Summary
Paul Childs is a Senior Software Engineer and PhD-trained signal processing researcher with 15 years of industry experience and a 50-paper publication record focused on Fourier and transform-based techniques. He has translated deep academic breakthroughs—such as Fourier-based multiplexing that increased sensor network capacity eightfold and the cladding ring sensor used in refractometry and DNA sensing—into practical products and patents. Paul blends low-level C and assembler expertise with C++, Python, Matlab and systems tooling (GNU autotools, Debian/RPM packaging), often working on high-performance and embedded signal-processing systems like LiDAR classification, acoustic beamforming and optical sensors. His career spans research fellowships and postdocs through senior roles in industry, evidencing comfort across component-level innovation and sensor-network architecture. Based in Newcastle-Maitland, Australia, he pairs mathematical rigor with hands-on engineering, and is notable for shipping both algorithmic inventions and production-grade code in constrained hardware environments.
15 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD), Electrical, Electronics and Communications Engineering, Doctor of Philosophy (PhD), Electrical, Electronics and Communications Engineering at University of New South Wales
High School, High School at Sydney Technical High School
Oatley Public
Grad. Cert., Tertiary Teaching, Grad. Cert., Tertiary Teaching at Curtin University
English, Russian, Chinese, Kazakh, Greek