Mike Stannett
Senior Lecturer at School of Computer Science, University of Sheffield
Sheffield, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolMike Stannett is a Senior Lecturer in the School of Computer Science at the University of Sheffield with over two decades of academic experience and eleven years in his current focused roles. A theoretical computer scientist and mathematician by training (BA, Oxford; PhD, Sheffield), he specialises in logic and logical approaches to relativity theory while applying formal verification techniques to physical theories using Isabelle/HOL. He has a rare blend of pure-maths pedigree—work on general and analytic topology including Stone-Čech compactification—and practical data-science contributions, such as implementing integral kernels for the widely used GPy Gaussian processes library to handle binned data. Mike has organised numerous international workshops, is active in professional societies like the LMS and ASL, and brings interdisciplinary insight informed by a postgraduate diploma in social science and earlier macroeconomic forecasting work. Colleagues describe him as someone who bridges rigorous theory with tool-building for empirical problems, advancing formal methods in physics in a hands-on way.
11 years of coding experience
BA, Mathematics, BA, Mathematics at University of OxfordPhD, General Topology, Analytic Topology, Stone-Cech Compactification, PhD, General Topology, Analytic Topology, Stone-Cech Compactification at The University of Sheffield
English, French, German, Hungarian
Github Skills (8)
gpy10
mathematical10
python10
modeling10
numpy10
kernel-methods10
gaussian-processes10
machine-learning9
Programming languages (9)
Github contributions (5)
SheffieldML/GPy
Jun 2016 - May 2019
Gaussian processes framework in python
Role in this project:
Data Scientist
Data ScientistContributions:54 commits, 5 PRs, 44 pushes in 2 years 11 months
Contributions summary:Mike primarily contributed to the development of integral kernels for the GPy framework, a Gaussian processes library in Python. Their work involved implementing new kernel types, specifically for handling histogram or binned data, as well as updating and testing existing kernel functionalities. The changes included significant code modifications to classes like `Integral_Limits` and `Multidimensional_Integral_Limits` for improved performance and features. This indicates a focus on expanding the capabilities of the library for specific data types.
gaussiangaussian-processespython
lionfish0/GPAdversarialBound
Jan 2018 - Feb 2022
Contributions:48 pushes, 1 branch in 4 years 1 month
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