Assistant Professor of Biostatistics
Harvard T.H. Chan School of Public Health
Department of Biostatistics
655 Huntington Avenue, Building 1, Room 419
Boston, Massachusetts 02115
I'm interested in using statistics to understand the molecular mechanisms of diseases of aging. My methodological research has focused on:
- robustness to model misspecification,
- nonparametric Bayesian models,
- frequentist analysis of Bayesian methods, and
- efficient algorithms for inference in complex models.
- studying Alzheimer's disease using whole-genome sequences, and
- inferring cancer tumor phylogenetic trees (clonal evolution).
Flexible models for microclustering with application to entity resolution, B. Betancourt, G. Zanella, J. W. Miller, H. Wallach, A. Zaidi, and B. Steorts, Advances in Neural Information Processing Systems (NIPS), Vol. 29, 2016, pp. 1417-1425. (pub) (pdf) (arXiv)
Microclustering: When the cluster sizes grow sublinearly with the size of the data set, J. W. Miller, B. Betancourt, A. Zaidi, H. Wallach, and R. C. Steorts, Bayesian Nonparametrics: The Next Generation workshop, NIPS 2015. (pdf) (arXiv)
A simple example of Dirichlet process mixture inconsistency for the number of components, J. W. Miller and M. T. Harrison, Advances in Neural Information Processing Systems (NIPS), Vol. 26, 2013. (pub) (pdf) (arXiv)
Nonparametric and Variable-Dimension Bayesian Mixture Models: Analysis, Comparison, and New Methods,
J. W. Miller, Brown University, Division of Applied Mathematics, 2014.
(Received the Brown University Outstanding Dissertation Award in the Physical Sciences, generously sponsored by the Joukowsky Family Foundation.)
A practical algorithm for exact inference on tables, J. W. Miller and M. T. Harrison, Proceedings of the Joint Statistical Meetings 2010, Statistical Computing Section.