Nicholas Pritchard
Applied Scientist (Machine Learning) at Cohesion Technologies
Perth, Western Australia
Summary
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Senior🎓
Top SchoolNicholas Pritchard is an applied scientist specializing in neuromorphic computing and energy-efficient machine learning, currently pursuing a PhD at The University of Western Australia while working in industry roles including Applied Scientist and co-founder. He builds large, lightweight spiking neural networks for real-world problems like radio-frequency interference detection in radio astronomy, achieving state-of-the-art accuracy with far lower computational cost. With eight years’ experience spanning software engineering, high-performance computing, computer vision and workflow systems for the Square Kilometre Array, he moves rapidly from research ideas to production-ready systems. Nicholas combines rigorous academic training in AI and physics with practical product instincts from startup and collaborative international projects, and often explores intersections between data-centric methods and hardware-aware model design. An intriguing thread through his work is applying neuromorphic principles to scale ML for constrained environments—delivering tangible performance and energy wins that traditional architectures struggle to match.
8 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at The University of Western AustraliaStudy Abroad, Study Abroad at University of Illinois Urbana-Champaign
Stackoverflow
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Github Skills (48)
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Programming languages (6)
Github contributions (5)
pritchardn/SNN-RFI-SUPER
Jan 2024 - Mar 2025
Supervised SNN for RFI detection
Contributions:3 releases, 18 PRs, 148 pushes in 1 year 2 months
pritchardn/dietProgramming
Dec 2018 - May 2023
Contributions:30 pushes, 2 branches in 4 years 5 months
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