Dhanya Sridhar works with David Blei to combine modern machine learning techniques with causal inference to study social science questions. She uses text and network data and adapts probabilistic models and deep learning methods to find causality. She applies causal inference in various ways, such as studying how language affects persuasion or political outcomes, how influence spreads in social networks, and whether algorithmic decisions learned from historical data are fair. She completed her Ph.D. in computer science at the University of California, Santa Cruz, working under the direction of Lise Getoor. Her research there was recognized with the president’s Dissertation of the Year fellowship.