Timothy I. Cannings



School of Mathematics,

University of Edinburgh,

James Clerk Maxwell Building,

Peter Guthrie Tait Road,

Edinburgh, EH9 3FD


I am a lecturer in statistics and data science at the School of Mathematics, University of Edinburgh, and a Turing Fellow at the Alan Turing Institute. I completed my PhD with Prof Richard Samworth in the Statistical Laboratory at the University of Cambridge in 2015. I also worked with Prof Yingying Fan as a Postdoc at the University of Southern California.

Research interests

• Statistical learning: classification and clustering

• High-dimensional data: data perturbation techniques, random projections

• Incomplete data: semi-supervised problems, noisy data, transfer learning

• Applications in genomics

Publications and Preprints

Cannings, T. I. and Fan, Y. (2020) The correlation-assisted missing data estimator. Preprint. (.pdf).

Cannings, T. I. (2020) Random projections: Data perturbation for classification problems. Wiley Interdisciplinary Reviews: Computational Statistics, DOI: 10.1002/wics.1449.

Cannings, T. I., Fan, Y. and Samworth, R. J. (2020) Classification with imperfect training labels. Biometrika, 107, 311-330. (.pdf).

Cannings, T. I., Berrett, T. B. and Samworth, R. J. (2020) Local nearest neighbour classification with applications to semi-supervised learning. Ann. Statist., 48, 1789-1814. (.pdf).

Dubourg-Felonneau, G., Cannings, T. I., Cotter, F., Thompson, H., Patel, N., Cassidy, J. W. and Clifford, H. W. (2018) A framework for implementing machine learning on Omics data. NeurIPS ML4H workshop (.pdf).

Cannings, T. I. and Samworth, R. J. (2017) Random projection ensemble classification. J. Roy. Statist. Soc., Ser. B (with discussion), 79 , 959-1035. (.pdf). The accompanying R package RPEnsemble is available from CRAN.

Cannings, T. I. (2015) New Approaches to Modern Statistical Classification Problems. PhD thesis (.pdf).

Cannings, T. I. (2013) Nearest neighbour classification in the tails of a distribution. (.pdf)

Some other interesting things

The Centre for Statistics

Maxwell Institute for Mathematical Sciences

Cambridge Cancer Genomics