John Hughes: h-index, Total Citations, and Citation Map
John Hughes's h-index is 23 (36 i10-index, 1,988+ total citations across 109+ publications) according to Google Scholar as of June 2026. John Hughes is affiliated with Associate Professor, Lehigh University.
John Hughes is a researcher affiliated with Associate Professor, Lehigh University, specializing in dependent data, statistical computing, Bayesian methods. Their work has been cited 1,988 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
John Hughes's Citation Metrics
Bibliometric impact based on 109 indexed publications. Of these, 19 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 23
- i10-Index
- 36
- Total Citations
- 1,988
- Citing Countries
- 56
As of June 2026.
John Hughes has an h-index of 23 and 1,988 total citations across 109 publications, with research cited by institutions in 56 countries.
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Dimension reduction and alleviation of confounding for spatial generalized linear mixed models
2013443
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Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About John Hughes's research
John Hughes is a researcher in dependent data, statistical computing and Bayesian methods at Associate Professor, Lehigh University. Their work has been cited 1,988 times across 109 publications (h-index 23), according to Google Scholar.
Their most-cited work, “Dimension reduction and alleviation of confounding for spatial generalized linear mixed models” (2013), has accumulated 443 citations. Other influential works include “mcmcse: Monte Carlo standard errors for MCMC” (2017) with 195 citations and “Autologistic models for binary data on a lattice” (2011) with 130 citations.
Citations of John Hughes's research come primarily from United States, United Kingdom and Canada, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
