Daniel Newman is an Advanced Technologist at Boeing with a decade of experience building embedded Linux and IoT solutions for aviation health monitoring. He combines hands-on embedded C and Python development with statistical and machine learning deployment (Scikit-Learn, TensorFlow) to detect unhealthy signals in near real time and enable proactive maintenance. A Georgia Tech PhD graduate and former research assistant, he has a strong foundation in high-frequency vibration acquisition, MQTT-based IoT architectures, and system dynamics control validated through experimental work and publications. Daniel’s background ranges from mechanical design and FEA to data engineering and edge ML, giving him a rare ability to bridge hardware, software, and analytics for safety-critical aerospace systems.
10 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Mechanical Engineering, 4.0, Doctor of Philosophy - PhD, Mechanical Engineering, 4.0 at Georgia Institute of Technology
GPA: 4.0, GPA: 4.0 at Lafayette High School
Master’s Degree, Mechanical Engineering, 3.5, Master’s Degree, Mechanical Engineering, 3.5 at University of Louisiana at Lafayette
Contributions:10 PRs, 16 pushes, 2 branches in 3 years 5 months
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