David Hildebrand
Industrial Engineer at Stellantis
Toledo, Ohio, United States
Summary
👤
Senior🎓
Top SchoolDavid Hildebrand is an industrial engineer with 11+ years of hands-on experience optimizing assembly operations and supervising production teams in UAW environments, currently supporting Stellantis in Toledo. He combines practical supervisory experience—having led a 65-person trim line—with deep process improvement skills across FIAT World Class Manufacturing, MODAPTS-certified standards-setting, and workplace organization. His background spans lean transformations, facility layout and AutoCAD-driven redesigns, and supply-chain/throughput studies that delivered measurable gains (e.g., dramatic lead-time reductions and award-winning implementations). Unusually for an industrial engineer, he has contributed code to an open-source scientific project, integrating a Minolta photometer into PsychoPy to enable display calibration for vision research, demonstrating comfort with hardware interfacing and serial communications. Based in Toledo, he brings a pragmatic blend of shop-floor leadership, continuous improvement rigor, and a knack for bridging physical processes with technical solutions.
11 years of coding experience
19 years of employment as a software developer
Associate MicroComputer Engineering, Associate MicroComputer Engineering at Penn State University
Github Skills (10)
controls10
serial-communication10
python10
interfacing10
psych10
hardware-interface10
experimental-design9
psychopy9
neuroscience8
experiment7
Programming languages (5)
Github contributions (5)
psychopy/psychopy
May 2022 - May 2022
For running psychology and neuroscience experiments
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 commits, 1 PR, 4 comments in 6 days
Contributions summary:David's commits primarily involve the integration of the Minolta CS100A photometer with the PsychoPy library. This includes creating a Python class to interface with the device, implementing methods to control and read data from it, and incorporating it into the existing calibration tools. Their work enables luminance and chromaticity measurements, significantly expanding PsychoPy's capabilities for display calibration and experimental control within the domain of vision science. The user's code demonstrates a solid understanding of serial communication and hardware interfacing.
neurosciencepythonexperiment-controlcognitive-scienceopenscience
davidhildebrand/hildebrand16
May 2016 - Jan 2017
Contributions:95 commits, 2 PRs, 70 pushes in 7 months
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