Dylan Spicker|They/Them

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About me

I am a PhD candidate (in Statistics) at the University of Waterloo , co-supervised by Michael Wallace and Grace Yi .

About Me

My work focuses on measurement error and causal inference. Briefly, measurement error occurs whenever we are interested in measuring something and we do a bad job of it. This happens in almost every study that is run, and unfortunately means that the conclusions that we draw may not be accurate: statistical work on measurement error tries to correct this. Causal inference asks questions of the form “Does $X$ cause $Y$?” [For instance “Does smoking cause lung cancer?” (yes, it does).] I have a keen interest in providing a theoretical basis for (comparatively) straightforward methods, which are easy to use for non-statisticians, while exhibiting provably good theoretical properties.

Outside of causal inference and measurement error, I am interested in machine learning, and in particular in trying to establish a statistical basis for novel machine learning techniques (including questions related to inference, interpretability, and model selection).

I previously did an undergraduate degree in Finance and Mathematics at Queen’s University (I transferred there after completing my first year at Waterloo/Laurier in the ‘Double Degree’ program), and a Master’s of Statistics at Waterloo.

Outside of my research, I pay very close attention to sports, mostly hockey, (and how statistics is, or should be, applied there), play music (without any connection to statistics), and enjoy board/video games (with varying degrees of statistical relevance). I have a cat (Charles) who is wonderful.

My Teaching

Contacting Me