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Emma Southall

Emma graduated in 2022 with a PhD in Mathematics of Real-World Systems. Emma was supervised by Louise Dyson and Mike Tildesley. Emma's research interests include epidemiology, network science, applied dynamical systems, and statistical physics.

Emma's research included work on potential indicators of disease elimination using the theory of critical slowing down. She focused on the application of early-warning signals to epidemiological time series data, using real-time analysis of statistical indicators to inform control policies for disease elimination. In particular, she developed techniques for detrending time series data and addressed challenges of imperfect data, such as aggregated incidence data.


E. Southall, TS. Brett, MJ. Tildesley and L. Dyson. "Early warning signals of infectious disease transitions: a review." J. R. Soc. Interface. Sept 2021 (

E. Southall*, A. Holmes*, E. Hill, B. Atkins, T. Leng, R. Thompson, L. Dyson, M. Keeling, M. Tildesley. "An analysis of school absences in England during the Covid-19 pandemic". BMC Medicine, June 2021 (

MJ. Keeling, MJ. Tildesley, B Atkins, B. Penman, E. Southall, G Guyver-Fletcher, ... & L. Dyson. "The impact of school reopening on the spread of COVID-19 in England." Philosophical Transactions of the Royal Society B, May 2021 (

E. Southall, M. Tildesley and L. Dyson. "Prospects for detecting early warning signals in discrete event sequence data: application to epidemiological incidence data." PLOS Comp. Bio., Sep 2020 (

A. Gama Dessavre*, E. Southall*, M. Tildesley, and L. Dyson. "The problem of detrending when analysing potential indicators of disease elimination." Journal of Theoretical Biology, Nov 2019 ( opens in a new window)

* = authors contributed equally to the work.

Academic Activities

Work Experience and Study Groups

  • IBM Research UK, Feb-April 2020
    • 3 month internship in the Enabling Technologies Data Group, under the supervision of Dr Anne Jones. Project involved developing scalable tools for forecasting malaria in sub-Saharan Africa by integrating large datasets on climate drivers (utilising forecast products from the Weather Company, an IBM business) with simulation models. I learnt a variety of data science techniques for handling spatiotemporal data, including leveraging high-performance computing (HPC) and Big Data technology.
  • AI in Health & Care Study Group, May 2019
    • Problem solving week with academics from a variety of UK institutions. Problem presented by isardSAT, using machine learning techniques with earth observation data to predict precipitation and infer the risk of mosquito habitation. Funded by UKRI
  • Mobile App Developer, Nov-Feb 2019
    • Part-time app developer for the Green Research Group, University of Warwick. Role involved ensuring the functionality and providing technical support for users of an app which tracks and reduce lameness in sheep flocks.
  • Epirecipes, Oct 2018
    • Participated in a 3-day hackathon at the Alan Turing Institute. Developing a cookbook of epidemiological models in as many computer languages as possible. Cookbook available here: Funded by Dept. of Veterinary Medicine, Cambridge University.

Conferences and Seminars

  • Contributed Talk: "Identifying indicators of critical transitions in epidemiological data", at e-SMB 2020
  • Invited Seminar: "Early-warning signals of disease elimination: an equation-free method for monitoring the control of infectious disease", Centre of Infectious Disease Modelling, National Institute for Public Health and the Environment (Netherlands), Nov 2019
  • Invited Seminar: "Detecting signals of disease elimination in epidemiological data", Experimental Ecology & Conservation, University of Bristol, Oct 2019
  • Contributed Talk: "Detecting signals of disease elimination in epidemiological data", at IDDConf 2019
  • Contributed Talk: "Anticipating Disease Elimination", at BAMC 2019 - funded by LMS
  • Invited Talk: "Use of Transect Study Data to Inform Mathematical Models of FMD in Endemic Settings", EuFMD, Food and Agriculture Organization of the United Nations, June 2018

Previous Projects


  • 2021 - Present: TA for Epidemiology by Example (MA4M1, fourth-year maths MATLAB course).
  • 2020 - Present: TA for Analysis I (MA131, first-year maths module).
  • 2019 - Present: TA for Maths by Computer (MA124, first-year maths MATLAB (2019) and Python (2021) course).
  • 2019 - Present: Delivered an Introduction to Computing course for MSc students. Course involved setting laptops up for students; giving an overview of bash scripting, python and an introduction to HPC.
  • 2018 - Present: TA for Bifurcations, Catastrophes and Symmetries (MA3J3, third-year maths module).
  • 2018 - Present: TA for Networks and Random Processes (MA933, MSc-year complexity science module). Coding examples can be found on my GitHub.
  • 2017 - 2019: Supervisor to first year Maths-Stats Students. This involves supervising and providing feedback for 2 groups of 1st year students. Modules taught includes: Analysis, Linear Algebra, Abstract Algebra and Differential Equations.
  • 2014 - 2019: Advanced Mathematics Support Programme (AMSP) teaching assistant for STEP exams. This involves teaching a group of 20-30 sixthform students, preparing them for their STEP exam which is required by many universities to study mathematics.


2017-2018: MSc in Mathematics for Real-World Systems, University of Warwick (Distinction)
2014-2017: BSc in Mathematics, University of Warwick (First Class Honours)

Other Activities

  • Member of the Epidemiology Reading Group in the Complexity Science centre.
  • Postgraduate representative on the Mathematics Department Equality & Diversity Committee (formerly Athena Swan).
  • Postgraduate representative on the Complexity Department SSLC (student staff liaison committee).
  • Contributor to the MathSys Newsletter.
  • 2019 Women in Maths Outreach Day, University of Manchester - Presented a workshop to groups of year 10 & 12 school students showcasing research possibilities in mathematics.
  • 2018 LMS Prospects in Mathematics Meeting - contributed to the break-out session for prospective PhD students.

My non academic interests include climbing, crochet and DiY.