Biography

The idea of versatile models able to identify and utilise complex patterns in data has always been an intriguing part of Information Engineering. Whilst studying at the University of Cambridge, I conducted multiple research projects with a special focus on a family of such models called deep neural networks. Applied to areas ranging from speaker diarisation to active learning, I slowly started to understand the wide ranging applicability, but also drawbacks of this family of approaches. One of these drawbacks is the lack of uncertainty estimation, the ability to account a model’s prediction to various causes of uncertainty, and this is where I will focus my research. I plan on developing efficient neural networks that will be able to quantify different types of uncertainties, and apply them in both high-risk and sensitive domains, where previously, such models would not have been applicable due to a limited understanding of how and when they work.

Previous Education

University of Cambridge Eng. Tripos (Information Eng.) 2021