Spring 2026
COS 598D
Empirical Research Methods for CS (Website)
Establishing causal claims and evaluating systems and models are at the core of modern Computer Science research. This course provides a rigorous introduction to empirical methods, combining foundational theory on causal inference with practical applications. Topics include causal diagrams, experimental and quasi-experimental designs, regression analysis, and benchmarks. Evaluation is based on weekly programming assignments, active class participation, and a final paper in which students develop and motivate a research project proposal.
Spring 2025
COS 598B
Machine Behavior (Website)
Machine learning models are everywhere, and their role in society may increase as they become more popular and influential. At the same time, recent work has shown that LLMs can simulate and predict human behavior remarkably well. Thus, understanding and steering the behavior of such systems can amplify their benefits, mitigate their harms, and increase our understanding of human behavior. This seminar course aims to facilitate publishable student research on these broad topics. Coursework is a mix of readings and a research project.