| Description and assessment of the new ONERA 2D icing suite IGLOO2D P Trontin, A Kontogiannis, G Blanchard, P Villedieu 9th AIAA Atmospheric and Space Environments Conference, 3417, 2017 | 101 | 2017 |
| An extended rough-wall model for an integral boundary layer model intended for ice accretion calculations E Radenac, A Kontogiannis, C Bayeux, P Villedieu 2018 Atmospheric and Space Environments Conference, 2858, 2018 | 23 | 2018 |
| Joint reconstruction and segmentation of noisy velocity images as an inverse Navier–Stokes problem A Kontogiannis, SV Elgersma, AJ Sederman, MP Juniper Journal of Fluid Mechanics 944, A40, 2022 | 17 | 2022 |
| Robust fluid-structure interaction analysis of an adaptive airfoil using shape memory alloy actuators T Machairas, A Kontogiannis, A Karakalas, A Solomou, V Riziotis, ... Smart Materials and Structures 27 (10), 105035, 2018 | 13 | 2018 |
| Viscous-inviscid analysis of transonic swept wings using 2.5 D RANS and parametric shapes A Kontogiannis, M Parenteau, E Laurendeau AIAA Scitech 2019 Forum, 2116, 2019 | 12 | 2019 |
| Physics-informed compressed sensing for PC-MRI: an inverse Navier–Stokes problem A Kontogiannis, MP Juniper IEEE Transactions on Image Processing 32, 281 - 294, 2022 | 9 | 2022 |
| Adjoint state of nonlinear vortex-lattice method for aerodynamic design and control A Kontogiannis, E Laurendeau AIAA Journal 59 (4), 1184-1195, 2021 | 7 | 2021 |
| Sensitivity of Glaze Ice Accretion and Iced Aerodynamics Prediction to Roughness A Kontogiannis, A Prakash, E Laurendeau, F Moens 26th Annual Conference of the Computational Fluid Dynamics Society of Canada …, 2018 | 3 | 2018 |
| Bayesian inverse Navier–Stokes problems: joint flow field reconstruction and parameter learning A Kontogiannis, SV Elgersma, AJ Sederman, MP Juniper Inverse Problems 41 (1), 015008, 2024 | 2 | 2024 |
| Learning rheological parameters of non-Newtonian fluids from velocimetry data A Kontogiannis, R Hodgkinson, EL Manchester arXiv preprint arXiv:2408.02604, 2024 | 1 | 2024 |
| Inverse problems in fluid dynamics for magnetic resonance velocimetry A Kontogiannis | 1 | 2024 |
| Inverse Problems in Magnetic Resonance Velocimetry: Shape, Forcing and Boundary Condition Inference A Kontogiannis, M Juniper Fluids Engineering Division Summer Meeting 85291, V002T04A018, 2021 | 1 | 2021 |
| Physics-informed compressed sensing: reconstruction of magnetic resonance velocimetry signals as an inverse Navier-Stokes problem A Kontogiannis, M Juniper APS Division of Fluid Dynamics Meeting Abstracts, H20. 001, 2021 | 1 | 2021 |
| Inverse problems in magnetic resonance velocimetry: shape, velocity and boundary condition inference A Kontogiannis, M Juniper APS Division of Fluid Dynamics Meeting Abstracts, T07. 012, 2020 | 1 | 2020 |
| Methods and systems for improved reconstruction of magnetic resonance velocimetry data and a method of compressing flow data of a fluid M Juniper, A Kontogiannis US Patent App. 18/291,138, 2025 | | 2025 |
| Bayesian inference of mean velocity fields and turbulence models from flow MRI A Kontogiannis, P Nair, M Loecher, DB Ennis, A Marsden, MP Juniper arXiv preprint arXiv:2412.11266, 2024 | | 2024 |
| 3D flow-MRI data of steady axisymmetric laminar jet flow of a shear-thinning fluid A Kontogiannis, R Hodgkinson, S Reynolds, E Manchester | | 2024 |
| Proceedings of the NFFDy Summer Programme on ‘Data in Fluids’ A Atoufi, L Baker, F Contò, M Crowe, A Doak, R Doran, A Guseva, ... | | 2024 |
| Learning Bayesian digital twins of flows from PC-MRI data A Kontogiannis, M Juniper Bulletin of the American Physical Society, 2023 | | 2023 |
| Physics-enhanced velocimetry (PEV) for joint reconstruction and segmentation of noisy velocity images M Juniper, A Kontogiannis, A Sederman, S Elgersma Bulletin of the American Physical Society 67, 2022 | | 2022 |
Prof. Matthew P. JuniperProfessor of Thermofluids Dynamics, University of CambridgeПідтверджена електронна адреса в cam.ac.uk
