Item talk:Q46525

ORCID:

 '@context': http://schema.org
 '@id': https://orcid.org/0000-0002-0583-4237
 '@reverse':
   creator:
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       value: 10.1016/j.jhydrol.2020.125802
     name: Multivariate event time series analysis using hydrological and suspended
       sediment data
   - '@id': https://doi.org/10.5194/tc-13-3367-2019
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     name: Optimization of over-summer snow storage at midlatitudes and low elevation
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     name: Application of unmanned aircraft system (UAS) for monitoring bank erosion
       along river corridors
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     name: Impact of an Extreme Storm Event on River Corridor Bank Erosion and Phosphorus
       Mobilization in a Mountainous Watershed in the Northeastern United States
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     name: A New Machine-Learning Approach for Classifying Hysteresis in Suspended-Sediment
       Discharge Relationships Using High-Frequency Monitoring Data
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     name: Quantifying streambank movement and topography using unmanned aircraft
       system photogrammetry with comparison to terrestrial laser scanning
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     name: Rapid Flood Exposure Assessment of Vermont Mobile Home Parks Following
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 '@type': Person
 address:
   '@type': PostalAddress
   addressCountry: US
 alternateName: Scott Hamshaw
 alumniOf:
 - '@type': Organization
   alternateName: Deptarment of Civil & Environmental Engineering
   identifier:
     '@type': PropertyValue
     propertyID: RINGGOLD
     value: '2092'
   name: University of Vermont
 - '@type': Organization
   alternateName: School of Engineering
   identifier:
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     propertyID: RINGGOLD
     value: '2092'
   name: University of Vermont
 familyName: Hamshaw
 givenName: Scott
 mainEntityOfPage: https://orcid.org/0000-0002-0583-4237
 name: Scott D. Hamshaw

USGS Staff Profile:

 '@context': https://schema.org
 '@type': Person
 affiliation: []
 description:
 - '@type': TextObject
   abstract: Machine Learning Specialist with the Water Resources Mission Area
   additionalType: short description
 - '@type': TextObject
   abstract: Scott Hamshaw, Ph.D., P.E. is a Machine Learning Specialist in the Analysis
     & Prediction Branch of the USGS Water Resources Mission Area.
   additionalType: staff profile page introductory statement
 - '@type': TextObject
   abstract: "Scott Hamshaw received his Ph.D. in Civil & Environmental Engineering\
     \ from the University of Vermont where he undertook mapping of watershed erosion\
     \ and data-driven modeling of sediment transport in the Lake Champlain Basin.\
     \ After completing his Ph.D., he was a postdoctoral associate and research assistant\
     \ professor at the University of Vermont applying machine learning to water\
     \ resource problems as well as teaching land surveying and mapping. Prior to\
     \ his Ph.D., Scott worked as a consulting engineer in Burlington, VT practicing\
     \ stormwater management, water system design, and site engineering. Scott joined\
     \ the Analysis & Prediction Branch of the Water Resources Mission Area in 2021\
     \ and is based in Bristol, VT.Scott\u2019s interests are in the broad area of\
     \ applied machine learning and water resource engineering with emphasis on using\
     \ data-driven approaches to understand dynamics in streamflow and river water\
     \ quality. Scott is active in national-scale research on applying deep learning\
     \ methods to the prediction of water quantity and quality in rivers across the\
     \ U.S."
   additionalType: personal statement
 email: shamshaw@usgs.gov
 hasCredential:
 - '@type': EducationalOccupationalCredential
   name: Ph.D. Civil & Environmental Engineering, University of Vermont, 2018
 - '@type': EducationalOccupationalCredential
   name: P.E., State of Vermont, License No. 100919, 2015
 - '@type': EducationalOccupationalCredential
   name: M.S. Civil & Environmental Engineering, University of Vermont, 2014
 - '@type': EducationalOccupationalCredential
   name: B.A. Engineering, St. Michael's College, 2006
 - '@type': EducationalOccupationalCredential
   name: B.S. Civil Engineering, University of Vermont, 2006
 hasOccupation:
 - '@type': OrganizationalRole
   affiliatedOrganization:
     '@type': Organization
     name: Water Resources Mission Area
     url: https://www.usgs.gov/mission-areas/water-resources
   roleName: Machine Learning Specialist
   startDate: '2024-05-12T16:04:24.352805'
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Machine Learning Specialist, U.S. Geological Survey, Water Mission Area
     - 2021 to present
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Research Assistant Professor, Civil & Environmental Engineering, University
     of Vermont - 2019 to 2021
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Post-Doctoral Associate, Vermont EPSCoR, University of Vermont - 2017 to
     2019
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Research Assistant, Civil & Environmental Engineering, University of Vermont
     - 2011 to 2017
 - '@type': Occupation
   additionalType: self-claimed professional experience
   name: Staff Engineer, Engineered Solutions, Inc., Burlington, VT - 2007 to 2010
 identifier:
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   propertyID: GeoKB
   value: https://geokb.wikibase.cloud/entity/Q46525
 - '@type': PropertyValue
   propertyID: ORCID
   value: 0000-0002-0583-4237
 jobTitle: Machine Learning Specialist
 knowsAbout:
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Machine Learning
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Surface Water
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Hydrologic Modeling
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Sediment Transport
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Land Surveying
 - '@type': Thing
   additionalType: self-claimed expertise
   name: Data Science
 memberOf:
   '@type': OrganizationalRole
   member:
     '@type': Organization
     name: U.S. Geological Survey
   name: staff member
   startDate: '2024-05-12T16:04:24.350159'
 name: Scott Hamshaw, Ph.D., P.E.
 url: https://www.usgs.gov/staff-profiles/scott-hamshaw