I'm Isaac — I build and ship geospatial AI from research through production. Currently Director of AI/ML Research at Taylor Geospatial, where I'm leading the team and building the models behind our earth observation research and creating open data products to elevate the geospatial market and community as a whole. Previously I built and shipped the RasterFlow platform at Wherobots for global-scale geospatial inference, and served as PI on the IARPA SMART program at BlackSky.I maintain widely-used open-source projects — TorchGeo, SMP, and FTW — and publish country-scale and global-scale prediction maps as open data. I write a weekly blog with Caleb Robinson at geospatialml.com covering ML experiments for geospatial applications. Ph.D. in Electrical Engineering from UTSA.
News
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Projects
Selected Publications
CVPR Image Matching Workshop 2026
Are Pretrained Image Matchers Good Enough for SAR–Optical Satellite Registration?
Isaac Corley, Alex Stoken, Gabriele Berton
CVPR 2026
PRUE: A Practical Recipe for Field Boundary Segmentation at Scale
G. Muhawenayo, Caleb Robinson, S. Khanal, Z. Fang, Isaac Corley, A. Wollam, et al.
ICCV VISION 2025
InspectVLM: Unified in Theory, Unreliable in Practice
Conor Wallace, Isaac Corley, Jonathan Lwowski
CVPR PBVS 2025
Aerial Infrared Health Monitoring of Solar Photovoltaic Farms at Scale
Isaac Corley, Conor Wallace, Sourav Agrawal, Burton Putrah, Jonathan Lwowski
IROS 2024
🏆 Best Application Paper Runner-Up
Barely-Visible Surface Crack Detection for Wind Turbine Sustainability
Sourav Agrawal, Isaac Corley, Conor Wallace, Clovis Vaughn, Jonathan Lwowski
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Talks & Podcasts
Apr 2026
UT Austin
Cloud Native GeoAI
Guest lecture at UT Austin on Cloud Native GeoAI, with slides and recording linked below.
Watch recordingApr 2026
Clark University
Geospatial AI and Deep Learning with PyTorch
Guest lecture for Lyndon Estes' class at Clark University, with slides linked below.
Oct 2025
Spatial Stack Podcast
Beyond the Hype: Embeddings, Foundation Models, and the Future of Earth Observation
Joined Matt Forrest's Spatial Stack podcast with Chris Ren to discuss the current state of Geospatial Foundation Models and Embeddings.
Aug 2025
Satellite-Image-Deep-Learning Podcast
Chained Models for High-Res Aerial Solar Fault Detection
Joined Robin Cole's Satellite-Image-Deep-Learning podcast to discuss our CVPR PBVS paper: Aerial Infrared Health Monitoring of Solar Photovoltaic Farms at Scale.
Education
University of Texas at San Antonio
Ph.D. in Electrical Engineering
Advisor: Paul Rad
University of Texas at San Antonio
M.S. in Electrical Engineering
Advisor: Yufei Huang
Texas A&M University - Kingsville
B.S. in Electrical Engineering, Minor in Mathematics
Experience
Director of AI/ML Research — Taylor Geospatial
Building the AI/ML research team and shipping geospatial foundation models and earth observation pipelines from prototype through production.
Senior Machine Learning Engineer — Wherobots
Built and scaled geospatial vision models powering the Wherobots spatial analytics platform. Shipped country-scale field boundary predictions and open-sourced prediction maps for 5 countries.
Senior Machine Learning Scientist — Zeitview (formerly DroneBase)
Research, develop, train, and deployed computer vision, vision-language models (VLM), and 3D Reconstruction methods at scale for enhancing renewable energy inspections and analytics, including solar farms, wind turbines, commercial and residential rooftops, transmission and distribution stations, and telecom towers.
Ph.D. Research Intern — Microsoft Research
Advisor: Simone Fobi Nsutezo & Anthony Ortiz
Researched multimodal pretraining methods for large-scale geospatial vision-language datasets.
Senior Machine Learning Engineer — Spruce
Applied state-of-the-art Optical Character Recognition (OCR) and Text Summarization methods to parse real estate and financial documents.
Senior Machine Learning Engineer — BlackSky
Served as PI on the IARPA SMART program. Built and deployed models powering the Spectra AI platform's satellite image analytics.
Senior Data Scientist — HouseCanary
Developed and deployed computer vision models for extracting insights and features from real estate property images for improving HouseCanary's Automated Valuation Model (AVM) and property recommender system utilized by real estate investors.
Senior Data Scientist — Booz Allen Hamilton
Researched and developed prototypes for deep learning-based image steganography detection and removal as well as adversarial domain generation detection.
Research Engineer — Southwest Research Institute (SwRI)
Advisor: Kenneth Holladay
Developed and deployed software updates to the A-10 Warthog aircraft as well as researched machine learning methods for detecting engine stalls and exploiting the MIL-STD-1553 communications bus.
Research Intern — Oak Ridge National Laboratory (ORNL)
Advisor: Paul Ewing
Recorded and annotated a dataset of seismic signals of human and vehicle activity and trained machine learning methods to detect this activity.