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个人简介
His current research uses machine learning to understand complex problems in human behavior, social policy, and especially medicine, where computational techniques have the potential to uncover biomedical insights from large-scale health data.
In past work he has combined insights from economics and behavioral science with causal inference tools—lab, field, and natural experiments—to study social problems such as discrimination and poverty. Papers include: the impact of poverty on mental bandwidth; how algorithms can improve on judicial decision-making; whether CEO pay is excessive; using fictitious resumes to measure discrimination; showing that higher cigarette taxes makes smokers happier; and modeling how competition affects media bias.
In past work he has combined insights from economics and behavioral science with causal inference tools—lab, field, and natural experiments—to study social problems such as discrimination and poverty. Papers include: the impact of poverty on mental bandwidth; how algorithms can improve on judicial decision-making; whether CEO pay is excessive; using fictitious resumes to measure discrimination; showing that higher cigarette taxes makes smokers happier; and modeling how competition affects media bias.
研究兴趣
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QUARTERLY JOURNAL OF ECONOMICS (2024)
Social Science Research Network (2024)
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PERSPECTIVES ON PSYCHOLOGICAL SCIENCEpp.17456916231212138-17456916231212138, (2023)
Proceedings of the National Academy of Sciences of the United States of Americano. 26 (2023): e2206054120-e2206054120
Nature Human Behaviourno. 11 (2023): 1-3
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