Applied Researcher & Computational Engineer interested in developing technology to enable and accelerate STEM
View My WorkI'm a PhD candidate at the University of Southampton's Rolls-Royce UTC for Computational Engineering & Design, focusing on geometric deep learning applications at the interface between computer-aided design and engineering/manufacturing.
With a background in aerospace engineering and industry experience in simulation and modeling, I'm passionate about developing innovative computational solutions that bridge the gap between design and practical implementation.
My research interests include machine learning and CAD/CAE integration, with a particular focus on how advanced computational methods can accelerate engineering workflows.
Implemented point-based NN approach from my PhD directly into the NX CAD environment using PyTorch/libtorch and NX UGOpen C++ APIs. Integrated into an existing proprietary RR C++ codebase.
Implemented a DLL for a background process to be queried by a MATLAB/Simulink model for data, significantly reducing memory and computation overhead. Designed the data structure and implemented in C.
Restructured an existing model to modularize it and add functionality, both in Simulink structure and MATLAB code. The model simulated trajectory due to various forces including aerodynamics, inertia, stage separation, and thrust.
Toolkit for creating arbitrary swirling inlet boundary conditions for use with a CFD framework (SU2). Code could also translate contour plot images into velocity values for boundary conditions.
Part of a team which designed, built, and flew a 7kg UAV with a 2kg payload. Designed a 'lifting body' fuselage and main wing, performed CFD analysis, and developed computer vision algorithms for target detection.
University of Southampton - Rolls-Royce UTC for Computational Engineering & Design
Researching the application of geometric deep learning to the interface between computer-aided design and computer-aided engineering.
Supporting the delivery of the 'Systems Design and Computing' module involving Arduino, electronics, and C++.
MBDA UK
Developing hierarchical and modular numerical models for system performance assessment, using MATLAB, Simulink, and C.
Received 'Reward & Recognition Award' for work done towards meeting a key model delivery milestone during the COVID-19 pandemic.
Queen's University Belfast
First Class Honours.