Associate Professor of Statistical Science
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Research in high-dimensional inference, nonparametric methods, Bayesian modeling, and biostatistics. Tackling statistical and computational challenges in analyzing big data. A recent focus of my research is on using multi-scale techniques to construct flexible probability models that can be applied to massive data sets. Traditional nonparametric approaches, while enjoying many established theoretical properties, are often computationally intractable for big data. Multi-scale inference provides a general framework for tackling the computational bottleneck while preserving the theoretical guarantees enjoyed by classical methods.