Jeffrey Udall
Electrophysics Engineer at Boeing
Seattle, Washington, United States
Summary
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Senior🎓
Top SchoolJeffrey Udall is an Electrophysics Engineer at Boeing Phantom Works with eight years of experience applying modeling and simulation to defense and special-mission sensor problems. He came to Boeing after designing and testing electro-optical systems at NAWCAD and supporting advanced test equipment at Rohde & Schwarz, blending hands-on electronics troubleshooting with higher-level physics modeling. Jeffrey holds an MEng in Electrical and Electronics Engineering from UMBC and pairs rigorous engineering training with a creative background in digital film and illustration, which helps him communicate complex technical results clearly. Based in Seattle, he focuses on practical, scalable simulation solutions for defense applications and has a track record of improving benchmarking and automation tools from his research internship work.
8 years of coding experience
14 years of employment as a software developer
Electrical Engineering, 4.0, Electrical Engineering, 4.0 at Portland Community CollegeBachelor's degree, Electrical Engineering, 3.36, Bachelor's degree, Electrical Engineering, 3.36 at Portland State UniversityUMBCAssociate of Science - AS, Illustration, 3.53, Associate of Science - AS, Illustration, 3.53 at Salt Lake Community CollegeBachelor, Digital Film Production, 3.25, Bachelor, Digital Film Production, 3.25 at The Art Institutes
Github Skills (11)
von-neumann10
automata9
regular-expression9
benchmark8
high-performance7
architectures6
levenshtein3
pattern3
edit-distance2
automaton2
javascript2
Programming languages (1)
Github contributions (5)
jeffudall/Team14
Oct 2017 - Dec 2017
Contributions:66 commits, 61 pushes, 1 branch in 2 months
jackwadden/ANMLZoo
Aug 2017 - Sep 2017
High-performance automata-processing engines are traditionally evaluated using a limited set of regular expression rulesets. While regular expression rulesets are valid real-world examples of use cases for automata processing, they represent a small proportion of all use cases for automata-based computing. With the recent availability of architectures and software frameworks for automata processing, many new applications have been found to benefit from automata processing. These show a wide variety of characteristics that differ from prior, popular regular-expression benchmarks, and these should be considered when designing new systems for automata processing. This paper presents ANMLZoo, a benchmark repository for automata-based applications as well as automata engines for both von-Neumann and reconfigurable data flow architectures.
Contributions:117 commits, 9 PRs, 4 comments in 29 days
casesvonvon-neumanncharacteristicsproportion
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