Timothy I. Cannings

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Timothy I. Cannings

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Contact:

School of Mathematics and Maxwell Institute for Mathematical Sciences,

University of Edinburgh,

James Clerk Maxwell Building,

Peter Guthrie Tait Road,

Edinburgh, EH9 3FD

I am a Reader in Statistics and Data Science in the School of Mathematics, University of Edinburgh. I completed my PhD with Prof Richard Samworth in the Statistical Laboratory at the University of Cambridge in 2015 and then worked with Prof Yingying Fan as a Postdoc at the University of Southern California. I moved to Edinburgh in August 2018.

My research is currently supported by a three-year EPSRC New Investigator Award on `New challenges in robust statistical learning' [EP/V002694/1].

Research interests

• Statistical learning: classification and clustering

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

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

• Subgroup analysis and subgroup selection

• Applications in genomics and precision medicine

Preprints and Publications

Sell, T., Berrett, T. B. and Cannings, T. I. (2023) Nonparametric classification with missing data. *Preprint*. (.pdf).

Müller, M. M., Reeve, H. W. J., Cannings, T. I. and Samworth, R. J. (2023) Isotonic subgroup selection. *Preprint*. (.pdf). The accompanying ** R ** package ** ISS ** is available from CRAN.

Sionakidis, A., Cannings, T. I., Figueroa, J. D. and Sims, A. H. (2023) A novel gene signature to predict response to neoadjuvant chemotherapy and endocrine treatment in estrogen receptor-positive breast cancer patients. *Preprint*. (.pdf).

Merzbacher, C., Ryan, B., Goldsborough, T., Hillary, R. F., Campbell, A., Murphy, L., McIntosh, A. M., Liewald, D., Harris, S. E., McRae, A. F., Cox, S. R., Cannings, T. I., Vallejos, C. A., McCartney, D. L. and Marioni, R. E. (2023) Integration of datasets for individual prediction of DNA methylation-based biomarkers. *Genome Biology*, **24**, 278. (.pdf).

Reeve, H. W. J., Cannings, T. I. and Samworth, R. J. (2023) Optimal subgroup selection. *Ann. Statist.*, **51**, 2342-2365. (.pdf).

Cheng, Y., Gadd, D. A., Gieger, C., Monterrubio-Gómez, K., Zhang, Y., Berta, I., Stam, M. J., Szlachetka, N., Lobzaev, E., Wrobel, N., Murphy, L., Campbell, A., Nangle, C., Walker, R. M., Fawns-Ritchie, C., Peters, A., Rathmann, W., Porteous, D. J., Evans, K. L., McIntosh, A. M., Cannings, T. I., Waldenberger, M., Ganna, A., McCartney, D. L., Vallejos, C. A. and Marioni, R. E. (2023) Development and validation of DNA Methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes. *Nature Aging*, **3**, 450-458. (.pdf). The accompanying ** R ** package ** MethylPipeR-UI ** is available on GitHub.

Bradley, J. R. and Cannings, T. I. (2022) Data-driven design of targeted gene panels for estimating immunotherapy biomarkers. *Commun. Biol.*, **5**, 156. (.pdf) The accompanying ** R ** package ** ICBioMark ** is available from CRAN and an associated *`Behind the Paper'* blog post can be read here.

Cannings, T. I. and Fan, Y. (2022) The correlation-assisted missing data estimator. *J. Mach. Learn. Res.*, **23**(41), 1-49. (.pdf)

Reeve, H. W. J., Cannings, T. I. and Samworth, R. J. (2021) Adaptive transfer learning. *Ann. Statist.*, **49**, 3618-3649. (.pdf)

Cannings, T. I. (2020) Random projections: Data perturbation for classification problems. * WIREs Computational Statistics*, **13**, 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

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)

Group Members (past and present)

• Jacob Bradley, PhD student Sept 2019-Sept 2023, cosupervised with Kevin Myant. (Research Engineer, Canon Medical)

• Louis Chislett, PhD student Sept 2022-, cosupervised with Louis Aslett, James Liley and Catalina Vallejos

• Ria Dunn, MSc by Research student Sept 2023-Feb 2024, cosupervised with Sjoerd Beentjes

• Vasilios Raptis, PhD student Sept 2022-, cosupervised with Alasdair Maclullich and Albert Tenesa

• Torben Sell, Post-doc May 2021-Aug 2023. (Lecturer, School of Mathematics, University of Edinburgh)

• Aristeidis Sionakidis, PhD student Sept 2020-Feb 2024, cosupervised with Jonine Figueroa. (Research Associate - Machine Learning, Department of Oncology, University of Cambridge)

• Wenxing Zhou, PhD student Sept 2022-

Some other interesting things

• Maxwell Institute for Mathematical Sciences

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