Summary
Jenning Lim is a Machine Learning Scientist with nine years of experience bridging rigorous statistical research and applied ML in industry and academia. Currently based in London and completing a PhD in Statistics at the University of Warwick, Jenning focuses on kernel methods, model testing and criticism, and approximate Bayesian inference, bringing strong theoretical depth to practical problems. His background includes applied roles and fellowships at Relation, Amazon, The Alan Turing Institute, and research stints at Max Planck and Kyoto University, reflecting a pattern of translating research into real-world systems. He holds an MSc in Data Science and Machine Learning (Distinction) from UCL and a First Class BSc in Mathematics and Computer Science from Bristol, underscoring a solid quantitative foundation. Notably, Jenning combines classical statistical perspectives with modern ML tooling, making him adept at diagnosing model failure modes and building robust, interpretable solutions.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BSc), Mathematics and Computer Science, First Class, Bachelor of Science (BSc), Mathematics and Computer Science, First Class at University of Bristol
Doctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at University of Warwick
University College London