Match tier
Likely match
Presence
Current · Arkansas
Last published
2025
Sources
OpenAlex · ORCID
Refreshed
2026-08-15
J
Jon Johnson
This is a likely match — the affiliation was inferred from OpenAlex, ORCID, and web sources but has not been fully confirmed. Treat with appropriate caution.
Researcher
Unknown Researcher
4 h-index
9 pubs
67 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Jon Johnson's research utilizes machine learning to predict sand modal composition, as demonstrated by the development of the GloPrSM model. His work also explores principal-agent dynamics and examines the consequences of selecting qualified lead independent directors within a quad model framework. Johnson has published nine papers and has a citation count of 62, with an h-index of 4. He has collaborated with Alan E. Ellstrand, Glenn R. Sharman, and Jason W. Ridge, all from the University of Arkansas at Fayetteville, on multiple publications.
Metrics
- h-index: 4
- Publications: 9
- Citations: 67
Selected Publications
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New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors (2025)
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GloPrSM: Global Prediction of Sand Modal Composition (2022)
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GloPrSM: Global Prediction of Sand Modal Composition (2022)
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Toward An Affect Based View of Principal–Agent Dynamics (2022)
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Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model (2022)
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Process network modularity, commonality, and greenhouse gas emissions (2019)
Collaboration Network
Top Collaborators
Glenn R. Sharman
University of Arkansas at Fayetteville
3 shared publications
In database
- Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model
- GloPrSM: Global Prediction of Sand Modal Composition
- GloPrSM: Global Prediction of Sand Modal Composition
Eugene Szymanski
Utah Geological Survey (US)
3 shared publications
- Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model
- GloPrSM: Global Prediction of Sand Modal Composition
- GloPrSM: Global Prediction of Sand Modal Composition
Xiao Huang
University of Arkansas at Fayetteville (US)
3 shared publications
- Machine Learning Applied to a Modern‐Pleistocene Petrographic Data Set: The Global Prediction of Sand Modal Composition (GloPrSM) Model
- GloPrSM: Global Prediction of Sand Modal Composition
- GloPrSM: Global Prediction of Sand Modal Composition
Alan E. Ellstrand
University of Arkansas at Fayetteville
2 shared publications
In database
- Toward An Affect Based View of Principal–Agent Dynamics
- New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors
Jacqueline Tilton
Walker (United States) (US)
1 shared publication
- Toward An Affect Based View of Principal–Agent Dynamics
Hansin Bilgili
Kansas State University (US)
1 shared publication
- Toward An Affect Based View of Principal–Agent Dynamics
Dinesh Hasija
Augusta University (US)
1 shared publication
- New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors
Jason W. Ridge
University of Arkansas at Fayetteville
1 shared publication
In database
- New sheriff in town: A quad model approach to examining the consequences of selecting a qualified lead independent directors
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