We focus on the development, validation, application, and instruction of methods for 

• Causal inference

• Machine Learning

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Our main applications are for​ preventing HIV and improving community health.

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​Overall, our work is informed by cross-disciplinary real-world problems and aims to ensure methodological advances in Academia translate into real-world impact.