Dominik Schneider
Meteorological Data Engineer
Moscow, Idaho, United States
Summary
👤
Senior🎓
Top SchoolDominik Schneider is a meteorological data engineer with 11 years of experience applying machine learning, computer vision, and geospatial methods to environmental and water-resource problems. He has managed phenomics and geospatial projects end-to-end—from robotic image acquisition and pipeline development to downstream analytics—and built production-ready tools used in research and operational settings. His work spans academic research (PhD in Geography) and industry data engineering roles, recently contributing backend improvements to the well-known PlantCV image-analysis library. Dominik combines field deployment experience (installing and maintaining hydrologic sensor networks) with software practices like Docker, Make, and pipeline automation, enabling robust, repeatable data products for stakeholders. Based in Moscow, Idaho, he seeks to join teams in the public or private sector focused on using advanced techniques to improve system understanding and decision-making.
11 years of coding experience
15 years of employment as a software developer
BS Civil Engineering, BS Civil Engineering at University of DelawareDoctor of Philosophy (Ph.D.) Geography, Doctor of Philosophy (Ph.D.) Geography at University of Colorado BoulderMS Civil Engineering, MS Civil Engineering at Villanova University
English, German, German, Spanish
Github Skills (6)
image-analysis10
bioinformatics10
opencv10
python10
numpy10
documentation8
Programming languages (19)
Github contributions (5)
danforthcenter/plantcv
Nov 2018 - Aug 2021
Plant phenotyping with image analysis
Role in this project:
Backend Developer
Backend DeveloperContributions:17 reviews, 83 commits, 40 PRs in 2 years 10 months
Contributions summary:Dominik primarily contributed to the `plantcv` repository by modifying and updating existing Python scripts. These changes focused on refining image analysis functions, including color analysis, contour processing, and pseudocoloring. Additionally, the user addressed documentation issues, corrected input parameters, and made improvements to the code's structure and compatibility, demonstrating a focus on improving the library's functionality and usability. Several commits involved modifications to core image processing functions, suggesting an understanding of the underlying algorithms.
plantimage-analysissciencephenotypingbioinformatics
hoargroup/stationsweRegression
May 2017 - Jan 2024
Contributions:46 pushes, 3 branches, 2 comments in 6 years 9 months
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