11/3/2023 0 Comments Jing du texas a n mPut simply, I like to study the probabilistic structure and properties of processes that statisticians and others want to observe and analyze. My research interests fall under the general heading applied probability and stochastic processes. Title : Professor and Associate Department Head of Operations Others: Concentration inequalities and tail bounds Empirical processes Debiasing and sample-splitting Model misspecification Non-parametric regression Sufficient dimension reduction. Methodology: Semi-supervised inference Semi-parametric inference with high dimensional data Missing data and causal inference High dimensional inference Regularized estimation Non-asymptotic performance guarantees.Īpplications: Discovery research using EMR data Automated phenotyping Personalized medicine (treatment selection, treatment effects estimation, risk prediction, comparative effectiveness etc.) Some of my specific research interests are listed below. This has led me recently to considering problems of gene-environment interactions (where nutrition is the environment) and their effect on cancer, understanding the nature of dietary intake patterns in humans and the effect of those patterns on a host of diseases, and most recently, whether increasing physical activity increases the mean and decreases the variance of sleep efficiency.Įmail : research interests broadly lie at the interface of semi-parametric inference, high dimensional statistics and statistical learning in semi-supervised settings and weakly supervised settings, with applications in the statistical analysis of large and complex observational datasets arising in modern studies, especially biomedical studies such as electronic medical records (EMR). My main application interest lies in problems of nutrition and physical activity, both at the molecular level and in the individual level. My main general methods currently are in developing statistical methods within the frameworks of semiparametric and functional regression, understanding the structure of variability, and in latent variables especially as they arise in the case that important variables are measured with error and subject to excess zeros.
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