Career
- 2018-: PhD, CCIMI/DAMTP, University of Cambridge
- 2017-2018: Research Assistant, MRC Biostatistics Unit
- 2016-2017: MPhil in Computational Biology, University of Cambridge
- 2013-2016: BA in Mathematics, University of Cambridge
Research
Tom is a member of the Department of Applied Mathematics and Theoretical Physics Computational Biology research group, supervised by Dr Stephen Eglen and Dr Ari Ercole. His current research interests are in intensive care unit big data.
Publications
Bayesian model selection for multilevel models using integrated likelihoods.
– PloS one
(2023)
18,
e0280046
(doi: 10.48550/arxiv.2207.02144)
Bayesian model selection for multilevel models using integrated likelihoods
(2022)
(doi: 10.48550/arxiv.2207.02144)
Sepsis-3 criteria in AmsterdamUMCdb: open-source code implementation.
– GigaByte (Hong Kong, China)
(2022)
2022,
1
(doi: 10.46471/gigabyte.45)
Causality indices for bivariate time series data: A comparative review of performance
– Chaos: An Interdisciplinary Journal of Nonlinear Science
(2021)
31,
083111
(doi: 10.1063/5.0053519)
Causality indices for bivariate time series data: A comparative review of performance
– Chaos
(2021)
31,
083111
(doi: 10.1063/5.0053519)
DeepClean: Self-Supervised Artefact Rejection for Intensive Care Waveform Data Using Deep Generative Learning
– Acta Neurochirurgica: Supplementum
(2021)
131,
235
(doi: 10.1007/978-3-030-59436-7_45)
Causality indices for bivariate time series data: a comparative review of performance
(2021)
(doi: 10.48550/arxiv.2104.00718)
DeepClean: Self-Supervised Artefact Rejection for Intensive Care Waveform Data Using Deep Generative Learning.
(2019)
(doi: 10.1007/978-3-030-59436-7_45)
DeepClean -- self-supervised artefact rejection for intensive care waveform data using deep generative learning
(2019)
(doi: 10.48550/arxiv.1908.03129)
meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays
– PLoS Computational Biology
(2018)
14,
e1006506
(doi: 10.1371/journal.pcbi.1006506)