For decades, the Department has been known as a leading center of statistical science, and as the premier center worldwide for research and education in Bayesian methods. Statistical Science at Duke helped advance and popularize the Bayesian statistical paradigm, which offers a prescriptive framework for using probabilistic models to make inferences about scientific and social phenomena. Nowadays, Bayesian methods are used in nearly every field of inquiry. In recent years, we have expanded our research and education portfolios in areas such as causal inference, data privacy, data science, machine learning, and optimization. We continue to be a center of intellectual leadership in Bayesian methods and to grow our reputation as a top-tier department at the forefront of research and education in statistical science more broadly.
Faculty Research Focus
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Filippo Ascolani, Assistant Professor of Statistical Science
Bayesian nonparametric theory and modelling, Theory of Bayesian computation and MCMC, Model-based clustering. Read More |
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David L. Banks, Professor of the Practice of Statistical Science |
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James O. Berger, Arts and Sciences Distinguished Professor Emeritus of Statistical Science |
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Mine Çetinkaya-Rundel, Professor of the Practice of Statistical Science |
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Merlise Clyde, Professor of Statistical Science |
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David B. Dunson, Arts and Sciences Distinguished Professor of Statistical Science |
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Alexander Fisher, Assistant Professor of the Practice of Statistical Science
Bayesian modeling, hierarchical models, scalable inference machinery, statistical computing. Read More |
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Alan E. Gelfand, James B. Duke Distinguished Emeritus Professor of Statistical Science |
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Amy H. Herring, Sara and Charles Ayres Distinguished Professor of Statistical Science Longitudinal and multivariate data, Hierarchical models, Latent variables, Bayesian methods, Missing and mismeasured data. Read More |
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Peter D. Hoff, Professor of Statistical Science
Multivariate analysis, multilinear modeling, small area inference, hierarchical modeling. decision theory. Read More |
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Edwin S. Iversen, Research Professor of Statistical Science
Problems at the interface between statistics and molecular biology, genetics, personalized medicine and epidemiology. Read More |
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Yue Jiang, Assistant Professor of the Practice of Statistical Science
Mediation analysis, survival analysis, statistical education, quantitative literacy, public health. Read More |
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Eric Laber, Professor of Statistical Science and Biostatistics and Bioinformatics Precision medicine, reinforcement learning, causal inference, non-standard asymptotics. Read More |
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Fan Li, Professor of Statistical Science
Causal inference in observational data, missing data, Bayesian variable selection and imaging analysis. Read More |
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Li Ma, Professor of Statistical Science Nonparametric methods, high-dimensional inference, scalable inference, Bayesian modeling. Read More |
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Simon Mak, Assistant Professor of Statistical Science
Reduction of big and high-dimensional data, scalable Bayesian methods, computer experiments, and Monte Carlo and Quasi-Monte Carlo sampling. Read More |
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Sayan Mukherjee, Professor of Statistical Science and Mathematics |
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Galen Reeves, Associate Professor of Electrical and Computer Engineering and Statistical Science
Signal processing, statistics, and information theory, with applications in high-dimensional statistical inference, compressed sensing, and machine learning. Read More |
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Jerome P. Reiter, Professor of Statistical Science
Data privacy and confidentiality, missing data, multiple imputation, data integration. Read More |
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Colin Rundel, Associate Professor of the Practice of Statistical Science Computing in statistics and data science education; Bayesian spatial methodologies. Read More |
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Scott C. Schmidler, Associate Professor of Statistical Science
Computational biology and biophysics, Monte Carlo algorithms, Convergence rates of Markov chains, Statistical shape theory. Read More |
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Rebecca C. Steorts, Associate Professor of Statistical Science Entity resolution (record linkage or deduplication), statistical machine learning, and Small area estimation. Read More |
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Maria Tackett, Assistant Professor of the Practice of Statistical Science Statistics pedagogy, writing interventions to help students understand complex statistical concepts, forensic evidence. Read More |
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Surya T. Tokdar, Professor of Statistical Science
Nonparametric Bayesian analysis, asymptotic theory, regression smoothing, quantile regression. Read More |
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Alexander Volfovsky, Associate Professor of Statistical Science
Causal inference, high dimensional data, network analysis. Read More |
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Mike West, Arts and Sciences Distinguished Professor of Statistics and Decision Sciences
Bayesian analysis, decision theory and casual prediction. Multivariate time series and dynamic modelling. Business, economic, finance and governmental applications. |
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Robert L. Wolpert, Emeritus Professor of Statistical Science
Spatial statistics, extreme events, stochastic processes, non-parametric Bayesian analysis, statistical synthesis of information. Read More |
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Jason Qian Xu, Assistant Professor of Statistical Science |