alexandros kontogiannis

EPSRC Research Fellow in Fluid Dynamics @ Cambridge University

my_pic.jpg

Hopkinson Lab (ISO-40)

CUED Trumpington Street

Cambridge CB2 1PZ UK

ak2239@cam.ac.uk


I am EPSRC research fellow in fluid dynamics and applied mathematics at Cambridge University Engineering Department.

I am currently working on Bayesian inverse problems in fluid dynamics for magnetic resonance velocimetry. In the past, I have worked on aerodynamic modelling, fluid-structure interaction, simulations of ice accretion on aircraft wings, and aerodynamic shape optimisation.

My main research concerns the formulation of new machine learning methods that automatically reconstruct corrupted flowfields. These methods learn the most probable simulation that corresponds to the corrupted flowfield, and, at the same time, infer unknown quantities (e.g. pressure) that are either hard or impossible to measure otherwise.

In a nutshell, I develop algorithms that learn the most probable physical model (aka digital twin) of the flowfield dynamics from data.

selected publications

2024

  1. 3d_jet_reco_turb.png
    Bayesian inference of mean velocity fields and turbulence models from flow MRI
    A. Kontogiannis, P. Nair, M. Loecher, D. B. Ennis, and 2 more authors
    2024
  2. 3d_jet_reco.jpeg
    Learning rheological parameters of non-Newtonian fluids from velocimetry data
    A. Kontogiannis, R. Hodgkinson, and E. L. Manchester
    2024
  3. bayesian_inv_ns_problems.png
    Bayesian inverse Navier–Stokes problems: joint flow field reconstruction and parameter learning
    A. Kontogiannis, S. V. Elgersma, A. J. Sederman, and M. P. Juniper
    Inverse Problems, Dec 2024

2023

  1. pics_concept4.png
    Physics-informed compressed sensing for PC-MRI: an inverse Navier-Stokes problem
    A. Kontogiannis, and M. P. Juniper
    IEEE Transactions on Image Processing, Jan 2023

2022

  1. graphical_abstract.png
    Joint reconstruction and segmentation of noisy velocity images as an inverse Navier–Stokes problem
    A. Kontogiannis, S. V. Elgersma, A. J. Sederman, and M. P. Juniper
    Journal of Fluid Mechanics, Jul 2022