Generate a tailored SOP for Dr. Frederick Eberhardt. Improve your application with a focused, well-structured draft.
Frederick Eberhardt's research interests lie at the intersection of formal philosophy of science, machine learning, and statistics in computer science. His work primarily focuses on methods for causal discovery and statistical data analysis, particularly the use of experiments in causal inference and integrating causal inferences from data sets with philosophical issues in the foundations of causality and probability. Eberhardt also explores computational models relevant to cognitive science, drawing on historical philosophical work, notably that of Hans Reichenbach, and addresses the frequentist interpretation of probability.
Most Caltech graduate programs are PhD-only. GRE General and Subject tests vary by department; many have made them optional or no longer accept them.