Link Search Menu Expand Document

Welcome to the AME Lab!

The Almost Matching Exactly Lab provides a range of matching methods for causal inference using statistical machine learning algorithms.

View us on GitHub


About

The Almost Matching Exactly Lab is a joint venture of the Departments of Computer Science and Statistics at Duke University in Durham, North Carolina. Our goal is to develop and apply interpretable machine learning algorithms to estimate causal effects using observational data. In general, our algorithms match units with similar covariate distributions, creating high quality, exact or almost exact matches for treatment effect estimation. To learn more about how these algorithms work, visit our algorithm overview page or read one of our publications. To begin using one of our matching methods, choose a software package and get started!

People

Professors

Professors


Sudeepa Roy

Computer Science

Cynthia Rudin

Computer Science

Alexander Volfovsky

Statistics

Graduate Students

Graduate Students


Neha Gupta

Economics

Srikar Katta

Computer Science

Vittorio Orlandi

Statistics

Harsh Parikh

Computer Science

Quinn Lanners

Biostatistics and Bioinformatics

Undergraduates

Undergraduates


Haoning Jiang

Computer Science

Alumni

Alumni


Muhammad Usaid Awan

Economics

Angikar Ghosal

Computer Science

Thomas Howell

Computer Science and Mechanical Engineering

Saksham Jain

Electrical and Computer Engineering

Marco Morucci

Political Science

Xian Sun

Computer Science

Tianyu Wang

Computer Science