Summary
Ian Mason is a Principal Researcher in AI based in California with nine years of experience bridging deep learning and biologically inspired intelligence. He develops models and methods aimed at closing the gap between current neural network performance and the adaptive, compositional behaviours observed in biological systems. His trajectory spans a PhD on few-shot learning, a neuroscience-focused postdoc at MIT studying compositionality and distribution shift, and research leadership roles at Fujitsu Research. Ian combines rigorous mathematical training (BSc Mathematics, Imperial College) with hands-on machine learning practice, bringing both theory and applied research to production-facing problems. He is particularly interested in robust generalization across changing domains—a through-line from his thesis to his postdoctoral work and industry projects. Outside standard research outputs, he emphasizes translating neuroscientific insights into practical ML architectures that improve adaptability under distribution shift.
9 years of coding experience
4 years of employment as a software developer
The University of Edinburgh
Postdoctoral Studies, Postdoctoral Studies at Massachusetts Institute of Technology
Bachelor of Science (BSc), Mathematics, 1st, Bachelor of Science (BSc), Mathematics, 1st at Imperial College London
English