Liam Hiley
Software Engineer at Rowden
Abertillery, Wales, United Kingdom
Summary
👤
Senior🎓
Top SchoolLiam Hiley is a seasoned software engineer with a decade of experience building backend systems, currently focused on Web3 and blockchain-enabled services. He combines a strong Python backend skillset with academic rigor from PhD research in deep learning interpretability and a BSc in Engineering, bridging research and production engineering. Liam has progressed from research roles at Cardiff University to senior engineering positions at SIMBA Chain and now Rowden, delivering distributed analytics and smart-contract backends. An embedded and robotics enthusiast who also dabbles in amateur game development, he brings a practical systems mindset and a knack for translating complex ML and security-driven research into maintainable code. Notably, his background includes applied work on interpretability for activity recognition in adversarial contexts — a perspective that informs robust, explainable system design.
10 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Engineering, Bachelor of Science - BS, Engineering at The Open UniversityBSc, Computer Science with Year in Industry, BSc, Computer Science with Year in Industry at Cardiff University / Prifysgol Caerdydd11 GCSEs at Grade C or higher, 11 GCSEs at Grade C or higher at Abertillery ComprehensiveGCE, N/A, GCE, N/A at Coleg Gwent Crosskeys Campus
Welsh, English
Github Skills (13)
adaptation9
modular5
deep-learning5
machine-learning5
pytorch4
hardware2
stream2
rgb2
computer-vision2
acceleration1
action-recognition1
hardware-acceleration1
autograd1
Programming languages (3)
Github contributions (5)
liamhiley/selective_relevance
Mar 2020 - Jul 2021
Contributions:2 releases, 74 commits, 18 pushes in 1 year 4 months
liamhiley/torchexplain
Jan 2019 - Sep 2021
An adaptation of PyTorch's autograd functionality to LRP based local explanation techniques.
Contributions:35 commits, 18 pushes, 1 branch in 2 years 7 months
pytorchtechniquesdeep-learningexplanationadaptation
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