About Me

I am currently pursuing a PhD at the Mullard Space Science Laboratory, under the supervision of Prof. Lucie Green. There, the main focus of my research is in the application of machine learning (ML) techniques to solar physics, in particular focusing on how these techniques may help us forecast Coronal Mass Ejections (CMEs). Developing better prediction tools for CMEs would be relevant not only from a scientific point of view, by furthering our understanding of these events, but also from a practical point of view. Indeed, CMEs are one of the major drivers of space weather and can have a significant impact on our technological infrastructure.

When it comes to ML methods, I am interested in methods that are explainable and interpretable. Although what this may mean is still an open question, I believe it's a crucial step towards integrating ML more deeply into scientific research. ML has the potential to uncover the underlying physical processes it tries to model, furthering our understanding of physics. If we harness this potential, we can use ML to help us make new discoveries and answer questions we haven't even thought of yet.

However, the field of ML and AI is extensive and my broader interests extend into the realms of Artificial Intelligence and Artificial General Intelligence. I am deeply fascinated by the philosophical and psychological aspects of these fields, particularly the concept of consciousness in machines. The ethical considerations regarding the creation and interaction with potential artificial consciousness, how this consciousness may even be defined, are topics I find fascinating. Though not part of my formal training so far, these topics often find their way into my learning process and I hope to be able to explore them further in the future. In an era marked by rapid technological progress, I am eager to contribute and engage in discussions that shape how we develop and interact with emerging AI technologies.