CV

Pursuing doctoral studies in topics related to gauge/gravity duality at the University of Southampton. Possesses 8 months of cumulative research experience developed through a number of research internships. Solves problems by applying mathematical and coding experience to study a variety of physical systems. Interested in pursuing a career in theoretical physics research.

Education

  • Sep 2025 - Present
    PhD Mathematical Sciences
    University of Southampton, Southampton, UK
  • Oct 2024 - Jun 2025
    MASt Mathematics (Theoretical Physics)
    University of Cambridge, Cambridge, UK
    • Essay Title - Positivity of Bondi Energy in General Relativity.
    • Relevant Modules
      • Quantum Field Theory
      • General Relativity
      • Advanced Quantum Field Theory
      • String Theory
      • Black Holes
    • Audited Modules
      • Gauge/Gravity Duality
      • Solitons, Instantons and Geometry
      • Canonical Gravity
      • Cosmology
      • Symmetries, Particles and Fields
      • Statistical Field Theory
  • Sep 2020 - Jun 2024
    MSci Theoretical Physics
    University College London, London, UK
    • Final Year Project - Uncertainties on Parton Distributions.
    • Supervisor - Professor Robert Thorne
    • Relevant Modules
      • Quantum Field Theory
      • Mathematics for General Relativity
      • Practical Machine Learning for Physicists
      • Techniques of High-Performance Computing
      • Cosmology

Research Experience

  • Jul - Aug 2025
    Cambridge Mathematics Placement
    Sainsbury Laboratory Cambridge University (SLCU)
    • Supervisor - Dr Amir Porat
    • Completed an 8-week project on modelling plant growth by implementing concepts from Riemannian geometry using C++.
  • Jul - Sep 2023
    Astrophysics Summer Research Programme
    Department of Physics, University of Oxford
    • Supervisor - Dr James Matthews
    • Undertook an 8-week project on modelling disk winds from the accretion disk of X-ray binaries using the Monte Carlo radiative transfer code: PYTHON.
    • Devised a method for approximating the movement of points in the output parameter space using a Monte Carlo string energy minimisation method.
    • Successfully reproduced P-Cygni blueshifted absorption lines in the optical spectrum for an X-ray binary as seen in observations for the first time.
  • May - Jul 2023
    MAPS Research Internship
    High Energy Physics (HEP), University College London
    • Supervisor - Professor Jonathan Butterworth
    • Undertook a 6-week project on analysing data from the LHC using the CONTUR package in Python to constrain the parameter space of dark meson masses in a composite dark matter model.
    • Created code to verify simulated cross-sections from RIVET with detector data.
    • Results of the project are available here.
  • May - Jul 2022
    Biophysics Research Internship
    Institute for the Physics of Living Systems (IPLS), University College London
    • Supervisor - Dr Zena Hadjivasiliou
    • Completed a 10-week project on using coupled, non-linear, differential equations to simulate the evolution of a gene regulatory network in Python to explore convergence in evolution.
    • Delivered two presentations to other IPLS students and their supervisors on the aims and results of the project. Additionally, wrote a report on the outcomes of the investigation.

Honors and Awards

  • 2025
    • Jennings Prize - Achieved a First Class or Distinction in University examinations as a Wolfson College Student.
  • 2024
    • Dean's list - Top 5% of the UCL Faculty of Mathematical and Physical Sciences.
    • Winton Prize Recipient - Best overall academic achievement by a UCL 4th year MSci Theoretical Physics student.

Skills and Interests

  • Adept in Python, including NumPy, pandas, Astropy, Numba, SciPy and Keras packages.
  • Ability to model physical systems in Mathematica and C++, utilising Eigen, gnuplot and SDL libraries.
  • Proficient in producing reports and documents using LaTeX/Overleaf.
  • Experienced in using the Unix shell in Linux to run simulations written in Python and C on a cluster developed in the research experiences listed above.
  • Constructs programs in free time to develop coding aptitude and learn how to apply new concepts.