
About
David Bickel is a Professor in the School of Information, Library, and Research Sciences at the University of North Carolina at Greensboro. With a PhD from the University of North Texas and undergraduate studies at Baylor University, he has established himself as a leading researcher in statistical methodology for genomic and biological data analysis.
Dr. Bickel's research focuses on empirical Bayes methods, false discovery rates, uncertainty quantification, and information theory. His work bridges theoretical statistics with practical applications in genomics, molecular evolution, metabolomics, and proteomics. He has developed several influential software packages including LFDRenrich, LFDRhat, and LFDREmpiricalBayes that implement his methodological contributions.
His publications reveal a consistent focus on improving statistical inference in high-dimensional biological data, with particular attention to proper calibration of statistical evidence and uncertainty quantification. His work helps researchers navigate the challenges of multiple testing that are ubiquitous in modern genomics.
Dr. Bickel has authored three major books: Phylogenetic Trees and Molecular Evolution: A Hands-on Introduction with Uncertainty Quantification, Genomics Data Analysis: False Discovery Rates and Empirical Bayes Methods, and a book on Bayes-frequentist statistics that explores integrating these complementary approaches.
His research has practical impact across biological sciences, providing methodological tools that help scientists extract reliable insights from complex data while properly accounting for statistical uncertainty. His software implementations make advanced statistical methods accessible to domain scientists who may not have deep statistical expertise.
Dr. Bickel maintains an active research program as evidenced by recent publications and software updates, continuing to contribute to the evolving field of statistical genomics and bioinformatics.
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