Item talk:Q49376
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ORCID:
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OpenAlex:
created_date: '2023-07-21' display_name: J. D. Smith display_name_alternatives: - Joe Smith - Jared Smith - Jared D. Smith - J. Smith - J. Denham Smith - J. D. 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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: Jared D. Smith, Ph.D., is a Machine Learning Specialist in the USGS Water Resources Mission Area. He is based in Reston, VA. additionalType: staff profile page introductory statement - '@type': TextObject abstract: Jared has a background in environmental systems engineering, spatial data analysis, and statistics. His previous research has coupled physical and mathematical models with statistical analyses to inform planning and management decisions for environmental, earth-energy, and water resources systems. Jared joined the USGS in 2021 after completing a postdoc at The University of Virginia, where he developed green infrastructure portfolio optimizations that were designed to be robust to Bayesian-estimated parametric uncertainty of a watershed model. Jared completed his Ph.D. at Cornell University, where his research addressed Appalachian Basin geothermal resource assessment and subsequent uncertainty assessments for deep geothermal district heating projects at the Cornell and West Virginia University campuses. Previous work has also addressed ice jam flood frequency analysis under climate change, applied to the Peace-Athabasca Delta in Canada. additionalType: personal statement - '@type': TextObject abstract: "\u200BCluster Analysis and Prediction of Flood Flow Metrics for Minimally\ \ Altered Catchments in the Conterminous United States, HydroML Symposium 2022" additionalType: staff profile page abstract - '@type': TextObject abstract: Discovering Flood Regions and Predicting Flood Flow Metrics to Inform Bridge Scour Studies in the Conterminous United States, National Hydraulic Engineering Conference, 2022 additionalType: staff profile page abstract email: jsmith@usgs.gov hasCredential: - '@type': EducationalOccupationalCredential name: "\u200BPh.D. Environmental and Water Resources Systems Engineering, Cornell\ \ University, 2019" - '@type': EducationalOccupationalCredential name: M.S. Environmental and Water Resources Systems Engineering, Cornell University, 2016 - '@type': EducationalOccupationalCredential name: B.S. Environmental Engineering, Clarkson University, 2013 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: '2024-05-12T15:17:41.378526' identifier: - '@type': PropertyValue propertyID: GeoKB value: https://geokb.wikibase.cloud/entity/Q49376 - '@type': PropertyValue propertyID: ORCID value: 0000-0003-3124-8255 jobTitle: Machine Learning Specialist knowsAbout: - '@type': Thing additionalType: self-claimed expertise name: Model Diagnostics - '@type': Thing additionalType: self-claimed expertise name: Machine Learning - '@type': Thing additionalType: self-claimed expertise name: Hydrologic Statistics - '@type': Thing additionalType: self-claimed expertise name: Optimization - '@type': Thing additionalType: self-claimed expertise name: Water Resource Management - '@type': Thing additionalType: self-claimed expertise name: Surface Water - '@type': Thing additionalType: self-claimed expertise name: Geothermal Resource Assessment - '@type': Thing additionalType: self-claimed expertise name: Heat Flow memberOf: '@type': OrganizationalRole member: '@type': Organization name: U.S. Geological Survey name: staff member startDate: '2024-05-12T15:17:41.376020' name: Jared Smith url: https://www.usgs.gov/staff-profiles/jared-smith
