About me
I’m a Computer Science student at the University of Cambridge.
My interests are in Deep Learning, with a particular focus on Natural Language Processing. In addition, I appreciate the awesome, research-driven engineering1 behind the highly-performant deep learning systems!
Throughout my year-long MPhil degree, I have worked along the CaMLSys group, where I focused on Federated Learning. My dissertation explored how several institutions with limited computational resources can collaborate on training a joint foundational language model. During my studies, I also benchmarked the inner workings of torch.compile(), and explored the KV-caching strategies in LLM inference. On the more theoretical front, I looked into the phenomenon of attention sinks2 in transformers and studied the concept of dynamic tokenisation. What a year it was!
Previously, I have been working with researchers from UCL NLP on BritLLM – a joint effort towards producing freely available Large3 Language Models for UK languages4. In my undergraduate dissertation, I focused on the problem of the poor availability of LLMs for low-resource languages and worked on language model adaptation methods for African languages. Furthermore, we explored Data-Efficient Task Unlearning in LMs, a method for increasing the safety of language models and removing their undesired capabilities.
Please, don’t hesitate to reach out or connect! I’m very happy to hear about your research, tell you a bit about mine, or just chat about anything interesting!