Could you tell us a little about yourself and about your studies before coming to Imperial?
I did my undergraduate degree in Materials Science and Engineering, also at Imperial, and following that I worked as a consultant. I became really interested in AI and wanted to shift to a more technical role, which led me to explore the idea of doing a master’s degree in that field.
What attracted you about the MSc in AI?
There were two things that made it really stand out to me: how practical it was, and its core focus on AI. First, with the range of courseworks and industry projects available I was confident that I would be able to jump into technical roles directly after the MSc. Secondly, I liked that the degree truly focuses on different fields and applications of AI thus providing a comprehensive foundation regardless of the field I might have wanted to pursue after.
What did you enjoy the most?
From a module perspective, I really enjoyed Machine Learning for Imaging, Reinforcement Learning, and Robot Learning. The extended projects—the AI software engineering group project, and the individual project—were definitely highlights as well.
What did you find more challenging?
Symbolic AI took me a bit of time to get my head around, but the teaching was great. Something that I praised (the coursework) was also quite difficult at times, especially when trying to gauge what level of performance of your models was a good stopping point.
Could you tell us about some of your achievements on the MSc that make you proud?
Some are small, some are bigger. Training my first model was really satisfying and going from that to training VAEs and GANs within a few months still blows my mind. I was also really proud of our software engineering group project. We collaborated with an industrial partner, which even led to an open-source contribution to one of their libraries.
What did you do in your spare time?
I was really focused on my degree during term time, but in my free time I loved trying new restaurants and catching up with friends. Imperial also has amazing student-run societies that are great to meet people from other courses and relax.
Could you tell us about your individual project?
I took advantage of the ability to self-propose your research project in order to investigate the application of Quality-Diversity algorithms to materials discovery. These methods stem originally from the field of robotics, but have been successfully used in other fields with complex optimisation problems. I wanted to see if they could translate to materials science too—they can!
What have you been doing since you graduated?
I worked on publishing my research project and started working at an applied research company as an ML Research Engineer. I’m currently working on applications of foundational models in the field of genomics.
Do you have any advice for prospective students?
If you’re interested in AI and are considering applying, then go for it! For me, doing the MSc was definitely the right choice and allowed me to make huge leaps in my knowledge and skill in such a short period of time.