Bio: Allison is a machine learning researcher, working as a postdoc with Barbara Engelhardt and Brandon Stewart at Princeton. She finished her PhD in 2016 (dissertation); her advisor was David Blei. She develops models for human-centered applications like recommendation systems and her inference algorithm of choice is stochastic variational inference, as it scales well to large data. She is interested in what happens after model fitting, including posterior predictive checks, user studies, and visualization. These steps are important not only for evaluating and improving our models, but also for integrating them into live systems and making their results accessible.
Her website can be found here.