“I am developing a completely new type of computer-assisted technique that combines tools from different areas of mathematics with the latest advances in numerical optimisation”
I joined Imperial as an undergraduate back in 2010 to study Aeronautical Engineering. I found myself so much at home that after graduating I decided to stay, first as a PhD student and now as an Imperial College Research Fellow.
My work explores new ways in which optimisation – the science of doing things as well as possible – can help engineers design technology that performs at its best, and is robust to changes in its operating environment. This is key to making industries such as energy and transport sustainable.
To meet this ambitious goal, one must be able to answer questions like, “How much energy can a wind turbine generate?” or “In which conditions does it operate safely?”. High-fidelity computer simulations and machine learning methods can only provide partial answers because, for engineering systems of such complexity, the number of scenarios that one can simulate accurately and use to train artificial intelligence is typically very limited.