Graham Van Goffrier Research Affiliate

Graham Van Goffrier is a second-year PhD student in neutrino theory and data science at University College London and is loving every minute of it. Mathematics has long been the driving passion in his life, and his research tends to straddle the boundary between theory and application. At present, he is investigating how numerical Bayesian inference methods can be applied to the hunt for neutrinoless double-beta decay. He collaborates with the Engineering Department at the University of Cambridge on geometric optimization techniques in the cone of symmetric positive-definite (SPD) matrices. On the data science side, he recently collaborated with the UK Atomic Energy Authority on surrogate modeling of the tritium breeding ratio, a key quantity in the development of the next generation of D-T breeder reactors, such as ITER. Last but not least, as a Wolfram Summer School student and research affiliate, he is studying the construction of fully discretized gauge theories, which can be thought of as an extension to lattice gauge theory where the underlying space is a general hypergraph, and the gauge group is finitely represented by a graph permutation. His prior education has been in physics (BS) and electrical engineering (MS) at the University of Maine, followed by applied mathematics (MASt) at the University of Cambridge.



Institutional Affiliation

University College London

Research Topics & Interests

  • Mathematical Physics
  • BSM Neutrino Theory
  • Discrete Gauge Theories
  • Geometric Optimisation
  • Machine Learning