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
MPhys, Astronomy, Physics, MPhys, Astronomy, Physics at University of St Andrews
North Berwick High School
University College London