Ran Dai received her PhD in Statistics at the University of Chicago in July 2020. Ran’s research interest is in high dimensional inference, nonparametric modeling, and shape-constrained regressions, multiple testing, and causal inference. In particular, Ran is interested in developing computationally efficient algorithms for these problems with statistical convergence guarantee and valid inference; and applying these methods towards real datasets in the areas of drug development, HIV mutation study and cancer study.

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