We say that we will put the sun in a box. The idea is pretty. The problem is, we don’t know how to make the box.
– Pierre Gilles de Gennes
About me
I’m a first year PhD student at the University College London, supervised by Ilija Bogunovic.
My project is jointly supported by the UK Atomic Energy Authority (UKAEA), a government research institute seeking to lead the delivery of sustainable fusion energy, where I am a visiting researcher.
I work closely with the UKAEA integrated modelling group, designing scenarios for the UK’s proposed next-generation fusion reactor.
Research
Fusion power could be the biggest game-changer in history; to achieve it, we need advanced control systems and highly optimised designs.
My research connects ideas from control, optimisation, Bayesian statistics, and plasma physics in order to tackle the hardest engineering challenge humanity has ever faced.
Buzzwords that get me excited include:
- Probabilistic machine learning
- Verifiably robust and safe algorithms for critical systems
- Trajectory planning and controller design
- Adaptive and learning-based control
- Physics-informed machine learning
- Bayesian optimisation
Education
PhD, Machine Learning
University College London | Sep 2023 - present
MEng, Information and Control Engineering
University of Cambridge | Sep 2016 - Jul 2023
Thesis: Reinforcement learning and Bayesian optimisation for tokamak plasma control
Publications
Hobbies
I’m often found in the garage doing woodwork or outside looking after my garden. I also love hiking, jazz, classic novels, korfball, and board games.
I’m a passionate advocate for wider recognition and research concerning the long-term impacts of mild traumatic brain injury.