Match tier
Likely match
Presence
Current · Arkansas
Last published
2026
Sources
OpenAlex · ORCID
Refreshed
2026-10-01
C
Cade Wagner
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.
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1 pubs
Research Areas
Biography and Research Information
OverviewAI-generated summary
Cade Wagner's research focuses on applying machine learning to predict barge tow sizes on inland waterways. This work utilizes vessel trajectory data to derive features for predictive modeling, as demonstrated in his proof-of-concept study published in 2026. His research contributes to the understanding of maritime logistics and transportation analytics.
Metrics
- Publications: 1
Selected Publications
-
Predicting barge tow size on inland waterways using vessel trajectory-derived features: proof of concept (2026)
Collaboration Network
Top Collaborators
Geoffery Agorku
University of Arkansas at Fayetteville
1 shared publication
In database
- Predicting barge tow size on inland waterways using vessel trajectory-derived features: proof of concept
Sarah V. Hernandez
University of Arkansas at Fayetteville
1 shared publication
In database
- Predicting barge tow size on inland waterways using vessel trajectory-derived features: proof of concept
Hayley Hames
University of Arkansas at Fayetteville
1 shared publication
In database
- Predicting barge tow size on inland waterways using vessel trajectory-derived features: proof of concept
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