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Research

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Louis Aslett, BA (Mod), PhD Trinity College Dublin

Personal web page

Assistant Professor, Statistics in the Department of Mathematical Sciences
Telephone: +44 (0) 191 33 43067
Room number: CM212

(email at louis.aslett@durham.ac.uk)

Current Research

My current primary research interest is at the interface between cryptography and statistics, with the focus on privacy preserving statistical analyses. My personal interest is on the statistics side of this fusion, developing novel statistical methodology which is amenable to use in the constrained environment of encrypted computation made possible by recent developments in homomorphic encryption.

My other main strand of research is in reliability theory, where interest is in the structural reliability of engineered systems, usually taken from a Bayesian perspective. I also have research interests in computational acceleration of Hidden Markov Models (HMMs) as used in genetics which result in intractable inference as population sizes grow. Threaded through all these research interests is a particular interest in modern massively parallel computing architectures such as GPUs and the development of statistical methodology which is amenable to implementation in such environments.

Grants

SPARRA (Scottish Patients At Risk of Re-admission and Admission)

I am seconded to the Alan Turing Institute working on a project for NHS Scotland to update SPARRA. SPARRA is a model constructed on the entire Scottish population using centralised NHS data in order to predict those patients who require early primary care intervention to reduce the risk of emergency hospital admission.

Atom Bank KTP

Myself and Camila Caiado are running the Durham part of a Knowledge Transfer Partnership between Atom Bank, Newcastle University and Durham University. The project is exploring the use of encrypted statistical methods in mortgage book modelling.

Research Groups

Department of Mathematical Sciences

Research Interests

  • Cryptography and Privacy in Statistics
  • Reliability Theory
  • Bayesian Statistics
  • MCMC
  • Computational Statistics and High Performance Computing

Indicators of Esteem

  • Invited talks:
    • Bayesian Statistics in the Big Data Era, Marseille, France, 2018 (forthcoming).
    • Isaac Newton Institute, University of Cambridge. Scalable Statistical Inference Workshop, 2017.
    • 3rd UCL Workshop on the Theory of Big Data, 2017.
    • Google Inc., European Headquarters, 2013.
  • Visiting Turing Fellow, The Alan Turing Institute, London (2018-19):

    Partially seconded as a Fellow to The Alan Turing Institute, the UK national institute for data science and artificial intellegence.

Publications

Conference Paper

  • Esperança, P. M., Aslett, L. J. M. & Holmes, C. C. (2017), Encrypted accelerated least squares regression, in Singh, Aarti & Zhu, Jerry eds, Proceedings of Machine Learning Research 54: The 20th International Conference on Artificial Intelligence and Statistics. Fort Lauderdale, Florida, PMLR, Fort Lauderdale, FL, USA, 334-343.
  • Wilson, S. P., Mai, T., Cogan, P., Bhattacharya, A., Robles-Sánchez, O., Aslett, L. J. M., Ó Ríordáin, S. & Roetzer, G. (2014), Using Storm for scaleable sequential statistical inference, in Gilli, Manfred, González-Rodríguez, Gil & Nieto-Reyes, Alicia eds, 21st International Conference on Computational Statistics (COMPSTAT 2014). Geneva, Switzerland, International Association for Statistical Computing, Geneva, 103-109.

Journal Article

Software

Supervises

Selected Grants

  • 2018: SPARRA: Scottish Patients At Risk of Re-admission and Admission, ATI Secondment