The JAMS is a weekly seminar with talks given by junior researchers on a topic in all areas in Mathematics. It is a great opportunity to share research, get feedback from other students and to become more confident in presenting work. We also provide drinks and snacks!
This year, there are two different types of talks:
Classic JAMS: Short talks, somewhat specialised and more focused on new results. A great opportunity to get know what fellow PhD students’ research is about.
Introductory JAMS: Longer talks, but more accessible and educational. These are meant to introduce you to the basic ideas of active research fields, and give you a broader picture of modern Applied Mathematics.
If you are interested in giving a talk (of either type) or have further questions, please email us at email@example.com. You can also sign up to our Mailing List to receive regular updates on these events!
Venue: Huxley 130
Time: Wednesday 4pm-5pm
(02/10/19)Where has all my sand gone?: Advanced numerical and statistical techniques to assess erosion risk in the coastal zone
An estimated 250 million people live in areas less than 5m above average sea level. As sea levels rise and storms increase in strength and frequency due to climate change, the coastal zone is becoming an ever more critical location for the application of advanced mathematical techniques. There is also a high degree of uncertainty associated with these models. By considering the case study of beach erosion, I will show how statistical methods can be used in conjunction with numerical models to quantify uncertainty. In particular, I will focus on the relatively new method of Multilevel Monte Carlo.
(02/10/19)Mean field games and knowledge spillovers
In this talk I will present an introduction to mean field games (MFGs) as a limit of stochastic differential games as the number of players goes to infinity. I will explain the notion of an equilibrium and discuss the PDE description of such an equilibrium.
In the second half of this talk I will develop an MFG model of innovation that we can use to evaluate the size of knowledge spillovers.
To view past seminars check here