Statistical Science

Zaid Abdo, Ph.D.
Associate Professor
Here are the areas I am interested in, listed in order of interest: Bioinformatics, Statistical Genetics, Bayesian Statistics, Mathematical Biology, Stochastic Processes & Optimization
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Brian Dennis
Professor
Research interests: Statistical Ecology, Biometrics, Mathematical Modeling, Theoretical Ecology, Conservation Biology, Population Dynamics
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Paul Hohenlohe, Ph.D.
Assistant Professor
Our research focuses on the genomic architecture of evolving populations, developing sophisticated theory and analytical tools to harness the power of modern DNA sequencing technology. We address basic questions of evolutionary biology as well as applications to conservation and cancer biology.
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Timothy R. Johnson, Ph.D.
Associate Professor
Currently, most of my research concerns ordinal variables and random utility models for categorical data. More broadly I am interested in categorical data, latent variable models, measurement error models, simulation-based computations for inference, and Bayesian statistics. I sometimes collaborate in research in judgment and decision making.
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Paul Joyce, Ph.D.
Professor|Director of BCB
My research focuses on developing and rigorously testing statistical methods and stochastic models to describe genetic phenomena. These include models and methods to: predict how viruses adapt; show the effect of antibiotic resistance genes encoded on plasmids; predict ancestral relationships among species; and to understand the ecological structure of bacterial communities in biofilms. This broad focus has lead to collaborations with researchers in phylogenetics, population genetics, theoretical ecology, mircobial ecology, experimental evolution, conservation genetics, and the list is growing.
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Stephen Sauchi Lee, Ph.D.
Associate Professor
My general research area is Multivariate and Computational Statistics. It includes: Integrating models and methods from statistics, neural networks, machine learning, and data mining communities to discover relationships and recognize patterns in databases; modeling using regression and classification for interpretation and forecasting; extracting information and patterns; and developing computational algorithms to increase efficiency and prediction accuracy.
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Shafii, Bahman Ph.D.
Professor

(208) 885-9498 | bshafii@uidaho.edu
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Michelle Wiest, Ph.D.
Assistant Professor
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Christopher Williams, Ph.D.
Professor
Affiliate Professor of Bioinformatics and Computational Biology
My research interests are on problems in statistical genetics, biostatistics, and statistical methods applied to issues in natural resources. One of the topics that I work on is the analysis of human twin data. Another area of interest is the estimation of disease prevalence from various types of data, such as in groups of fish that are collected and have their tissue pooled to test for disease status.
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