Welcome to my website! I am a Canadian statistician currently working as a postdoctoral research fellow at Memorial Sloan Kettering Cancer Center. I recently completed my Ph.D at Southern Methodist University, with research taking place at the Medical Artificial Intelligence and Automation lab at UT Southwestern Medical Center. My dissertation itself consists of methodology that combines AI and classical statistics (linear and nonlinear Bayesian mixed models and Reinforcement Learning) to optimize response-adaptive radiotherapy plans, and my current research involves spatial genetic modelling of the tumor microenvironment in the context of immunotherapy research.
I believe that one of the major problems in the world is a phenomenon called dichotomistic bias: The human tendency to simplify phenomena by categorizing and imposing dichotomies. While dichotomies aren't necessarily bad in themselves, our tendency to simplify by imposing them when they aren't useful often gets in the way of justice, honesty, and good scientific research.
Some examples of dichotomistic bias have been pointed out by Stephen Senn in "Dichotomania: an obsessive compulsive disorder that is badly affecting the quality of analysis of pharmaceutical trials;" and by Frank Harrell in "Statistical Errors in the Medical Literature;" I believe the effects of this "dichotomaniac" cognitive bias also permeate society through a plethora of social and cultural issues beyond those outlined in the paper. I am committed to dismantling the grip of dichotomistic bias by counteracting false dichotomies with balance. In the words of Francois Chollet, "I want to write code that feels like art, and make art that thinks like code".
When I'm not doing statistics, you can usually find me at the Judo dojo (watch one of my competition matches here), or lifting weights at the gym. I also listen to a lot of music, and particularly enjoy blackened symphonic deathcore. I occasionally write reviews and interviews at Metal Exposure as well.