Biography

I am a Senior Privacy Researcher at Huawei Reserach, working on privacy, security and robustness of AI agents and LLMs. Previously I obtained my PhD at the Joint Academy of Doctoral Studies (JADS) launched between Imperial College London and Technical University of Munich. During my PhD I worked on topics such as privacy-preserving machine learning, attacks on collaborative machine learning, adversarial robustness, federated learning and memorisation in ML.

Some of my highlighted works include gradient-based model inversion attacks on collaboratively trained computer vision models (ACM TOPS 2023), low-cost empirical defences against privacy adversaries (PoPETS 2022), a framework for trustworthy collaborative medical image analysis (Nature Machine Intelligence 2021) and an overview of the current state of PPML and attacks on CML (Nature Machine Intelligence 2021).

Previously I was a Machine Learning Researcher at Microsoft Research (memorisation and factuality in differentially private LLMs for healthcare), Brave Research (efficient data and client selection in federated learning). I was also a Privacy Researcher at Oblivious (differentially private SQL and synthetic data), OpenMined (differentially private deep learning for healthcare). Outside of all that cool privacy and ML stuff I am a rower (mostly retired), Investment Parter at an early-stage deep tech VC fund (fully retired) and a WSET-certified expert in beer (no retirement planned any time soon).