Summary
Zexun Chen is a Lecturer in Predictive Analytics with nine years of experience developing probabilistic machine learning methods that bridge rigorous theory and real-world applications in fairness, prediction, and human behaviour. His PhD work on Gaussian processes underpins research spanning Bayesian nonparametrics, ethical AI for credit scoring, time series forecasting and financial risk, and complex network analysis of human mobility—insights that inform urban planning and public health. At the University of Edinburgh he leads projects on interpretable, scalable models for financial time series and teaches postgraduate modules in statistics and network analytics. He has secured competitive research funding, produced open-source tools used by peers, and previously embedded fairness constraints into Gaussian process classifiers as part of an EPSRC EthicalML project. Colleagues value his ability to translate mathematical models into practical, interpretable solutions and his openness to interdisciplinary collaborations.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science (BSc), Applied Mathematics, GPA: 87.35/100, Bachelor of Science (BSc), Applied Mathematics, GPA: 87.35/100 at Shandong University
Doctor of Philosophy (Ph.D.), Gaussian process for machine learning, Doctor of Philosophy (Ph.D.), Gaussian process for machine learning at University of Leicester
chinese,mandarin, English, shanghaiese