Welcome to my website! I am a Canadian statistician originally from Calgary, Alberta. 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.
Interests: In addition to the topics in my dissertation work, I enjoy thinking about philosophy and take heavy influence from Albert Camus, Michel Foucault, and the Tao Te Ching. I also engage in a variety of athletic activities including weight lifting and Judo, and I listen to a lot of music; heavy metal (specifically blackened symphonic deathcore) is my favourite genre.
Mission: One of the major problems in the world, in my opinion, 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.
I am committed to dismantling the grip of dichotomistic bias through various means including scientific unification of theory, bridging in communication between theorists and applied scientists, and 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".