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- David B. Dunson

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Mathematics
D-index
71
Citations
47,764
340
World Ranking
112
National Ranking
63

2010 - COPSS Presidents' Award For his wide-ranging and fundamental contributions to the development of parametric and nonparametric modeling within complex Bayesian frameworks; for making significant concurrent scientific progress in machine learning through this development; for use of this methodology in substantive applications, notably in reproductive epidemiology; and for outstanding service to the profession as well as mentoring of students and post-doctoral researchers.

2007 - Fellow of the American Statistical Association (ASA)

- Statistics
- Artificial intelligence
- Normal distribution

His scientific interests lie mostly in Statistics, Bayesian probability, Applied mathematics, Prior probability and Algorithm. Bayesian probability is closely attributed to Data mining in his study. His Applied mathematics research includes elements of Lasso, Convergence of random variables, Multivariate random variable and Random graph.

His study in Algorithm is interdisciplinary in nature, drawing from both Nonparametric statistics, Dirichlet process and Markov chain Monte Carlo. David B. Dunson has researched Dirichlet process in several fields, including Marginal likelihood, Hierarchical Dirichlet process and Markov chain. Dynamic Bayesian network and Probabilistic programming language is closely connected to Bayesian statistics in his research, which is encompassed under the umbrella topic of Variable-order Bayesian network.

- Bayesian Data Analysis (13605 citations)
- High cumulative incidence of uterine leiomyoma in black and white women: Ultrasound evidence☆☆☆★ (1344 citations)
- Changes with age in the level and duration of fertility in the menstrual cycle (411 citations)

His primary scientific interests are in Bayesian probability, Algorithm, Artificial intelligence, Statistics and Applied mathematics. The concepts of his Bayesian probability study are interwoven with issues in Inference and Data mining. His work in Algorithm tackles topics such as Markov chain Monte Carlo which are related to areas like Markov chain.

The study incorporates disciplines such as Machine learning and Pattern recognition in addition to Artificial intelligence. David B. Dunson performs multidisciplinary study in Applied mathematics and Gaussian process in his work. As a member of one scientific family, David B. Dunson mostly works in the field of Prior probability, focusing on Dirichlet process and, on occasion, Mixture model.

- Bayesian probability (30.64%)
- Algorithm (20.84%)
- Artificial intelligence (20.53%)

- Bayesian probability (30.64%)
- Algorithm (20.84%)
- Markov chain Monte Carlo (14.62%)

David B. Dunson mainly focuses on Bayesian probability, Algorithm, Markov chain Monte Carlo, Artificial intelligence and Inference. His Bayesian probability research incorporates themes from Mixture model, Multivariate statistics, Data mining and Cluster analysis. His Markov chain Monte Carlo course of study focuses on Bayesian inference and Scalability.

His biological study spans a wide range of topics, including Machine learning and Pattern recognition. His research in Inference intersects with topics in Statistics and Latent variable. His study looks at the intersection of Prior probability and topics like Applied mathematics with Eigenvalues and eigenvectors and Rate of convergence.

- A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels (85 citations)
- Robust Bayesian Inference via Coarsening (73 citations)
- Scalable Bayes via Barycenter in Wasserstein Space (60 citations)

- Statistics
- Artificial intelligence
- Machine learning

His primary areas of study are Bayesian probability, Bayesian inference, Markov chain Monte Carlo, Artificial intelligence and Algorithm. His studies in Bayesian probability integrate themes in fields like Mixture model, Conditional probability distribution and Inference. His Bayesian inference study combines topics in areas such as Sampling and Scalability.

His studies deal with areas such as Embedding, Orthogonal matrix, Applied mathematics and Stiefel manifold as well as Markov chain Monte Carlo. David B. Dunson has included themes like Rate of convergence, Eigenvalues and eigenvectors and Hybrid Monte Carlo in his Applied mathematics study. His study looks at the relationship between Cluster analysis and topics such as MNIST database, which overlap with Data mining.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Bayesian Data Analysis

Andrew Gelman;John B. Carlin;Hal S. Stern;David B. Dunson.

**(1995)**

27792 Citations

High cumulative incidence of uterine leiomyoma in black and white women: Ultrasound evidence☆☆☆★

Donna Day Baird;David B. Dunson;Michael C. Hill;Deborah Cousins.

American Journal of Obstetrics and Gynecology **(2003)**

1996 Citations

Changes with age in the level and duration of fertility in the menstrual cycle

David B. Dunson;Bernardo Colombo;Donna D. Baird.

Human Reproduction **(2002)**

660 Citations

Increased infertility with age in men and women.

David B. Dunson;Donna D. Baird;Bernardo Colombo.

Obstetrics & Gynecology **(2004)**

544 Citations

Bayesian data analysis, third edition

A Gelman;JB Carlin;HS Stern;DB Dunson.

**(2013)**

528 Citations

The timing of the “fertile window” in the menstrual cycle: day specific estimates from a prospective study

Allen J Wilcox;David Dunson;Donna Day Baird.

BMJ **(2000)**

512 Citations

Genetic heterogeneity of diffuse large B-cell lymphoma

Jenny Zhang;Vladimir Grubor;Cassandra L. Love;Anjishnu Banerjee.

Proceedings of the National Academy of Sciences of the United States of America **(2013)**

512 Citations

The genetic landscape of mutations in Burkitt lymphoma

Cassandra Love;Zhen Sun;Dereje Jima;Guojie Li.

Nature Genetics **(2012)**

512 Citations

Multitask Compressive Sensing

S. Ji;D. Dunson;L. Carin.

IEEE Transactions on Signal Processing **(2009)**

486 Citations

Genetic and Functional Drivers of Diffuse Large B Cell Lymphoma.

Anupama Reddy;Jenny Zhang;Nicholas S. Davis;Andrea B. Moffitt.

Cell **(2017)**

462 Citations

King Abdullah University of Science and Technology

Aalto University

Temple University

University of Melbourne

Columbia University

National Institutes of Health

University of Helsinki

Cleveland Clinic

Vanderbilt University

National Institutes of Health

Profile was last updated on December 6th, 2021.

Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).

The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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