Cory Glenn Garms
Academic & Professional Record

Cory Glenn Garms, Ph.D.

Senior Scientist • Spectral Sciences, Inc. • Burlington, MA

coryglenngarms@gmail.com • LinkedIn Profile • github.com/cory-garms • Google Scholar

Executive Summary

Remote sensing scientist and software architect with a Ph.D. in Sustainable Forest Management. Experienced in turning complex physical data—from satellite imaging and mobile 3D LiDAR to hyperspectral cubes—into robust, containerized software pipelines.

Proven track record leading federal robotics projects (USDA STTR), building image restoration algorithms for NASA space telescopes, and publishing peer-reviewed research in remote sensing, forestry, and optical calibration.

Professional Experience

Senior Scientist

Spectral Sciences, Inc. • Burlington, MA
2022 – Present
  • CUTMAP Principal Investigator & Lead Algorithm Architect (USDA-NIFA STTR Phase I Awardee, Forests & Related Resources): Directed software and sensor integration for CUTMAP (Comprehensive Utility for Thinning Mechanically via Automated Prescription), an autonomous robotic forest inventory platform developed at Spectral Sciences, Inc. in partnership with Dr. Bogdan Strimbu at the Oregon State University College of Forestry. Developed real-time mobile LiDAR and stereo-vision pipelines to map tree locations, trunk diameter, lean, and timber volume under dense canopy.
  • UNJITR Astrophysics Restoration Engine (NASA Swift UVOT): Co-investigator and algorithm developer (with Dr. Jonathan Gelbord). Designed sub-pixel Fourier cross-correlation algorithms that restored blurred, jitter-corrupted space telescope images across 282 Swift galaxy observations (99.7% recovery rate).
  • Hyperspectral Sensor Calibration & MTF Ground Truth: Designed and deployed ground calibration targets to verify camera sharpness (MTF) and color accuracy for airborne imaging systems during flight.
  • High-Performance Containerized Pipelines: Built reproducible Docker and Podman environments to process large 3D point clouds and hyperspectral datasets efficiently in Python and C++.

UAS Scientist / Full-Stack Web Developer

AeroTract Geospatial • Albany, OR
Sep 2021 – 2022
  • Delivered aerial analytics and maps from drone sensor payloads for agriculture, forestry, and utility clients.
  • Built and deployed an AWS cloud platform (S3, Lambda, EC2) to process and deliver client geospatial data; mentored two junior developers.
  • Created automated Python workflows and statistical tools for geospatial data processing.

UAS Scientist • Interim Aerial Section Chief

CDR Maguire • Salem, OR
Jan 2021 – Aug 2021
  • Established a drone inspection team to monitor hazard tree removal along Oregon highways after the 2020 wildfires.
  • Trained and led 5 commercial drone pilots flying LiDAR and high-resolution cameras.
  • Developed 3D point cloud workflows to inspect steep, inaccessible hazard trees safely from the ground.

Co-Founder

Greensense Remote Sensing • Corvallis, OR
Jan 2018 – Apr 2021
  • Co-founded a drone remote sensing company providing crop health and canopy volume maps to Oregon growers.
  • Flew drone missions covering 1,250+ acres of multispectral and thermal imagery across orchards and specialty crops.
  • Built point cloud processing tools and completed the Oregon State University Advantage Accelerator program (2020).

Education

Oregon State University

Doctor of Sustainable Forest Management (Ph.D.)
Corvallis, OR
2016 – 2020

Focus: Forest remote sensing, 3D LiDAR, and photogrammetry. Researched how tree lean and trunk curvature affect tree measurements and timber volume calculations from laser scans.

Louisiana State University

Master of Science in Renewable Natural Resources (M.S.)
Baton Rouge, LA
2013 – 2016

Focus: Forest biomechanics. Researched in situ static winching, tilt-sensor accelerometry, and stem breaking resistance (MOE/MOR) in southern pine species following hurricane exposure.

University of Texas at San Antonio

Bachelor of Science in Environmental Science & Biology (B.S.)
San Antonio, TX
2008 – 2012

Graduated Cum Laude. Coursework in ecology, botany, statistics, and GIS.

Technical Expertise & Arsenal

Scientific Programming & Math
Python (NumPy, SciPy, Pandas, laspy, rasterio, Open3D), R (biometrics, spatial statistics), C++, GLSL, Bash scripting
Point Clouds & Geospatial
PDAL, CloudCompare, GDAL/OGR, QGIS, Agisoft Metashape, Potree, Three.js, React Three Fiber
Remote Sensing & Sensors
Airborne & Terrestrial LiDAR (Livox, DJI L1, Riegl), Hyperspectral/Multispectral, MTF verification, UAS Operations (Part 107)
Computer Vision & AI
YOLOv8, 3D Point Segmentation, RANSAC Cylinder Fitting, SLAM, PyTorch, Detectron2, OpenCV
Full-Stack & Cloud Architecture
JavaScript/TypeScript (Astro, React, Node.js), AWS (S3, Lambda, EC2), Plotly/Dash, MERN stack
DevOps & Reproducible Science
Docker, Podman, Linux/POSIX environments, Git CI/CD, Automated Testing, Scientific Documentation
Languages: English (Native) • Spanish (Limited working proficiency) • Italian (Elementary)

Select Publications & Proceedings

View Publications
Garms, C.G., Strimbu, B., et al. (2026). Calibrating a Low-SWaP-C Lidar–Stereo Platform: Staged Procedures, Failure Coupling, and Operational Validation. Journal of Field Robotics, in progress / in preparation.
Gelbord, J., Garms, C.G., et al. (2026). UNJITR: Catalog-Free Sub-Pixel Photon Jitter Restoration & Orbit Coregistration for NASA Swift UVOT. Publications of the Astronomical Society of the Pacific (PASP), in preparation.
Strauss, S.H., Garms, A.L., Garms, C.G., et al. (2026). Robust Growth, Leaf Coloration, and Adaptation of a Transgenic Purple-leaved Poplar. HortScience, 61(9), 1925–1934.
Garms, C.G. et al. (2023). Spectral-spatial ground targets for measurement of airborne electro-optical imaging system performance. Proc. SPIE Defense + Commercial Sensing, 1254308.
Moler, E.R.V., Page, G.F.M., Flores-Rentería, L., Garms, C.G., et al. (2021). A method for experimental warming of developing tree seeds with a common garden demonstration of seedling responses. Plant Methods, 17(1), 1–13.
Garms, C.G., Simpson, C., Parrish, C., Wing, M.G., & Strimbu, B.M. (2021). Assessing lean and positional error of individual mature Douglas-fir using active and passive sensors. Remote Sensing, 12(14), 2278.
Garms, C.G., Flores-Rentería, L., Waring, K.M., Whipple, A.V., Wing, M.G., & Strimbu, B.M. (2020). Augmenting Size Models for Pinus strobiformis Seedlings Using Dimensional Estimates from Unmanned Aircraft Systems. Canadian Journal of Forest Research, 50(7), 643–652.
Garms, C.G., & Strimbu, B.M. (2020). Impact of stem lean on estimation of Douglas-fir diameter and volume using mobile lidar scans. Canadian Journal of Forest Research, 50(9), 882–892.
Garms, C.G. (2020). Using Point Clouds for Single Tree Forest Inventory at the Beginning and End of the Rotation. Ph.D. Dissertation, Oregon State University.
Garms, C., & Dean, T.J. (2019). Relative resistance to breaking of Pinus taeda and Pinus palustris. Forestry: An International Journal of Forest Research, 92(4), 417–424.

Leadership & Community Service

Medford Malden Elks Lodge #915

Esteemed Lecturing Knight • Past Chaplain • Member since 2021
Medford, MA

Support charitable fundraisers, youth scholarships, and veterans outreach programs across greater Boston.

Interests & Avocations

Outdoor Field Science & Recreation: Kayaking, fishing, hiking, camping, gardening & botany.
Sports & Quantitative Analytics: Boston Red Sox (creator of Dirty Water MLB analytics suite), San Antonio Spurs, and LSU Tigers football.
Origins: Native of Amarillo, Texas.