معرفی
Dr Matthew Aldridge is a Lecturer in the School of Mathematics at the University of Leeds, affiliated with the Statistics department. He holds a PhD in Mathematics from the University of Bristol (2011) and earned his MMath and BA in Mathematics from the University of Cambridge.
- PhD Mathematics, University of Bristol, 2011
- Part III Mathematics (MMath), University of Cambridge, 2007
- BA (Hons) Mathematics, University of Cambridge, 2006
His research lies at the intersection of probability, information theory, combinatorics, and statistics, with a strong focus on group testing—a method for efficiently identifying rare positives in large populations, widely applied during the COVID-19 pandemic. He also investigates interference in multiuser communication systems and develops discrete analogues of continuous probability concepts. His current PhD projects include Pooled testing to prevent the next pandemic and Genuinely discrete discrete probability.
His recent publications center on group testing from both practical and theoretical angles, including survey papers co-authored with David Ellis and with Oliver Johnson and Jonathan Scarlett. These works explore applications in public health, communications, and genetics, and are grounded in information theory and statistical inference.
Dr Aldridge teaches MATH5835M Statistical Computing, covering Monte Carlo estimation, variance reduction techniques (control variates, antithetic variables, importance sampling), random number generation, Markov Chain Monte Carlo (MCMC), and bootstrap methods. He emphasizes practical implementation using R and provides detailed lecture notes and problem sheets.
He is actively engaged in research supervision and welcomes PhD applicants. His academic presence includes profiles on arXiv, Google Scholar, and ORCID (0000-0002-9347-1586).
