I am a final-year PhD student supervised by Prof. Graham Cormode and Prof. Carsten Maple (WMG). Before starting my PhD, I graduated with a first-class MEng in Discrete Mathematics at the University of Warwick.

My research sits at the intersection of computer security, data privacy, and machine learning, with a focus on privacy-preserving machine learning. I am particularly interested in Differential Privacy (DP), Federated Learning (FL), and Federated Analytics.

News

• [Sept 2025 - Mar 2026] Part-time Research Collaborator @ Meta: Generative modelling for tabular data.
• [September 2025] Attending VLDB 2025 @ London, UK; presenting the tutorial on “Synthetic Tabular Data: methods, attacks and defences”.
• [August 2025] Attending KDD 2025 @ Toronto, Canada; presenting the tutorial on “Synthetic Tabular Data: methods, attacks and defences”.
• [Summer 2025] Research Scientist Intern @ Meta, Menlo Park, CA: Central Applied Science (CAS) team; large-scale missing data imputation.
• [May 2024 - May 2025] Part-time Research Collaborator @ Meta: Scaling private synthetic tabular data.
• [August 2024] Attending KDD 2024 @ Barcelona; presenting “FLAIM: AIM-based Synthetic Data Generation in the Federated Setting”.
• [May 2023] Attending ICLR 2023 @ Kigali; presenting “CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning”.
• [December 2022] Attending CCS 2022 @ Los Angeles; presenting “Federated Boosted Decision Trees with Differential Privacy”.
• [Summer 2022] Research Intern @ Meta, Paris: Empirical privacy measurement in federated learning.