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"USGS Staff Profile": { "@context": "https://schema.org", "@type": "Person", "dateModified": "2024-09-21T07:57:19.118453", "name": "Jacob DeAngelo", "identifier": [ { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-7348-7839" } ], "jobTitle": "Geologist", "hasOccupation": [ { "@type": "OrganizationalRole", "startDate": "2024-09-21T07:57:19.124322", "affiliatedOrganization": { "@type": "Organization", "name": "Geology, Minerals, Energy, and Geophysics Science Center", "url": "https://www.usgs.gov/centers/gmeg" }, "roleName": "Geologist" }, { "@type": "Occupation", "additionalType": "self-claimed professional experience", "name": "2021 \u2013 Present, Geologist, Geology Minerals Energy and Geophysics Science Center, Moffett Field, CA" }, { "@type": "Occupation", "additionalType": "self-claimed professional experience", "name": "2008 - 2021, Cartographer, Geology Minerals Energy and Geophysics Science Center, Moffett Field, CA." } ], "description": [ { "@type": "TextObject", "additionalType": "short description", "abstract": "Geologist with the Geology, Minerals, Energy, and Geophysics Science Center" }, { "@type": "TextObject", "additionalType": "staff profile page introductory statement", "abstract": "Jacob DeAngelo is a Geologist with the GMEG Science Center in Moffett Field, CA. He received an M.S. degree in Geosciences from San Francisco State University and a B.S. in Geography and Environmental Science from the University of Oregon." }, { "@type": "TextObject", "additionalType": "personal statement", "abstract": "Since joining the USGS in 2008 as a Geologist, Jacob has devoted his career to studying geothermal resources and specializes in feature engineering with spatial data and machine learning based predictive modeling. Presently, his research focuses on producing geothermal assessments and products used to create them. is a member of the Geothermal Resource Investigations Project (GRIP) at USGS. Jacob is a core member of GRIP\u2019s small machine learning team, seeking to apply well founded modeling approaches in predictive models used to characterize geothermal resource potential in the US. Jacob specializes in work with spatial data, using GIS and programming to engineer features for our predictive models from geologic and geophysical data." } ], "email": "jdeangelo@usgs.gov", "url": "https://www.usgs.gov/staff-profiles/jacob-deangelo", "affiliation": [], "hasCredential": [ { "@type": "EducationalOccupationalCredential", "name": "M.S. Geosciences, San Francisco State University, 2019" }, { "@type": "EducationalOccupationalCredential", "name": "B.S. Physical Geography and Environmental Science, Biology minor, University of Oregon, 2006" } ], "knowsAbout": [ { "@type": "Thing", "additionalType": "self-claimed expertise", "name": "Geothermal" } ], "memberOf": { "@type": "OrganizationalRole", "name": "staff member", "member": { "@type": "Organization", "name": "U.S. Geological Survey" }, "startDate": "2024-09-21T07:57:19.118459" } }, "ORCID": { "@context": "http://schema.org", "@id": "https://orcid.org/0000-0002-7348-7839", "@reverse": {}, "@type": "Person", "familyName": "DeAngelo", "givenName": "Jacob", "mainEntityOfPage": "https://orcid.org/0000-0002-7348-7839" }, "OpenAlex": { "created_date": "2023-07-21", "display_name": "Jacob DeAngelo", "display_name_alternatives": [ "J. 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