Frederick Eberhardt
Institute of Cognitive and Brain Sciences
3210 Tolman Hall MC 3129
UC Berkeley
Berkeley, CA 94720, USA
fde [at] berkeley [dot] edu
office: 5427 Tolman Hall
Currently I am a Postdoc in Philosophy and Psychology at the University of California, Berkeley. I am part of the Causal Learning Collaborative Initiative supported by the James S. McDonnell Foundation, which brings together researchers from psychology, philosophy and cognitive science, and is led by Alison Gopnik.
I am interested in causation and experimentation and everything that connects the two: How can we learn about causal structure, how should we learn about causal structure and how do we learn about causal structure? The research draws on ideas from philosophy, statistics, machine learning and cognitive science.
At Berkeley I am working on formal models of how humans use interventions to learn about causal structure, from my PhD thesis with Richard Scheines and Clark Glymour at Carnegie Mellon University I am interested in optimal sequences of experiments to discover causal structure under a wide variety of assumptions, and with Clark Glymour I have been working on various historical projects on Hans Reichenbach, tracing the origins of modern causal models.
I started with philosophy and mathematics at the London School of Economics, continued with a Masters in Knowledge Discovery and Datamining from the (now) Machine Learning Department (School of Computer Science) at Carnegie Mellon and received a PhD in Logic, Computation and Methodology from the Department of Philosophy at Carnegie Mellon.