National Physical Laboratory

Spencer Thomas

Current interests

Spencer Thomas
  • Analytical techniques for real world problems and experimental data, including machine learning, statistical, optimisation, graph theoretic and equation-free methods
  • High performance computation and efficient implementation of algorithms
  • Tools and techniques to analyse complex and dynamical systems to extract insight into behaviour dependencies


Spencer Thomas graduated with a First Class Honours MPhys degree from the University of Surrey in 2010, which included a year-long research placement at the Joint Institute for Nuclear Astrophysics, University of Notre Dame, Indiana. After completing his undergraduate degree, Spencer began a PhD under the University of Surrey's Doctoral Training Centre programme. Initially working in quantum biology, he then moved to research in machine learning and computational biology. During his PhD, Spencer developed optimisation algorithms for the efficient reconstruction of biological networks from experimental data, as well as simulating mechanisms for the evolution of biological networks.

After being awarded his PhD in 2014, Spencer began working as a Research Fellow in Applied Mathematics at the University of Surrey, developing algorithms to analyse nonlinear stochastic systems. In particular, this method was applied to 'black-box' simulations in order to extract the underlying system behaviour and dependencies that is not otherwise obtainable. Spencer joined NPL in April 2016 as part of the NiCE-MSI group to develop analysis techniques for mass spectrometry imagining.

Selected publications

Contact details

Tel: 020 8943 6901

Last Updated: 11 May 2016
Created: 10 May 2016


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