About
I am a Ph.D. candidate at Imperial College London, supervised by Dr. Gege Wen and Prof. Samuel Krevor. I am broadly interested in AI and machine learning for physics, with an emphasis on fluid dynamical systems. My Ph.D. focuses on modelling multiphase flow in porous media: how different fluids displace one another inside complex, microscale structures such as rock. This research is closely tied to energy systems and a sustainable future, from storing carbon dioxide deep underground to storing hydrogen for clean energy.1
I obtained my MSc in Applied Computational Science and Engineering from Imperial College London, under the supervision of Dr. Stephan Kramer and Prof. Matthew Piggott, and my BEng in Computer Science and Information Technology from Southwest University.
Footnotes
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Underground storage relies on rock whose tiny pores are filled with salty water, which the injected gas must push aside. See the British Geological Survey, Understanding carbon capture and storage. ↩
Research
- AI/ML for physics. Neural surrogate models that learn physical systems from data, with an emphasis on fluid dynamics.
- Computational methods. Lattice Boltzmann methods for modelling multiphase flow, finite element methods and mesh adaptation.
News
I was awarded a Janet Watson Ph.D. Studentship and will be starting my Ph.D. project in Sep. 2024 at Imperial College London.
I obtained my MSc degree from Imperial College London with Distinction.
