Biography and Research Information
OverviewAI-generated summary
Laura Suzanne Ruhl-Whittle investigates the multi-scale spatiotemporal modeling of suspended sediment concentrations within the Upper Mississippi River. Her work utilizes automated machine learning (AutoML) approaches, integrating reflectance and topographic data to understand these concentrations. Ruhl-Whittle also explores the relationship between natural mineral crusts and kidney stones, drawing parallels between environmental observations and human health. She has collaborated with researchers at the University of Arkansas at Fayetteville, including B. G. Peter, Sahar Rezaei, Brad G. Peter, and Bradley George Peter, on multiple shared publications.
Metrics
- Publications: 2
Selected Publications
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Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data (2026)
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Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data (2026)
Collaboration Network
Top Collaborators
Sahar Rezaei
University of Arkansas at Fayetteville
2 shared publications
In database
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
Josh Weiss
2 shared publications
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
Danelle M. Larson
2 shared publications
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
Brad G. Peter
University of Arkansas at Fayetteville (US)
1 shared publication
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
Bradley George Peter
University of Arkansas at Fayetteville (US)
1 shared publication
- Multi-scale spatiotemporal modeling of suspended sediment concentrations across the Upper Mississippi River using AutoML and coupled reflectance and topographic data
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