CV

This is a brief CV following the standard set by jsonresume.org. For the complete version, follow the link to the PDF.

Basics

Name Lloyd Fung
Email (see ORCiD)
Url https://llfung.github.io/
Summary Fluid dynamicist. Machine Learning Researcher. Aeronautical Engineer. Mathematician with a strong interest in modelling anything that moves.

Work

  • 2024.10 - 2028.09

    London, UK

    Imperial College Research Fellow
    Department of Aeronautics, Imperial College London
    Flagship early-career research fellowship of Imperial College London. Also part of the I-X Centre for AI in Science
    • Supervisor: Prof. Luca Magri
    • Collaborators: Dr Urban Fasel, Dr Davide Amato
  • 2024.04 - 2024.09

    London, UK

    Research Associate
    Alan Turing Institute
    PDRA for the Adjoint-accelerated Programmable Inference for Large PDEs project, which aims to incorporate adjoint method into the Probabilistic Programming framework Turing.jl such that it can be used to assimilate data into PDE models.
    • Supervisor: Prof. Matthew Juniper
    • Attached to the Department of Engineering, the U of Cambridge
  • 2021.10 - 2024.09

    Cambridge, UK

    Research Fellow
    Peterhouse, University of Cambridge
    A 3-years Junior Research Fellowship at Peterhouse, University of Cambridge. This highly competitive fellowship is awarded to early-career researchers in any field of study.
    • Attached to the Mathematical Biology group at the Department of Applied Mathematics and Theoretical Physics (DAMTP), Centre for Mathematical Sciences
    • Supervisors: Prof. Raymond Goldstein, Prof. Eric Lauga

Education

  • 2021.10 - 2024.09

    London, UK

    PhD
    Imperial College London
    Aeronautics Research
  • 2017.10 - 2021.09

    London, UK

    MEng
    Imperial College London
    Aeronautical Engineering with a Year in Industry

Certificates

Languages

English
Native
Cantonese
Native

Interests

Machine Learning
Physics-Informed Machine Learning
Data-Driven Modelling
Digital Twins
Data Assimilation
Sparse Identification of Nonlinear Dynamical Systems (SINDy)
Symbolic Model Discovery
Active Learning
Bayesian Inference
Physics-Informed Neural Networks
Information Theory
Causality
Neural ODEs
Echo State Networks
Reservoir Computing
Extreme Learning Machines
Fluid Dynamics
Low Reynolds Number Hydrodynamics
Complex Fluids
(Biologically) Active Fluids
Non-Newtonian Fluids
Suspension Dynamics
Sedimentation
Turbulence
Fluid-Structure Interaction
Computational Fluid Dynamics (CFD)
Mathematical Biology
Collective Behaviour
Pattern Formation
Bioconvection
Continuum Modelling
Active Matter
Active Suspensions
Active Brownian Particles

References

Professor Matthew Juniper
Professor in Thermofluid Dynamics at the Department of Engineering, University of Cambridge. Supervisor during my time at the Alan Turing Institute.
Professor Luca Magri
Professor of Scientific Machine Learning. Current supervisor.