Item talk:Q50426
From geokb
{
"USGS Staff Profile": {
"@context": "https://schema.org",
"@type": "Person",
"dateModified": "2024-09-21T07:59:27.762933",
"name": "Jacob Zwart",
"identifier": [
{
"@type": "PropertyValue",
"propertyID": "ORCID",
"value": "0000-0002-3870-405X"
}
],
"jobTitle": "Data Scientist",
"hasOccupation": [
{
"@type": "OrganizationalRole",
"startDate": "2024-09-21T07:59:27.771328",
"affiliatedOrganization": {
"@type": "Organization",
"name": "Water Resources Mission Area",
"url": "https://www.usgs.gov/mission-areas/water-resources"
},
"roleName": "Data Scientist"
},
{
"@type": "Occupation",
"additionalType": "self-claimed professional experience",
"name": "2021 \u2013 present: Data Scientist, Integrated Information Dissemination Division"
},
{
"@type": "Occupation",
"additionalType": "self-claimed professional experience",
"name": "2019 \u2013 2021: Mendenhall Postdoctoral Fellow, Integrated Information Dissemination Division"
},
{
"@type": "Occupation",
"additionalType": "self-claimed professional experience",
"name": "2017 \u2013 2019: National Science Foundation Earth Sciences Postdoctoral Fellow, Integrated Information Dissemination Division"
},
{
"@type": "Occupation",
"additionalType": "self-claimed professional experience",
"name": "2014 \u2013 2017: National Science Foundation Graduate Research Fellow, University of Notre Dame"
},
{
"@type": "Occupation",
"additionalType": "self-claimed professional experience",
"name": "2012 \u2013 2014: Research and Teaching Assistant, University of Notre Dame"
}
],
"description": [
{
"@type": "TextObject",
"additionalType": "short description",
"abstract": "Data Scientist with the Water Resources Mission Area"
},
{
"@type": "TextObject",
"additionalType": "staff profile page introductory statement",
"abstract": "Dr. Jacob Zwart (he/him) is a data scientist for the USGS Water Resources Mission Area."
},
{
"@type": "TextObject",
"additionalType": "personal statement",
"abstract": "Jacob Zwart works within the Data Science Branch of the Water Resources Mission Area to develop aquatic ecosystem modeling techniques that provide timely information to stakeholders about important water resources across the nation. He uses his expertise in computational modeling, data assimilation, and limnology to help produce short-term forecasts of water quality at regional scales to aid in water resources decision making. Jacob\u2019s research themes are: 1) improve understanding of aquatic biogeochemical processes and predicting how these processes may respond to future global change, 2) develop techniques to inject scientific knowledge into machine learning models to make accurate predictions of environmental variables (also known as \u201cknowledge-guided machine learning\u201d), and 3) advance methods for assimilating real-time observations into knowledge-guided machine learning models to improve near-term forecasts of water quality. Jacob also serves as a Peer Support Worker at USGS promoting awareness and education on topics and USGS policies for antiharassment, discrimination, biases, and scientific integrity, as well as providing peer-to-peer support for USGS employees."
}
],
"email": "jzwart@usgs.gov",
"url": "https://www.usgs.gov/staff-profiles/jacob-zwart",
"affiliation": [],
"hasCredential": [
{
"@type": "EducationalOccupationalCredential",
"name": "Ph.D., Biological Sciences, University of Notre Dame, 2017"
},
{
"@type": "EducationalOccupationalCredential",
"name": "B.S., Biology, Calvin College, 2012"
}
],
"knowsAbout": [
{
"@type": "Thing",
"additionalType": "self-claimed expertise",
"name": "Ecological Forecasting"
},
{
"@type": "Thing",
"additionalType": "self-claimed expertise",
"name": "Limnology"
},
{
"@type": "Thing",
"additionalType": "self-claimed expertise",
"name": "Aquatic Ecosystems"
},
{
"@type": "Thing",
"additionalType": "self-claimed expertise",
"name": "Aquatic Biogeochemistry"
},
{
"@type": "Thing",
"additionalType": "self-claimed expertise",
"name": "Data Assimilation"
}
],
"memberOf": {
"@type": "OrganizationalRole",
"name": "staff member",
"member": {
"@type": "Organization",
"name": "U.S. Geological Survey"
},
"startDate": "2024-09-21T07:59:27.762942"
},
"award": [
"U.S. Geological Survey Mendenhall Postdoctoral Fellowship, 2019 \u2013 2021",
"National Science Foundation Earth Sciences Postdoctoral Fellowship, 2017 \u2013 2019",
"National Science Foundation Graduate Research Fellowship, 2014 \u2013 2017",
"University of Notre Dame Linked Experimental Ecosystem Facility Research Grant, 2017",
"Exceptional Promise in Graduate Research Award, Ecological Society of America Aquatic Ecology Section, 2015",
"University of Notre Dame Center for Aquatic Conservation Graduate Fellow, 2014",
"University of Notre Dame Environmental Research Center Graduate Research Fellowship, 2013 \u2013 2015",
"University of Notre Dame Environmental Research Center Graduate Mentoring Fellowship, 2012"
]
},
"ORCID": {
"@context": "http://schema.org",
"@id": "https://orcid.org/0000-0002-3870-405X",
"@reverse": {
"creator": [
{
"@type": "CreativeWork",
"name": "Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles"
},
{
"@type": "CreativeWork",
"name": "Physics-guided meta transfer learning for predicting temperature of unmonitored lake systems"
},
{
"@type": "CreativeWork",
"name": "Predicting cyanobacterial blooms in freshwater lakes: The promise of new partners, tools and technologies"
},
{
"@type": "CreativeWork",
"name": "Cross-scale interactions dictate regional lake carbon flux and productivity response to future climate"
},
{
"@type": "CreativeWork",
"name": "Global patterns and drivers of ecosystem functioning in rivers and riparian zones"
},
{
"@type": "CreativeWork",
"name": "Improving estimates and forecasts of lake carbon dynamics using data assimilation"
},
{
"@type": "CreativeWork",
"name": "Package \u2018rLakeAnalyzer\u2019"
},
{
"@type": "CreativeWork",
"name": "Physics Guided Machine Learning: A New Paradigm for Modeling Dynamic Systems"
},
{
"@type": "CreativeWork",
"name": "Physics guided RNNs for modeling dynamical systems: A case study in simulating lake temperature profiles"
},
{
"@type": "CreativeWork",
"name": "Process-guided deep learning predictions of lake water temperature"
},
{
"@type": "CreativeWork",
"name": "A framework for understanding variation in pelagic gross primary production of lake ecosystems"
},
{
"@type": "CreativeWork",
"name": "Bias correction or risk estimates in vaccine safety studies with rare adverse events using a self-controlled case series design"
},
{
"@type": "CreativeWork",
"name": "Experimental whole-lake dissolved organic carbon increase alters fish diet and density but not growth or productivity"
},
{
"@type": "CreativeWork",
"name": "Hydrologic setting constrains lake heterotrophy and terrestrial carbon fate"
},
{
"@type": "CreativeWork",
"name": "Integrated, regional-scale hydrologic modeling of inland lakes"
},
{
"@type": "CreativeWork",
"name": "Model-data fusion to test hypothesized drivers of lake carbon cycling reveals importance of physical controls"
},
{
"@type": "CreativeWork",
"name": "Process-Guided Data-Driven modeling of water temperature: Anchoring predictions with thermodynamic constraints in the Big Data era"
},
{
"@type": "CreativeWork",
"name": "Spatially explicit, regional-scale simulation of lake carbon fluxes"
},
{
"@type": "CreativeWork",
"name": "Toward real-time water quality forecasts"
},
{
"@type": "CreativeWork",
"name": "Towards real-time water quality forecasts for streams of the United States"
},
{
"@type": "CreativeWork",
"name": "rLakeAnalyzer: Lake Physics Tools. R package version 1.11. 4"
},
{
"@type": "CreativeWork",
"name": "Delving deeper: Metabolic processes in the metalimnion of stratified lakes"
},
{
"@type": "CreativeWork",
"name": "Hydrologic Regulation of Lake Carbon Cycling in Both Time and Space"
},
{
"@type": "CreativeWork",
"name": "Hydrologic setting constrains lake heterotrophy and terrestrial carbon fate: Hydrologic setting constrains lake heterotrophy"
},
{
"@type": "CreativeWork",
"name": "Hydrology or biology? Modeling simplistic physical constraints on lake carbon biogeochemistry to identify when and where biology is likely to matter"
},
{
"@type": "CreativeWork",
"name": "Improving Estimates and Forecasts of Lake Carbon Pools and Fluxes Using Data Assimilation"
},
{
"@type": "CreativeWork",
"name": "Innovations and Solutions for ASLO Student Travel Grants"
},
{
"@type": "CreativeWork",
"name": "Landscape patterns shape wetland pond ecosystem function from glacial headwaters to ocean"
},
{
"@type": "CreativeWork",
"name": "Light climate and dissolved organic carbon concentration influence species-specific changes in fish zooplanktivory"
},
{
"@type": "CreativeWork",
"name": "SPATIALLY-EXPLICIT SCALING OF REGIONAL LAKE CARBON FLUXES"
},
{
"@type": "CreativeWork",
"name": "The influence of hydrologic residence time on lake carbon cycling dynamics following extreme precipitation events"
},
{
"@type": "CreativeWork",
"name": "rLakeAnalyzer: Lake physics tools"
},
{
"@type": "CreativeWork",
"name": "Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes"
},
{
"@type": "CreativeWork",
"name": "Consequences of gas flux model choice on the interpretation of metabolic balance across 15 lakes, Inland Waters, 6, 581--592"
},
{
"@type": "CreativeWork",
"name": "Experimental whole-lake increase of dissolved organic carbon concentration produces unexpected increase in crustacean zooplankton density"
},
{
"@type": "CreativeWork",
"name": "LakeMetabolizer: an R package for estimating lake metabolism from free-water oxygen using diverse statistical models"
},
{
"@type": "CreativeWork",
"name": "Metabolic and physiochemical responses to a whole-lake experimental increase in dissolved organic carbon in a north-temperate lake"
},
{
"@type": "CreativeWork",
"name": "k. read: Returns a timeseries of gas exchange velocity"
},
{
"@type": "CreativeWork",
"name": "Integrated Surface Water/Groundwater Modeling in the Northern Midwest"
},
{
"@type": "CreativeWork",
"name": "Phytoplankton traits predict ecosystem function in a global set of lakes"
},
{
"@type": "CreativeWork",
"name": "The importance of lake-specific characteristics for water quality across the continental United States"
},
{
"@type": "CreativeWork",
"name": "rLakeAnalyzer: Package for the analysis of lake physics"
},
{
"@type": "CreativeWork",
"name": "2007 Environmental Protection Agency (EPA) National Lakes Assessment dataset plus deriveddata and additional spatially explicit ancillary environmental data."
},
{
"@type": "CreativeWork",
"name": "LakeMetabolizer: tools for the analysis of ecosystem metabolism"
},
{
"@type": "CreativeWork",
"name": "rLakeAnalyzer: Package for the analysis of lake physics. R package version 1.4"
},
{
"@type": "CreativeWork",
"name": "Quantifying terrestrial carbon sources of a small northern seepage lake"
}
]
},
"@type": "Person",
"address": {
"@type": "PostalAddress",
"addressCountry": "US"
},
"affiliation": [
{
"@type": "Organization",
"identifier": {
"@type": "PropertyValue",
"propertyID": "RINGGOLD",
"value": "2928"
},
"name": "US Geological Survey"
},
{
"@id": "https://doi.org/10.13039/100000001",
"@type": "Organization",
"alternateName": "Hosted by USGS ",
"name": "National Science Foundation"
},
{
"@type": "Organization",
"alternateName": "Biology",
"identifier": {
"@type": "PropertyValue",
"propertyID": "RINGGOLD",
"value": "6111"
},
"name": "University of Notre Dame"
}
],
"alternateName": "Jake Zwart",
"alumniOf": [
{
"@type": "Organization",
"alternateName": "Biology",
"identifier": {
"@type": "PropertyValue",
"propertyID": "RINGGOLD",
"value": "6111"
},
"name": "University of Notre Dame"
},
{
"@id": "grid.253573.5",
"@type": "Organization",
"alternateName": "Biology",
"name": "Calvin College"
}
],
"familyName": "Zwart",
"givenName": "Jacob",
"mainEntityOfPage": "https://orcid.org/0000-0002-3870-405X"
},
"OpenAlex": {
"created_date": "2023-07-21",
"display_name": "Jacob A. Zwart",
"display_name_alternatives": [
"Jacob Zwart",
"Jacob A. Zwart",
"J. Zwart",
"J. A. Zwart",
"Jacob Aaron Zwart",
"Jake Zwart"
],
"ids": {
"openalex": "https://openalex.org/A5005617262",
"orcid": "https://orcid.org/0000-0002-3870-405X"
},
"last_known_institutions": [
{
"country_code": "US",
"display_name": "United States Geological Survey",
"id": "https://openalex.org/I1286329397",
"lineage": [
"https://openalex.org/I1286329397",
"https://openalex.org/I1335927249"
],
"ror": "https://ror.org/035a68863",
"type": "government"
}
],
"orcid": "https://orcid.org/0000-0002-3870-405X",
"topics": [
{
"count": 26,
"display_name": "Hydrological Modeling using Machine Learning Methods",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T11490",
"subfield": {
"display_name": "Environmental Engineering",
"id": "https://openalex.org/subfields/2305"
}
},
{
"count": 25,
"display_name": "Hydrological Modeling and Water Resource Management",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T10330",
"subfield": {
"display_name": "Water Science and Technology",
"id": "https://openalex.org/subfields/2312"
}
},
{
"count": 25,
"display_name": "Marine Biogeochemistry and Ecosystem Dynamics",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Earth and Planetary Sciences",
"id": "https://openalex.org/fields/19"
},
"id": "https://openalex.org/T10032",
"subfield": {
"display_name": "Oceanography",
"id": "https://openalex.org/subfields/1910"
}
},
{
"count": 23,
"display_name": "Importance and Conservation of Freshwater Biodiversity",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T10302",
"subfield": {
"display_name": "Nature and Landscape Conservation",
"id": "https://openalex.org/subfields/2309"
}
},
{
"count": 18,
"display_name": "Eutrophication and Harmful Algal Blooms",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T10236",
"subfield": {
"display_name": "Environmental Chemistry",
"id": "https://openalex.org/subfields/2304"
}
},
{
"count": 10,
"display_name": "Biogeochemical Cycling of Nutrients in Aquatic Ecosystems",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T11311",
"subfield": {
"display_name": "Environmental Chemistry",
"id": "https://openalex.org/subfields/2304"
}
},
{
"count": 8,
"display_name": "Physics-Informed Neural Networks for Scientific Computing",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Physics and Astronomy",
"id": "https://openalex.org/fields/31"
},
"id": "https://openalex.org/T11206",
"subfield": {
"display_name": "Statistical and Nonlinear Physics",
"id": "https://openalex.org/subfields/3109"
}
},
{
"count": 7,
"display_name": "Global Flood Risk Assessment and Management",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T10930",
"subfield": {
"display_name": "Global and Planetary Change",
"id": "https://openalex.org/subfields/2306"
}
},
{
"count": 5,
"display_name": "Assessment of Surface Water Quality",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T11634",
"subfield": {
"display_name": "Water Science and Technology",
"id": "https://openalex.org/subfields/2312"
}
},
{
"count": 5,
"display_name": "Management and Reproducibility of Scientific Workflows",
"domain": {
"display_name": "Social Sciences",
"id": "https://openalex.org/domains/2"
},
"field": {
"display_name": "Decision Sciences",
"id": "https://openalex.org/fields/18"
},
"id": "https://openalex.org/T11986",
"subfield": {
"display_name": "Information Systems and Management",
"id": "https://openalex.org/subfields/1802"
}
},
{
"count": 4,
"display_name": "Data Sharing and Stewardship in Science",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Computer Science",
"id": "https://openalex.org/fields/17"
},
"id": "https://openalex.org/T11937",
"subfield": {
"display_name": "Information Systems",
"id": "https://openalex.org/subfields/1710"
}
},
{
"count": 4,
"display_name": "Real-time Water Quality Monitoring and Aquaculture Management",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T12697",
"subfield": {
"display_name": "Water Science and Technology",
"id": "https://openalex.org/subfields/2312"
}
},
{
"count": 4,
"display_name": "Neural Network Fundamentals and Applications",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Computer Science",
"id": "https://openalex.org/fields/17"
},
"id": "https://openalex.org/T10320",
"subfield": {
"display_name": "Artificial Intelligence",
"id": "https://openalex.org/subfields/1702"
}
},
{
"count": 4,
"display_name": "Groundwater Flow and Transport Modeling",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T10894",
"subfield": {
"display_name": "Environmental Engineering",
"id": "https://openalex.org/subfields/2305"
}
},
{
"count": 4,
"display_name": "Global Methane Emissions and Impacts",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T11588",
"subfield": {
"display_name": "Global and Planetary Change",
"id": "https://openalex.org/subfields/2306"
}
},
{
"count": 3,
"display_name": "Numerical Weather Prediction Models",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Earth and Planetary Sciences",
"id": "https://openalex.org/fields/19"
},
"id": "https://openalex.org/T10466",
"subfield": {
"display_name": "Atmospheric Science",
"id": "https://openalex.org/subfields/1902"
}
},
{
"count": 3,
"display_name": "Statistical Computing and Data Analysis in R",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Computer Science",
"id": "https://openalex.org/fields/17"
},
"id": "https://openalex.org/T13398",
"subfield": {
"display_name": "Artificial Intelligence",
"id": "https://openalex.org/subfields/1702"
}
},
{
"count": 3,
"display_name": "Scientific Computing and Data Analysis with Python",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Computer Science",
"id": "https://openalex.org/fields/17"
},
"id": "https://openalex.org/T13650",
"subfield": {
"display_name": "Artificial Intelligence",
"id": "https://openalex.org/subfields/1702"
}
},
{
"count": 2,
"display_name": "Coastal Hydrophysical Processes in Shallow Water Basins",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Earth and Planetary Sciences",
"id": "https://openalex.org/fields/19"
},
"id": "https://openalex.org/T13785",
"subfield": {
"display_name": "Earth-Surface Processes",
"id": "https://openalex.org/subfields/1904"
}
},
{
"count": 2,
"display_name": "Hydrologic Data Management and Analysis",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Earth and Planetary Sciences",
"id": "https://openalex.org/fields/19"
},
"id": "https://openalex.org/T14427",
"subfield": {
"display_name": "Geology",
"id": "https://openalex.org/subfields/1907"
}
},
{
"count": 2,
"display_name": "Arctic Sea Ice Variability and Decline",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Earth and Planetary Sciences",
"id": "https://openalex.org/fields/19"
},
"id": "https://openalex.org/T11459",
"subfield": {
"display_name": "Atmospheric Science",
"id": "https://openalex.org/subfields/1902"
}
},
{
"count": 2,
"display_name": "On-line Monitoring of Wastewater Quality",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Environmental Science",
"id": "https://openalex.org/fields/23"
},
"id": "https://openalex.org/T14249",
"subfield": {
"display_name": "Industrial and Manufacturing Engineering",
"id": "https://openalex.org/subfields/2311"
}
},
{
"count": 2,
"display_name": "Adaptation to Concept Drift in Data Streams",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Computer Science",
"id": "https://openalex.org/fields/17"
},
"id": "https://openalex.org/T12761",
"subfield": {
"display_name": "Artificial Intelligence",
"id": "https://openalex.org/subfields/1702"
}
},
{
"count": 2,
"display_name": "Stable Isotope Analysis of Groundwater and Precipitation",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Earth and Planetary Sciences",
"id": "https://openalex.org/fields/19"
},
"id": "https://openalex.org/T10398",
"subfield": {
"display_name": "Geochemistry and Petrology",
"id": "https://openalex.org/subfields/1906"
}
},
{
"count": 2,
"display_name": "Advanced Techniques in Reservoir Management",
"domain": {
"display_name": "Physical Sciences",
"id": "https://openalex.org/domains/3"
},
"field": {
"display_name": "Engineering",
"id": "https://openalex.org/fields/22"
},
"id": "https://openalex.org/T11801",
"subfield": {
"display_name": "Ocean Engineering",
"id": "https://openalex.org/subfields/2212"
}
}
],
"updated_date": "2024-05-16T15:10:59.060416"
}
}
