Summary
Alex Gibberd is an applied statistician and Assistant Professor specializing in high-dimensional time-series and non-stationary dependence, with a decade of experience bridging methodological development and real-world applications in neuroscience, finance, and anomaly detection. He develops regularized inference tools for describing and forecasting complex multistream systems, and his work spans correlated point-process models through to practical predictive pipelines. Previously a senior lecturer and a research associate at leading UK institutions, Alex also founded a fintech-oriented startup, bringing entrepreneurial pragmatism to academic research. Based in North Norfolk, he combines rigorous PhD training from UCL with interdisciplinary MRes and physics background, enabling a knack for translating abstract statistical theory into actionable insights for large data-stream settings.
10 years of coding experience
7 years of employment as a software developer
North Berwick High School
MPhys, Astronomy, Physics, MPhys, Astronomy, Physics at University of St. Andrews
Doctor of Philosophy (Ph.D.), Statistics, Doctor of Philosophy (Ph.D.), Statistics at University College London, U. of London