The highlights of the past seven months of continuous struggle while working from home is that I passed my Master part of the integrated PhD and MSc programme, and that I also passed my transfer to become a full PhD student (Hurray!)
Perhaps I can consider myself “lucky” because my PhD project is a fully computational one. Regardless of a few technical difficulties encountered in the first few months of working from home, work then continued relatively smoothly. During the past several months I had been working on the computational modelling of the mechanical behaviour of a segment of the spine before and after implanting a device that fuses vertebrae together. This required knowledge of the modelling software, a lot of literature reading, hand calculations, and many trial-and-error iterations. The learning curve was very steep, but I thoroughly enjoyed the different activities and was proud to write about them in my transfer report. Now, I have initial results that seem sensible, and more accurate evaluations will be conducted soon.
Currently, I’m preparing for the next big step in my project, which will be about using machine learning techniques to perform the same simulations I’ve performed before, but with extreme speed. Theoretically reducing computation time from 24 hours to around a few seconds. Therefore, I’m looking at automating the mechanical analysis, which will allow me to generate a training dataset for the machine learning algorithm. I’m also attending an online course in machine learning, which I believe will provide me with the basic knowledge I need to start designing my algorithm.