Statistics Research

Our faculty conduct research across a broad range of foundational and emerging areas of statistics and data science. They are renowned experts in their fields and their work drives progress and knowledge-generation within statistical sciences and across disciplines.

Foundational areas

Biostatistics and Bioinformatics Listed under Biostatistics research
Clinical Trials, Study Protocol and Experimental Design William Rosenberger, Pramita Bagchi, Brett Hunter, Jiayang Sun
Semiparametric and Nonparametric Analysis Wanli Qiao, Jiayang Sun, Lily Wang
Measurement Error and Selection Bias Jonathan Auerbach, David Kepplinger, Jiayang Sun
Geometric Data Analysis, Random Fields, and Inference for Geometric Objects Wanli Qiao, Jiayang Sun
Bayesian Analysis and Inference Jonathan Auerbach, Isuru Dassanayake
Spatial, Temporal, Functional Data Pramita Bagchi, Ben Lee, Lily Wang
Simultaneous Inference, Multiple Comparisons, and Extreme value theory Brett Hunter, David Kepplinger, Jiayang Sun
High-dimensional or Big Data Inchi Hu, Pramita Bagchi, David Kepplinger, Ben Lee, Jiayang Sun

Emerging areas

Crowdsourcing and Modern Sample Surveys Jonathan Auerbach, Jiayang Sun
Natural Language Processing, Statistics for Electronic Health Records (EHR and Multisourced data) David Iain Holmes, David Kepplinger, Martin Slawski, Jiayang Sun
Machine Learning (ML), Artificial Intelligence (AI), and Interface of Statistics and Computer Science Inchi Hu, David Kepplinger, Wanli Qiao, Martin Slawski, Jiayang Sun, Anand Vidyashankar, Lily Wang
Statistical Privacy and Security Analytics, Compliance and Regulatory Anand Vidyashankar
Statistical Computing, Visualization and Data Mining David Kepplinger, Ben Lee, Niloofar Ramezani, Jiayang Sun
Data Compression, Record Linkage, and Feature Selection David Kepplinger, Martin Slawski, Jiayang Sun
Statistical Imaging, Mixture Models, and Causal Inference David Kepplinger, Inchi Hu, Jiayang Sun

Further data analytics research is listed under Data Analytics research.