Brad Chambers
Director, Technology at St. Peter Area Robotics
St. Peter, Minnesota, United States
Summary
🤩
Rockstar🎓
Top SchoolBrad Chambers is a Director of Technology with 14+ years of deep experience in image and video processing, computer vision, 3D imaging, and lidar collection and exploitation. He leads geospatial software strategy and engineering at GCS Geospatial after producing scalable tooling and integrations at Maxar, including packaging PDAL for conda-forge and advancing GRiD APIs for terrain and point cloud workflows. A hands-on developer in C/C++, Python, and JavaScript, he has made notable open-source contributions to PCL and PDAL—adding filters, downsampling tools, and a Hausdorff-distance utility that improved point-cloud analysis. His background spans field data collection and lab algorithm development, from hyperspectral and lidar phenomenology experiments to production-ready plugins and CI-driven builds. Based in St. Peter, MN, he pairs technical leadership with active community engagement (conference talks and open-source stewardship) and even coaches youth robotics, reflecting a practical commitment to mentoring the next generation.
14 years of coding experience
19 years of employment as a software developer
MS, Electrical and Computer Engineering, MS, Electrical and Computer Engineering at University of Illinois Urbana-ChampaignBS, Electrical Engineering, BS, Electrical Engineering at Oklahoma State University
Github Skills (12)
algorithm10
pcl10
computer-vision10
algorithms10
point-cloud-library10
filtering10
cpp10
point-cloud10
filter10
cplus10
data-structure9
data-structures9
Programming languages (9)
Github contributions (5)
PointCloudLibrary/pcl
Feb 2014 - May 2014
Point Cloud Library (PCL)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:17 commits, 1 PR, 1 comment in 2 months
Contributions summary:Brad made significant contributions to the point cloud library, specifically focusing on the development of filtering algorithms and tools. Their work involved creating a local 2D grid for point cloud downsampling and implementing morphological filters operating on the Z dimension. Furthermore, they added a tool to compute the Hausdorff distance and a tool to generate random point clouds, demonstrating a focus on processing and analyzing point cloud data. The user also made improvements to the existing codebase including an approximate progressive morphological filter.
cpppoint-cloud-libraryc-plus-pluscomputer-visionpcl-library
conda-forge/hexer-feedstock
Apr 2018 - Mar 2021
A conda-smithy repository for hexer.
Contributions:5 PRs, 2 pushes, 3 comments in 2 years 11 months
condasmithy
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