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We focus on the development, validation, application, and instruction of methods for 
  • Causal inference
  • Machine Learning
Our main applications are for​ preventing HIV and improving community health.
​Overall, our work is informed by cross-disciplinary real-world problems and aims to ensure methodological advances in Academia translate into real-world impact.
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