Jay Laura
Principal at U.S. Geological Survey (USGS)
Flagstaff, Arizona, United States
Summary
🤩
Rockstar🎓
Top SchoolJay Laura is a principal research scientist and software lead at USGS Astrogeology with 13 years of experience building scalable geospatial analytics, computer vision, and planetary photogrammetry systems. She directs advanced research computing operations—including three deployed supercomputers—and manages software development for a community of over 1,100 scientists, blending on-premises and AWS pipelines. Jay has published over one million remotely sensed observations using the STAC metadata spec and contributes to foundational open-source spatial tools like PySAL, where her backend work advanced spatial statistics and graph algorithms. Trained to the PhD level and active as a lecturer, she combines rigorous academic methods with production engineering in GIS, CUDA, and C/C++ workloads. Known for automating complex geospatial processing and DEM generation, she brings a rare mix of planetary science domain expertise and large-scale systems leadership.
13 years of coding experience
Doctor of Philosophy (PhD), Doctor of Philosophy (PhD) at Arizona State UniversityMaster's of GIS, Master's of GIS at Penn State UniversityBloomfield High SchoolBachelor of Arts, Bachelor of Arts at Montclair State University
English, German
Stackoverflow
3,934reputation
836kreached
8answers
87questions
Github Skills (18)
python10
spatial-data-analysis10
data-structure9
distance-matrix9
open-source9
metric9
collaborative-editing9
collaboration9
data-structures9
statistics8
multiprocessing6
pysal6
shapefile6
gdal6
numpy6
Programming languages (17)
Github contributions (5)
pysal/pysal
Apr 2013 - Apr 2016
PySAL: Python Spatial Analysis Library Meta-Package
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:233 commits, 57 PRs, 28 pushes in 3 years 1 month
Contributions summary:Jay's commits primarily involve code modifications within the `pysal/pysal` repository, specifically focusing on spatial analysis and the implementation of functions and data structures for this domain. The commits detail significant modifications to functions related to weighted edge data structures (WED) and functionalities like shortest path analysis using Dijkstra's algorithm, and the integration of a new binary file reader/writer, indicating a focus on core backend and data processing aspects. The changes further involve work related to spatial autocorrelation using Moran's I and the development of a more general point-to-point distance framework, showcasing expertise in spatial statistics and data analysis tasks.
meta-packagepythonspatial-analysispysalspatial
USGS-Astrogeology/automated-metadata-generation
Mar 2021 - Feb 2022
A library for automated metadata generation
Contributions:2 releases, 17 reviews, 13 PRs in 11 months
metadata
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