Michael Burgess

Registered user since Thu 5 Sep 2024

Name:Michael Burgess
Bio:

I will soon start a part-time PhD in Computer Science and Philosophy at the University of Cambridge Computer Laboratory. My research is on Explainable AI, Probabilistic Programming Languages, Explanation, Interactive Explanatory Interfaces and Human-Computer Interaction.

My current research interests concern how we provide genuine explanations of computational models to those who are due them. This lies somewhat in tension with mainstream Explainable AI research which largely aims to provide model diagnostics to researchers building models. I draw from the emerging field “Simulation Intelligence” to provide more robust methods to provide genuine explanatory models, in particular Probabilistic Programming Languages and Agent-Based Modelling. Previously I studied Physics at Leeds University, with a final thesis on non-gradient-based machine learning methods for optimising experimental parameters in quantum metrology (differential evolution and particle-swarm optimisation).

In industry, I am the Head of Technical Consulting at Decoded, a Data & AI skills consultancy. There I work with national and multi-national clients primarily in investment banking, insurance and government to develop their practitioners knowledge and skills in Data Science, AI & Software Engineering, including designing and delivering MSc programmes in AI. I am a member of the government’s working group on the UK L7 (MSc) Artificial Intelligence programme and I have designed and delivered similar programmes for the UK defence sector. I have previously worked as a software engineer, data scientist, and industry researcher across defence, fintech, and similar.

Country:United Kingdom
Affiliation:University of Cambridge, UK
Research interests:Probabilistic Programming Languages, Computer Simulation & Modelling, Explainable AI, Human-Centric Computing, Philosophy of Science, Explanation,

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