Evan Funk is a computer vision engineer and Georgia Tech senior dual-majoring in Mathematics and Physics, blending strong theoretical insight with hands-on systems engineering. He builds production CV/ML pipelines—most recently designing a lightweight, AWS Lambda–hosted vision system that maps hand-marked golf strokes to GPS coordinates resilient to real-world noise—and has 11 years of engineering experience across data, backend, and DevOps. In research, he applied computational modeling to ultracold-atom experiments, implemented the lab’s first spatially resolved mean-field BEC simulations, and boosted trap stability by 164% through PID and hardware improvements. Comfortable moving from numerical optimization and time-series trading algorithms to MOSFET-based circuit redesigns, Evan excels at diagnosing cross-domain problems and delivering pragmatic, measurable improvements. He’s also an active open-source contributor focused on backend reliability and deployment, with work that improves logging, error handling, and automated image publishing.
11 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Mathematics, Bachelor of Science - BS, Mathematics at Georgia Institute of Technology
High School Diploma, High School Diploma at Fort Osage High School
Tools for creating images, including the Anaconda boot.iso, live disk images, iso's, and filesystem images.
Role in this project:
Backend & DevOps Engineer
Contributions:8 commits, 6 PRs, 15 comments in 1 month
Contributions summary:Evan primarily focused on improving the error handling and logging within the `lorax` project, particularly concerning Git repository interactions. They enhanced the error messages for failed operations and improved the logging output. Furthermore, they implemented a feature to automatically upload composed images to various cloud providers, demonstrating contributions to the system's deployment and integration aspects. They also updated the API to return the most relevant logs.
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