I am currently employed as a post-doctoral fellow at Harvard University. I completed my undergraduate degree in Psychology at the University of Toronto and in 2014, I completed a PhD and an MBA in Behavioral Science at the University of Chicago Booth School of Business.
My research program is focused on the Behavioral Science of Big Data - how new datasets and algorithms are changing our daily life, and expanding the researcher toolbox. These tools can be brought to bear on three kinds of problems in the modern world. One problem is “quantification” - algorithms can be combined with natural trace data to measure behavior like never before. Another problem is “prediction” - the forecasting power of machine learning algorithms can be used to better understand ourselves, and others. The final problem is “collaboration” - despite their efficacy, the scope of these tools can be constrained by our willingness to accept them in our lives. In each case, big data can help to uncover the roots of our decision-making, while nurturing and guiding our behavior outside the lab.