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orcid:
ORCiD:
   meta:
   meta:
     status_code: 200
     status_code: 200
Line 2,314: Line 2,314:
           url-name: Profile at USGS
           url-name: Profile at USGS
           visibility: public
           visibility: public
usgs_staff_profile:
USGS Staff Profile:
   meta:
   '@context': https://schema.org
    url: https://www.usgs.gov/staff-profiles/alison-appling
  '@type': Person
    timestamp: '2024-01-30T09:51:48.077388'
   affiliation: []
    status_code: 200
  description:
   profile:
  - '@type': TextObject
    name: Alison Appling, PhD
     abstract: Data Scientist with the Water Resources Mission Area
    name_qualifier: null
    additionalType: short description
     titles:
  - '@type': TextObject
    - Data Scientist
     abstract: Alison Appling, Ph.D., (she/her) is a data scientist and ecologist who
    organizations:
       applies machine learning and other data-driven methods to predict and understand
    - !!python/tuple
       water resources dynamics.
      - Water Resources Mission Area
     additionalType: staff profile page introductory statement
      - https://www.usgs.gov/mission-areas/water-resources
  - '@type': TextObject
    email: aappling@usgs.gov
     abstract: "Current RolesProject Manager: Predictive Understanding of Multiscale\
    orcid: 0000-0003-3638-8572
      \ Processes (PUMP)Task Lead: Advancing Machine Learning and Data Assimilation,\
     intro_statements:
      \ within the PUMP ProjectAlison studies the movement of energy, carbon, and\
    - Alison Appling, Ph.D., (she/her) is a data scientist and ecologist who applies
      \ nutrients through rivers, lakes, and floodplains to better predict and understand\
       machine learning and other data-driven methods to predict and understand water
      \ variations in water quality over space and time.As a machine learning modeler\
       resources dynamics.
      \ and biogeochemist, she seeks modeling advances that bring together scientific\
     expertise_terms:
      \ knowledge and data-driven models. \u201CProcess-guided deep learning\u201D\
     - Data science
      \ and \u201Cdifferentiable hydrology\u201D are two approaches on which she collaborates.As\
    - Ecology
      \ a data scientist, she conducts analyses in ways that are reproducible, efficient,\
     - Biogeochemistry
      \ and transparent, and she has developed tools and workflows to support others\
     - Rivers and streams
      \ in these goals.In her leadership roles, she facilitates fluid skill sharing\
     - Machine learning
      \ within teams and communities of practice, challenges individuals to excel\
     - Modeling
      \ in their projects and careers, and coordinates across projects to realize\
     professional_experience:
      \ the Water Mission Area\u2019s vision of broadly reusable, integrated tools\
     - Development Ecologist and Data Scientist, U.S. Geological Survey, 2019-Present
      \ for predicting water quantity and quality across the nation.Alison is based\
     - Ecologist, U.S. Geological Survey, 2016-2019
      \ in State College, PA, and is a member of the Analysis and Prediction Branch\
     - 'Postdoctoral Fellow, USGS Powell Center and University of Wisconsin-Madison.
      \ in the Integrated Modeling and Prediction Division in the Water Mission Area.\
      \ She is on the USGS career track called Equipment Development Grade Evaluation\
      \ (EDGE)."
     additionalType: personal statement
  email: aappling@usgs.gov
  hasCredential:
  - '@type': EducationalOccupationalCredential
     name: "Ph.D. Ecology, 2012. Duke University, Durham, NC. \nConnectivity Drives\
      \ Function: Carbon and Nitrogen Dynamics in a Floodplain-Aquifer Ecosystem.\
      \ Advisors: E. S. Bernhardt and R. B. Jackson"
  - '@type': EducationalOccupationalCredential
     name: "B.S. Symbolic Systems, 2004. Stanford University, Stanford, CA. \nCoursework\
      \ in computer science, decision analysis, logic, linguistics, and psychology."
  hasOccupation:
  - '@type': OrganizationalRole
     affiliatedOrganization:
      '@type': Organization
      name: Water Resources Mission Area
      url: https://www.usgs.gov/mission-areas/water-resources
    roleName: Data Scientist
     startDate: '2024-05-12T15:43:21.898129'
  - '@type': Occupation
     additionalType: self-claimed professional experience
    name: Development Ecologist and Data Scientist, U.S. Geological Survey, 2019-Present
  - '@type': Occupation
     additionalType: self-claimed professional experience
    name: Ecologist, U.S. Geological Survey, 2016-2019
  - '@type': Occupation
     additionalType: self-claimed professional experience
    name: 'Postdoctoral Fellow, USGS Powell Center and University of Wisconsin-Madison.
       Mentors: E. H. Stanley, J. S. Read, E. G. Stets, and R. O. Hall, 2015-2016'
       Mentors: E. H. Stanley, J. S. Read, E. G. Stets, and R. O. Hall, 2015-2016'
     - 'Postdoctoral Associate, University of New Hampshire. Mentor: W. H. McDowell,
  - '@type': Occupation
     additionalType: self-claimed professional experience
    name: 'Postdoctoral Associate, University of New Hampshire. Mentor: W. H. McDowell,
       2013-2015'
       2013-2015'
     - 'Postdoctoral Associate, Duke University. Mentor: J. B. Heffernan, 2012-2013'
  - '@type': Occupation
     - 'Ph.D. Student and Teaching Assistant: Organismal Diversity, Aquatic Field Ecology,
     additionalType: self-claimed professional experience
      and General Microbiology, University Program in Ecology, Duke University, 2006-2012'
    name: 'Postdoctoral Associate, Duke University. Mentor: J. B. Heffernan, 2012-2013'
     - Research Technician, Stanford University & Carnegie Institution of Washington,
  - '@type': Occupation
     additionalType: self-claimed professional experience
    name: 'Ph.D. Student and Teaching Assistant: Organismal Diversity, Aquatic Field
      Ecology, and General Microbiology, University Program in Ecology, Duke University,
      2006-2012'
  - '@type': Occupation
     additionalType: self-claimed professional experience
    name: Research Technician, Stanford University & Carnegie Institution of Washington,
       2004-2006
       2004-2006
     - 'Undergraduate Teaching Assistant: Programming Paradigms and Discrete Mathematics,
  - '@type': Occupation
     additionalType: self-claimed professional experience
    name: 'Undergraduate Teaching Assistant: Programming Paradigms and Discrete Mathematics,
       Computer Science, Stanford University, 2001-2003'
       Computer Science, Stanford University, 2001-2003'
    education:
  identifier:
    - 'Ph.D. Ecology, 2012. Duke University, Durham, NC. '
  - '@type': PropertyValue
     - 'Connectivity Drives Function: Carbon and Nitrogen Dynamics in a Floodplain-Aquifer
     propertyID: GeoKB
      Ecosystem. Advisors: E. S. Bernhardt and R. B. Jackson'
    value: https://geokb.wikibase.cloud/entity/Q44528
     - 'B.S. Symbolic Systems, 2004. Stanford University, Stanford, CA. '
  - '@type': PropertyValue
     - Coursework in computer science, decision analysis, logic, linguistics, and psychology.
    propertyID: ORCID
     affiliations: []
     value: 0000-0003-3638-8572
     honors: []
  jobTitle: Data Scientist
     abstracts: []
  knowsAbout:
     personal_statement: "Current RolesProject Manager: Predictive Understanding of\
  - '@type': Thing
      \ Multiscale Processes (PUMP)Task Lead: Advancing Machine Learning and Data\
     additionalType: self-claimed expertise
      \ Assimilation, within the PUMP ProjectAlison studies the movement of energy,\
    name: Data science
      \ carbon, and nutrients through rivers, lakes, and floodplains to better predict\
  - '@type': Thing
      \ and understand variations in water quality over space and time.As a machine\
     additionalType: self-claimed expertise
      \ learning modeler and biogeochemist, she seeks modeling advances that bring\
     name: Ecology
      \ together scientific knowledge and data-driven models. \u201CProcess-guided\
  - '@type': Thing
      \ deep learning\u201D and \u201Cdifferentiable hydrology\u201D are two approaches\
     additionalType: self-claimed expertise
      \ on which she collaborates.As a data scientist, she conducts analyses in ways\
     name: Biogeochemistry
      \ that are reproducible, efficient, and transparent, and she has developed tools\
  - '@type': Thing
      \ and workflows to support others in these goals.In her leadership roles, she\
    additionalType: self-claimed expertise
       \ facilitates fluid skill sharing within teams and communities of practice,\
    name: Rivers and streams
       \ challenges individuals to excel in their projects and careers, and coordinates\
  - '@type': Thing
      \ across projects to realize the Water Mission Area\u2019s vision of broadly\
    additionalType: self-claimed expertise
      \ reusable, integrated tools for predicting water quantity and quality across\
    name: Machine learning
      \ the nation.Alison is based in State College, PA, and is a member of the Analysis\
  - '@type': Thing
      \ and Prediction Branch in the Integrated Modeling and Prediction Division in\
    additionalType: self-claimed expertise
      \ the Water Mission Area. She is on the USGS career track called Equipment Development\
    name: Modeling
      \ Grade Evaluation (EDGE)."
  memberOf:
    '@type': OrganizationalRole
    member:
       '@type': Organization
       name: U.S. Geological Survey
    name: staff member
    startDate: '2024-05-12T15:43:21.895471'
  name: Alison Appling, PhD
  url: https://www.usgs.gov/staff-profiles/alison-appling
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