Supersonic Wing Design Optimisation and Exploration using Machine Learning Methods

Tim is a passionate Aerospace Engineer with experience in aerodynamic and aircraft design across a range of Mach numbers (low-Reynolds number regimes up to hypersonic). He is currently studying accelerated optimisation and design methods for low-boom supersonic wing design using surrogate-assisted techniques for his PhD at the Institute of Fluid Science, Tohoku University, under a Japanese government scholarship. Previously, he worked as an Aeromechanics Engineer at Airbus Group Innovations, developing methods for rapid buffet prediction and coupled aero-structural design and simulation of high aspect-ratio and folding transonic wings. Prior to that, he completed his MSc in Aerospace Vehicle Design at Cranfield University in 2014.

Pramudita Satria Palar (PhD; University of Tokyo) is an Assistant Professor at the Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung. Prior to his current position, he was a Research Fellow at the Institute of Fluid Science, Tohoku University. He completed his Ph.D. in Aeronautics and Astronautics from the University of Tokyo in 2015 and was a visiting researcher at the University of Cambridge in 2015 and at Leiden University in 2017. Pramudita's research interests are primarily in the areas of computationally expensive optimization, surrogate model / statistical learning, uncertainty and sensitivity analysis, and their applications on aerospace design optimization. He has published his research in top journals such as AIAA Journal, Computer Methods in Applied Mechanics and Engineering, and Aerospace Science and Technology.