Charlie Pilgrim is a research fellow and PhD researcher based in the UK with 11 years’ experience studying collective intelligence, multi-agent systems, and adaptive decision-making. He blends rigorous quantitative skills from physics and data science with practical full‑stack development experience, enabling him to design experiments, build analysis pipelines, and deploy interactive tools. His work spans academia and applied practice—from founding and scaling businesses to leading behavioural field campaigns—giving him a rare perspective on how group behaviour translates into real-world outcomes. Currently at the University of Leeds he investigates when and how groups outperform individuals, building on projects at UCL and the Alan Turing Institute. Colleagues describe him as a boundary‑spanning researcher who pairs complexity science and information theory with psychological insight to reveal surprising drivers of collective behaviour.
11 years of coding experience
10 years of employment as a software developer
Bachelor of Science (BSc), Physics, 1st Class (Hons), Bachelor of Science (BSc), Physics, 1st Class (Hons) at The University of Manchester
Master of Science (MSc), Sustainable Energy Futures, Merit, Master of Science (MSc), Sustainable Energy Futures, Merit at Imperial College London
piecewise-regression (aka segmented regression) in python. For fitting straight line models to data with one or more breakpoints where the gradient changes.
Contributions:2 releases, 200 commits, 2 PRs in 2 years 4 months
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Charlie Pilgrim - Research Fellow at Chasmani Data