Dr. N.A.K. (Anh Khoa) Doan
Dr. N.A.K. (Anh Khoa) Doan
Ruimte: 64.HSL 0.37
Dr. (Nguyen) Anh Khoa Doan is an Assistant Professor in AI for Fluid Mechanics at the faculty of Aerospace Engineering at TU Delft. He obtained a dual Master degree in Aerospace Engineering at the Free University of Brussels (ULB) and the Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO) in 2012. In parallel, he also received a Master of Research from the Université de Toulouse III Paul Sabatier. Subsequently, he obtained his PhD in Engineering at the University of Cambridge in 2018 with his research covering the direct numerical simulations of turbulent (reacting) flows and of a novel low-emission combustion concept called MILD combustion. During this period, he also covered research topics related to hydrogen combustion and turbulence/combustion modelling and spent some time as a visiting researcher at the Sandia National Laboratories, USA. After this, he worked as a postdoctoral fellow at the Technical University of Munich at the Institute for Advanced Study and the Mechanical Engineering department from 2018 focusing on the development of Machine Learning and AI-based tools for the prediction and control of extreme events in turbulence and turbulent reacting flows, before joining TU Delft in March 2021.
Dr. Doan's research interest lies in the development of AI-based tools for the prediction and analysis of turbulent (reacting) flows, which can deeply contribute towards the development of more energy efficient and sustainable aircrafts, wind turbines or power generation systems. His expertise includes
- Machine Learning and Artificial Intelligence tools for fluid mechanics
- Physics of turbulent (reacting) flows
- Flameless/MILD combustion
- CFD (Direct Numerical Simulation and Large Eddy Simulation)
- Modelling in turbulence and turbulent reacting flows
- Thermoacoustic instability prediction
- Hydrogen combustion
- 2021- ongoing: Co-leader of the TU Delft AIFluids lab
- 2019-2021: Co-Investigator - PRACE Tier1 DECI project PINNTFlows "Physics-Informed Neural Networks for Turbulent Flows"
- 2018-2019: Co-Investigator - UK Tier2 Research Allocation Panel Project cs054 "Data-driven prediction of rare and extreme events in turbulent reacting flows"
- 2015-2016: Co-Investigator - ARCHER Research Allocation Panel Project e419 "Direct Numerical Simulation of non-premixed MILD Combustion"
- 2020: Stanford CTR Summer Program Visiting Researcher Award
- 2018: ARCHER UK Case Award
- 2014-2018: Qualcomm European Research Studentship & Honorary Cambridge Trust Scholarship at Cambridge University
- 2014: Charles Frerichs prize in Engineer at Université Libre de Bruxelles
Auto-Encoded Reservoir Computing for Turbulence Learning
Nguyen Anh Khoa Doan / Wolfgang Polifke / Luca Magri
Chaotic systems learning with hybrid echo state network/proper orthogonal decomposition based model
Mathias Lesjak / Nguyen Anh Khoa Doan
Short- And long-term predictions of chaotic flows and extreme events
A physics-constrained reservoir computing approach
N. A.K. Doan / W. Polifke / L. Magri
2021-03-01 - 2023-03-01