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Edward Higson

Edward Higson
Room K14,
Kavli Institute for Cosmology,
c/o Institute of Astronomy,
Madingley Road

Cambridge CB3 0HA
Office Phone: +44 (0)1223 760796


2015 - Present: PhD in Physics, University of Cambridge. Supervisors: Prof. Anthony Lasenby and Prof. Mike Hobson.

2011 - 2015: MPhys in Physics, University of Oxford.

Research Interests

I am a third year PhD student working on Bayesian inference and machine learning methods, and their applications in astrophysics and cosmology. Recently my research has focused on nested sampling, Bayesian compressed sensing and neural networks. I created the dynamic nested sampling algorithm; a generalisation of nested sampling which is significantly more efficient for most parameter estimation problems and is implemented in the PerfectNS and dynesty packages. I am also interested in general relativity, theoretical cosmology and statistics.


Part III Relativistic Astrophysics and Cosmology

Part II General Relativity

Part IB Statistics (maths tripos) 


Key Publications

Dynamic nested sampling: an improved algorithm for parameter estimation and evidence calculation, E. Higson, W. Handley, M. Hobson and A. Lasenby, 2017, arXiv:1704.03459

Sampling errors in nested sampling parameter estimation, E. Higson, W. Handley, M. Hobson and A. Lasenby, 2017, Bayesian Analysis

The effect of phase front deformation on the growth of the filamentation instability in laser-plasma interactions, E. Higson, R. Trines et al., 2013, New Journal of Physics 15 (1), 015027