I am a Lecturer in Biostatistics with a joint position in the Department of Mathematics (Statistics Section) and the Department of Epidemiology and Biostatistics.
Throughout my career I have been interested in the development of statistical methods for the analysis of genomics datasets, to help identify and understand the causes of various diseases. Before joining Imperial, I worked as a Statistician at the University of Cambridge where I also completed my BA in Mathematics, MPhil and PhD in Statistics.
My other research interests include modelling cyber-security data-sources for the development of anomaly detection techniques.
I teach the the M5MS14 Statistical Bioinformatics and Genetics module as part of the MSc in Statistics. I am also co-leader of the Bayesian Statistics and Spatial analysis module of the MSc in Epidemiology.
et al., 2016, Correlation of pre-operative CT findings with surgical & histological tumor dissemination patterns at cytoreduction for primary advanced and relapsed epithelial ovarian cancer: A retrospective evaluation, Gynecologic Oncology, Vol:143, ISSN:0090-8258, Pages:264-269
et al., 2016, Regulatory T Cell Responses in Participants with Type 1 Diabetes after a Single Dose of Interleukin-2: A Non-Randomised, Open Label, Adaptive Dose-Finding Trial, Plos Medicine, Vol:13, ISSN:1549-1676
Gibberd AJ, Evangelou M, Nelson JDB, The time-varying dependency patterns of NetFlow statistics, IEEE International Conference on Data Mining Workshop Proceedings, IEEE
Evangelou M, Adams NM, 2016, Predictability of NetFlow data, 14th IEEE International Conference on Intelligence and Security Informatics - Cybersecurity and Big Data (IEEE ISI), IEEE, Pages:67-72
Larsen E, Truong T, Evangelou M, 2016, Exploring GenexEnvironment Interactions through Pathway Analysis, Annual Meeting of the International-Genetic-Epidemiology-Society, WILEY-BLACKWELL, Pages:648-649, ISSN:0741-0395