Joe McGlinchy

Principal Remote Sensing Scientist @AiDASH

Denver, CO, US
EMAILS
j•••@aidash.com
MOBILE NUMBERS
+13•••••••87

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WORK HISTORY

Jan 2025 — Present

Principal Remote Sensing Scientist @AiDASH

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CO, US

Developing production-ready image processing & geospatial workflows with open-source software* Construction of data models to commonly represent data from several commercial high-resolution satellite imagery providers for use in machine learning workflows* improving data sharpening workflows* improving georegistration and automating orthorectification of commercial high-resolution level-1 imagery to sub-meter accuracy through open-source python libraries* use of open-source stereo and tri-stereo image processing frameworks for surface generation

EDUCATION

2003 — 2008

The University of Akron

BSEE, Electrical Engineering

2008 — 2010

Rochester Institute of Technology

Masters of Science, Imaging Science (Remote Sensing)

SKILLS

AlgorithmsGisRemote SensingStatistics3dImage ProcessingSpatial AnalysisAnalysisTeamworkMatlabImage AnalysisResearchResearch and Development (R&D)Data AnalysisSimulationsArcgisDigital Image ProcessingLidarGeographic Information Systems (Gis)PythonEnviComputer VisionEsriProject ManagementGeomaticsImageryPattern Recognition

ABOUT JOE MCGLINCHY

My professional interests relate to utilizing remotely sensed data such as multi- and hyperspectral imagery, lidar, and radar, through data fusion, advanced processing, and exploitation to identify and solve big problems. As Principal Remote Sensing Scientist with AiDASH, I am enjoying the challenge of operationalizing image processing workflows for lower-level commercial satellite imagery to aid in 3D mapping of vegetation for applications in the utility sector.I have over 13 years of experience in the remote sensing and geospatial industries and hold a Masters of Science in Imaging Science from Rochester Institute of Technology and a Bachelors of Science in Electrical Engineering from the University of Akron.Related knowledge and skill sets• Extensive knowledge in remote sensing and imaging science fields• Physics-based retrieval of physical parameters like reflectance and temperature• Experience with atmospheric correction modules, such as (Py)6S• statistical background pertaining to classification techniques and spectral/textural analysis• Hyperspectral and multispectral image analysis, unmixing, matching, and target detection• Lidar and image-derived point cloud processing and filtering• 2D/3D geometric reconstruction from high resolution image collections• Implementation of computer vision algorithms in a geospatial framework• Participation in field data collection campaigns• Experience in cloud computing environments (AWS)

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