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Eric Carr

NIMBioS Computational Data Engineer (2008-2021)

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Eric Carr is the Computational Data Engineer for NIMBioS where he helps resident and visiting researchers use computational resources and implement models and analysis. A primary objective is to ensure that all participants have the tools they need to create great science, as well as the necessary training to use them. Working in conjunction with NIMBioS's Education and Outreach team, Carr develops computational resources for local and remote research and training events, including seminars, workshops, and tutorials. Carr developed and now manages the infrastructure for virtual participation.

Carr got his start at DUPONT Medical Imaging providing engineering and field support during the early stages of medical digital imaging. As a graduate student, Carr conducted spatially explicit environmental modeling under the ATLSS Florida Everglades Restoration. The initiative fostered a commitment to interdisciplinary academic approaches and inter-institutional collaboration with USGS, US Fish and Wildlife, NPS, US Army Corps Of Engineers, along with private and corporate partners. Carr's focus on spatial explicit approaches with regard to modeling led to a diverse geographic and spatial concentration including the use of ARCGIS and open source tools. His involvement in a wide ranging set of projects has generated products for both web-based consumptions and high performance computation in languages ranging from R, python, MATLAB, JavaScript, and D3 to Fortran, C, and C++.

Carr has an M.S. in Mathematics from the University of Tennessee, Knoxville, and a B.S. in Mechanical Engineering from Bucknell University, Lewisburg, PA.

Phone: 865-974-0223

1122 Volunteer Blvd., Suite 106
University of Tennessee
Knoxville, TN 37996-3410
PH: (865) 974-9334
FAX: (865) 974-9461
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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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