• Warren Alpert Fellow, Stanford
  • PhD, Duke
  • MS, Chicago
  • MS, Yale
  • BS, Johns Hopkins

I am a statistician and machine learning scientist developing novel methodology and theory motivated by biomedical and econometrics applications.

I am broadly interested in

  • Bayesian Statistics and Decision Theory

  • Sampling Methods and Generative Modeling

  • Deep Learning and Artificial Intelligence

On the more mathematical front, I am interested in graphs, geometry, concentration of measure and optimal transport.

Currently, I am the Warren Alpert Fellow in AI and Computational Biology at Stanford, working with Barbara Engelhardt. Prior to that, I received my PhD in Statistical Science from Duke, advised by David Dunson. I also hold degrees in biomedical engineering and computer science from Johns Hopkins, Yale and Chicago.

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