I am a Computer Science PhD student at the University of Warwick supervised by Graham Cormode. Until the end of September 2018, I was based at the Alan Turing Institute for Data Science and Artificial Intelligence. My research interests are in randomised algorithms for large-scale data analysis, particularly for fundamental matrix computations. Prior to joining the CS department at Warwick I completed my MSci in Mathematics at the University of Birmingham.
In August and September 2018 I was a visiting graduate student at the Simons Institute for the Foundations of Data Science program. Prior to that I was an Enrichment Year Student at the Alan Turing Institute for Data Science during which I studied how large-scale regression problems can be solved more quickly using sparse random projections (currently under submission).
Currently, I am an Applied Science intern at Amazonâ€™s Cambridge Laboratory. My internship has focused on scalable streaming algorithms for principled anomaly detection.
Here is my CV
ICML 2018 , Leveraging Well-Conditioned Bases: Streaming and Distributed Summaries in Minkowski $p$-Norms, with Graham Cormode and David P. Woodruff, Accepted for long talk at ICML 2018 Paper Code
NeurIPS 2019 (workshop: Beyond First Order Methods in Machine Learning), Iterative Hessian Sketch in Input Sparsity Time, with Graham Cormode Paper Code
Current research focusing on projected frequency estimation on data streams of matrices and streaming anomaly detection for machine learning.