Item talk:Q46525: Difference between revisions

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    timestamp: '2023-09-30T16:43:22.341883'
    url: https://www.usgs.gov/staff-profiles/scott-hamshaw
  profile:
    abstracts: []
    affiliations: []
    education:
    - Ph.D. Civil & Environmental Engineering, University of Vermont, 2018
    - P.E., State of Vermont, License No. 100919, 2015
    - M.S. Civil & Environmental Engineering, University of Vermont, 2014
    - B.A. Engineering, St. Michael's College, 2006
    - B.S. Civil Engineering, University of Vermont, 2006
    email: shamshaw@usgs.gov
    expertise_terms:
    - Machine Learning
    - Surface Water
    - Hydrologic Modeling
    - Sediment Transport
    - Land Surveying
    - Data Science
    honors: []
    intro_statements:
    - Scott Hamshaw, Ph.D., P.E. is a Machine Learning Specialist in the Analysis
      & Prediction Branch of the USGS Water Resources Mission Area.
    name: Scott Hamshaw, Ph.D., P.E.
    name_qualifier: null
    orcid: 0000-0002-0583-4237
    organization_link: https://www.usgs.gov/mission-areas/water-resources
    organization_name: Water Resources Mission Area
    personal_statement: "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."
    professional_experience:
    - Machine Learning Specialist, U.S. Geological Survey, Water Mission Area - 2021
      to present
    - Research Assistant Professor, Civil & Environmental Engineering, University
      of Vermont - 2019 to 2021
    - Post-Doctoral Associate, Vermont EPSCoR, University of Vermont - 2017 to 2019
    - Research Assistant, Civil & Environmental Engineering, University of Vermont
      - 2011 to 2017
    - Staff Engineer, Engineered Solutions, Inc., Burlington, VT - 2007 to 2010
    title: Machine Learning Specialist

Latest revision as of 20:33, 22 September 2024

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