I am defending my PhD in the Societal Computing program at Carnegie Mellon University’s School of Computer Science. I am co-advised by Dr. Jürgen Pfeffer, formerly of CMU's Institute for Software Research and now at the Technical University of Munich, and by Dr. Anind K. Dey, formerly of CMU’s Human-Computer Interaction Institute and now at the University of Washington.
My work brings statistical modeling to bear on critical, reflexive questions with and about social networks in large-scale digital trace data. I am broadly concerned with issues of algorithmic power and control, and of validity and rigor in computational social science; understanding the possible ways in which social media and other large-scale trace data may give a distorted picture of human behavior will allow us to make generalizations that are robust across time, platforms, and contexts, and that can ultimately inform just and effective policy-making.
In addition to doing empirical work modeling social media and mobile phone sensor data, I work on how to understand statistics, machine learning, and data science from critical and constructivist perspectives, on ethical and policy implications of predictive modeling, and on understanding and communicating foundational problems in statistical models of social networks.