After growing up in Ecuador I was fortunate to have the opportunity to pursue an undergraduate and master’s degree in Computer Science at Cornell University. It was during this time that I was first introduced to the untapped potential of machine learning algorithms and their applications in both academia and industry. As I continued to explore these methods as an early employee of a machine learning startup and as an MPhil student in Cambridge, it became abundantly clear to me that the deployment of these algorithms is often constrained by their lack of interpretability. This is perhaps most limiting in healthcare settings, where transparency and accountability are of utmost importance. During my PhD I wish to explore ways to design high-performing machine learning systems that can learn to explain their decisions using concepts that are intuitive to users. If successful, the deployment of such systems in day-to-day medical diagnosis could not only provide opportunities for early intervention in critical patients but may also open new leads for research in fields outside of medicine. The possibility of achieving these prospects, and the challenge they represent, make this research something I am incredibly excited to pursue.
University of Cambridge Advanced Computer Science 2021
Cornell University Computer Science 2017