Florence Nightingale Day 2024

Wednesday 10th January, 10:00-15:00, Lancaster University, George Fox Lecture Theatre 1

The venue can be found on this MazeMap.

To sign up for a school group, teachers should complete this registration form.

For enquiries contact Dr Sean Prendiville (s.prendiville@lancaster.ac.uk).

Provisional Timetable

  • 09.30-10.00: Registration
  • 10.00-10.05: Introduction
  • 10.05-10.50: Talk 1 - Dr Vandita Patel (University of Manchester), "Fermat's Last Theorem and Beyond".
    • Pythagoras showed that for any right-angled triangle, the square of the length of the hypotenuse is equal to the sum of the squares of the lengths of the other two sides. We famously remember the formula a2 + b2 = c2, for example, 32 + 42 = 52. What happens when we consider cubes instead of squares? How about fourth powers or 37579th powers? In other words, can we find whole positive numbers that satisfy xn + yn = zn when n is at least 3? This general problem is infamously known as Fermat's Last Theorem. In this talk, we explore the fascinating* history of this problem, and of course, go beyond to explore current problems of a similar flavour.
      [*SPOILER ALERT: Fermat's Last Theorem was unresolved for over 350 years!]
  • 10.50-11.10: Refreshments
  • 11.10-12.20: Maths quiz!
  • 12.20-13.00: Lunch break
  • 13.00-13.45: Talk 2 - Ziyang Yang (Statistics & Operational Research with Industry Centre for Doctoral Training, Lancaster University), "My journey: exploring the fascinating world of statistics".
    • Have you ever thought about what makes a movie really popular at the box office? Does having more money make people happier? And how exactly do viruses spread across different places and over time? These are all projects I worked on during my undergraduate and postgraduate studies. They sparked my curiosity to explore statistics further. Now, as a PhD student, I work on detecting unusual behaviour in data streams: the challenge is to do this as quickly as possible. In this talk, we will explore these projects and I hope to show you how enjoyable statistics can be!
  • 13.45-14.00: Results of the quiz and prizes; break
  • 14.00-14.45: Talk 3 - Dr Nicola Rennie (Center for Health Informatics, Computing and Statistics, Lancaster University), "Data, technology and medicine: Using data science to improve health outcomes".
    • The world is collecting more data than ever before, and there are many ways that it can be used in healthcare and medicine to improve our health and wellbeing. Data can help us to understand what happens to our brains as we get older, provide more information for doctors diagnosing rare heart murmurs, or identify ways to make the NHS more efficient. In this talk, I'll discuss some of the research projects I've had the privilege to contribute to and showcase some of the ways we can make better use of data and technology within medicine. I'm also looking forward to sharing the process of working on these projects, and the journey I’ve taken to working in data science.
  • 14.45-15.00: Closing comments, thank you gifts and feedback

Dr Vandita Patel

Vandita is a Lecturer in Pure Mathematics at The University of Manchester. Prior to this, she was a Neumann Research Fellow at The University of Manchester and postdoctoral researcher at the University of Toronto. She obtained her PhD in 2017 from the University of Warwick. Her research is in Number Theory, where she uses a mixture of classical and modern techniques to find integer solutions to certain algebraic equations.

Dr Vandita Patel
Ziyang Yang

Ziyang Yang

Ziyang Yang is currently a PhD student at STOR-i, Lancaster University. Her research focuses on anomaly detection in the Internet of Things (IoT) in partnership with British Telecom. Prior to joining Lancaster, she completed her postgraduate studies in Statistics at the University of Southampton and obtained an undergraduate degree in Economics and Statistics from China.

Dr Nicola Rennie

Nicola Rennie is a Lecturer in Health Data Science, based in the Centre for Health Informatics, Computing and Statistics at Lancaster Medical School. Nicola's research interests lie in applications of statistics and machine learning to health-related data, with a particular interest in neurology, cardiology, and cystic fibrosis. Nicola also has experience of working outside of academia, in data science consultancy, where she gained experience in a range of fields including epidemiology, public health, and manufacturing.

Dr Nicola Rennie