I am a statistician and my research centers on the development of methodological aspects of structured probability models for large-scale multivariate problems, with applications ranging from financial time series to high-throughput cancer genomics. My work also pays special attention to the ...

I am interested in Bayesian Methods and Stochastic Optimization. Academic Posts:University of Texas at Austin, 2004–present; University of Michigan; Duke University Research Areas:Bayesian Methods, Knowledge Management, Option Pricing, Risk Management Industry Areas:Energy, ...

Lauren Ancel Meyers received her B.A. degree in Mathematics and Philosophy from Harvard University in 1996 and her Ph.D. from the department of Biological Sciences at Stanford University in 2000. She joined the faculty at the University of Texas at Austin in 2003 where she was recently promoted ...

I am interested in methods and applications of Bayesian inference. More specifically, I am working on nonparametric Bayesian inference, decision problems, and applications to biomedical research problems. Nonparametric Bayesian inference refers to prior models for infinite dimensional random ...

My research focuses on statistical methods for neural data and the neural mechanisms underlying statistical inference in the brain. I develop Bayesian methods for high-dimensional neural datasets, with an emphasis on point process regression, dimensionality reduction, feature selection, state space ...

My main area of research is in statistical machine learning. The core problem here combines the statistical imperative of inferring reliable conclusions from limited observations or data with the computational imperative of doing so with limited computation. Of particular interest are modern ...

I am a Bayesian statistician. I study problems in model selection and multiple testing; connections between machine learning and Bayesian shrinkage estimation; variable selection and high-dimensional inference in non-linear, non-Gaussian models; and structured models for covariance matrices. Lately ...

My research focuses on nonparametric function estimation and its application in energy economics, finance, marketing and transportation science. Current problems of interest include estimating univariate functions nonparametrically subject to shape constraints such as monotonicity and convexity, ...