I am a Lecturer in the Statistics Section of the Department of Mathematics, Imperial College London. I also hold an EPSRC research Fellowship until January 2020.


Biographical outline

2008-2011: PhD, University of Cambridge, UK
2011-2014: Research Fellow, University of Bristol, UK, and
2013: Visiting Research Fellow, Princeton University, USA
2014-2016: Research Fellow, Princeton University, USA
2016-present: Lecturer, Imperial College London, UK


Battey, H.S. and Cox, D.R. (2018)
Large numbers of explanatory variables: a probabilistic assessment.
Proc. R. Soc. Lond. A., 474. Software.

Avella, M., Battey, H.S., Fan, J., Li, Q. (2018)
Robust estimation of high-dimensional covariance and precision matrices.
Biometrika, 105, 271-284. Supplementary file.

Battey, H.S., Fan, J., Liu, Lu, and Zhu, Z. (2018)
Distributed testing and estimation in sparse high dimensional models.
Ann. Statist., 46, 1352-1382. Supplementary file.

Cox, D.R. and Battey, H.S. (2017)
Large numbers of explanatory variables, a semi-descriptive analysis.
Proc. Nat. Acad. Sci., 114 (32), 8592-8595. Software.

Battey, H.S. (2017)
Eigen structure of a new class of structured covariance and inverse covariance matrices.
Bernoulli, 23, 3166-3177.

Nieto-Reyes, A. and Battey, H.S. (2017)
Functional depth.
In Functional Statistics and Related Fields. Springer.

Battey, H.S., Feng, Q. and Smith, R.J. (2016)
Improving confidence set estimation when parameters are weakly identified.
Statist. Probab. Lett., 118 117-123.

Nieto-Reyes, A. and Battey, H.S. (2016)
A topologically valid definition of depth for functional data.
Statistical Science, 31 61-79.

Battey, H.S. and Linton, O.B. (2014)
Sieve estimation of multivariate elliptic densities.
J. Multivariate Analysis, 123 43-67. (code)

Battey, H.S. and Sancetta, A. (2013)
Conditional estimation for dependent functional data.
J. Multivariate Analysis, 120 1-17. (code)

Beale, N., Rand, D.G., Battey, H.S., Croxson, K., May, R.M., Nowak, M.A. (2011)
Individual versus systemic risk and the Regulator's Dilemma
Proc. Nat. Acad. Sci., 108 (31) 12647-12652