Maggie Wang

using causal inference to understand how the world works and what works in the world.

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I’m a fifth year PhD student in Biomedical Data Science at Stanford University and am fortunate to be advised by Mike Baiocchi.

I work on methods for designing randomized experiments to evaluate interventions that target and influence behaviors and decision-making. I especially care about measuring the impact of interventions in the public health and healthcare spaces, including empowerment self-defense programs that equip women and girls with skills to resist sexual assault and machine learning-based decision support tools that help physicians make better decisions for their patients.

Previously, I received a B.S. in Biomedical Engineering and in Computer Science from Johns Hopkins University. Before Stanford, I am grateful to have worked with Michael Miller at the Johns Hopkins Center for Imaging Science, Sharon Hori at the Stanford Canary Center for Early Cancer Detection, and Alain Trouvé at the ENS Paris-Saclay Centre Borelli.

news

Aug 27, 2025 Wrote a blog post for the Center for Democracy & Technology explaining why AI developers ought to make their risk appetites and risk tolerances more transparent and legible to the public.
Jun 2, 2025 Started a summer internship with the AI Governance Lab at the Center for Democracy & Technology (CDT) in Washington, DC. (Supported by the Stanford Tech Ethics & Policy Fellowship.)
Apr 3, 2025 Inspection-Guided Randomization: A Flexible and Transparent Restricted Randomization Framework for Better Experimental Design was accepted to the Journal of Educational and Behavioral Statistics!
Jan 30, 2025 Accepted into the 2025 graduate cohort for the Stanford HAI Tech Ethics & Policy (TEP) Summer Fellowship!