John P. Huelsenbeck

John P. Huelsenbeck is the McCreight Chancellor’s Chair in Computational Biology and a Professor at the University of California, Berkeley. His research focuses on developing and applying Bayesian statistical methods to phylogenetic analysis, computational biology, and evolutionary processes. He has contributed extensively to software tools such as MrBayes and RevBayes, which are widely used for Bayesian phylogenetic inference. His work addresses challenges in phylogenetic model selection, accommodating phylogenetic uncertainty, and integrating genomic data into evolutionary studies.

Key research areas include Bayesian inference of phylogeny, statistical phylogenetics, and the development of high-performance computational libraries like BEAGLE. He explores topics such as host-parasite cospeciation, molecular clock relaxations, and the impact of dependent evolution in sequence analysis. His projects often involve collaborations in computational methods and their applications to understanding biodiversity, viral evolution (e.g., SARS-CoV-2), and adaptation in desert ecosystems.

Publications highlight advancements in phylogenetic algorithms, model choice methodologies, and applications to diverse datasets ranging from bacteriophage evolution to crinoid taxonomy. His work emphasizes rigorous statistical frameworks and computational efficiency, making significant contributions to both theoretical and applied evolutionary biology.