</p>.