Tuesday 31 March 2020, 6-8pm
The Mathematics Society at Queen Mary is hosting its annual conference for students interested in learning more about the power of Maths. The event will take place on 31 March from 6-8pm in our new School of Mathematical Sciences building.
The conference aims to demonstrate the depths and variety there is to mathematics, inspiring young minds to learn about both the simplicity and complexity of mathematics, and how it can be used for almost everything.
The event will include talks from three of our renowned academics, focussing on different areas of mathematics, outside of the National and University curriculum. Refreshments and food will be provided.
|18:00 - 18:30||Registration and Refreshments|
|18:30 - 18:35||Welcome||
|18:35 - 19:00||Talk One - Can Mathematics deal with real people?||
Dr Wolfram Just, Reader in Applied Mathematics
|19:00 - 19:25||Talk Two - The Knapsack Problem and Computational Complexity||
Dr Justin Ward, Lecturer in Optimisation/Operations Research
|19:25 - 19:50||
Talk Three - Space filling curves, nowhere smooth curves and other curiosities
|Dr Huy Nguyen, Lecturer in Mathematics|
|19:50 - 20:00||Concluding Remarks||Mathematics Society|
Can Mathematics deal with real people? (Dr Wolfram Just)
Normally one thinks mathematics is about equations. There is some truth in that, but actually mathematics is more about structure (and less about numbers). Even more importantly, the real mathematical discoveries have surprising impact on daily life. Here we will just outline one example which shows how mathematics can contribute to the understanding of crowd control, pedestrians motion, and the occurrence of congestion in traffic. And that is finally (and literally) a matter of life and death.
The Knapsack Problem and Computational Complexity (Dr Justin Ward)
In this talk, I will discuss the classical “Knapsack Problem,” which requires selecting the most valuable items to pack into a knapsack of limited capacity. We will see that the problem is relatively easy to solve if the items can be divided into pieces, but hard if they cannot. Along the way, I will introduce some of the fundamental concepts and connections underlying the theory of computational complexity, which gives us a formal way to distinguish between easy and hard problems.