Frederick Eberhardt’s research primarily focuses on methods for causal inference and how we might learn about causal relations from data. His research projects generally fall in an area of overlap between philosophy, machine learning, statistics, and cognitive science. He has also done some historical work on the philosopher Hans Reichenbach, especially on his frequentist interpretation of probability.

Frederick Eberhardt is Professor of Philosophy at Caltech, with an affiliate appointment in Computing & Mathematical Sciences. Before coming to Caltech in 2013, Eberhardt was an assistant professor in the Philosophy-Neuroscience-Psychology program in the department of philosophy at Washington University in St. Louis. He spent a year as a McDonnell Postdoctoral Fellow at the Institute of Cognitive and Brain Sciences at the University of California, Berkeley. He holds a PhD in Logic, Computation and Methodology from the department of philosophy at Carnegie Mellon University (CMU), and a masters in Knowledge Discovery and Data Mining from what is now CMU’s Machine Learning Department.