The Einstein equations in wave coordinates are an example of a system 
which does not obey the "null condition". This leads to many 
difficulties, most famously when attempting to prove global existence, 
otherwise known as the "nonlinear stability of Minkowski space". 
Previous approaches to overcoming these problems suffer from a lack of 
generalisability - among other things, they make the a priori assumption 
that the space is approximately scale-invariant. Given the current 
interest in studying the stability of black holes and other related 
problems, removing this assumption is of great importance.

The p-weighted energy method of Dafermos and Rodnianski promises to 
overcome this difficulty by providing a flexible and robust tool to 
prove decay. However, so far it has mainly been used to treat linear 
equations. In this talk I will explain how to modify this method so that 
it can be applied to nonlinear systems which only obey the "weak null 
condition" - a large class of systems that includes, as a special case, 
the Einstein equations. This involves combining the p-weighted energy 
method with many of the geometric methods originally used by 
Christodoulou and Klainerman. Among other things, this allows us to 
enlarge the class of wave equations which are known to admit small-data 
global solutions, it gives a new proof of the stability of Minkowski 
space, and it also yields detailed asymptotics. In particular, in some 
situations we can understand the geometric origin of the slow decay 
towards null infinity exhibited by some of these systems: it is due to 
the formation of "shocks at infinity".

Social surveys are widely used in today's society as a method for obtaining opinions and other information from large groups of people. The questions in social surveys are usually presented in either multiple-choice or free-response formats. Despite their advantages, free-response questions are employed less commonly in large-scale surveys, because in such situations, considerable effort is needed to categorise and summarise the resulting large dataset. This is the so-called coding problem. Here we propose a survey framework in which, respondents not only write down their own opinions, but also input information characterising the similarity between their individual responses and those of other respondents. This is done in much the same way as ``likes" are input in social network services. The information input in this simple procedure constitutes relational data among opinions, which we call the opinion graph. The diversity of typical opinions can be identified as a modular structure of such a graph, and the coding problem is solved through graph clustering in a statistically principled manner. We demonstrate our approach using a poll on the 2016 US presidential election and a survey given to graduates of a particular university.

Stochastic control problems are closely related to free boundary problems, where both the underlying fully nonlinear PDEs and the boundaries separating the action and waiting regions are integral parts of the problems. In this talk, we will propose a class of stochastic N-player games and show how the free boundary problems involve moving boundaries due to the additional game nature. We will provide explicit Nash equilibria by solving a sequence of Skorokhod problems. For the special cases of resource allocation problems, we will show how players change their strategies based on different network structures between players and resources. We will also talk about the insights from a sharing economy perspective. This talk is based on a joint work with Xin Guo (UC Berkeley) and Wenpin Tang (UCLA).

Function solutions to linear PDEs often carry rigidity properties directly associated to the equation they satsify. However, the realm of solutions covers a much larger sets of solutions. For instance, we can speak of measure solutions, as opposed to classical $C^\infty$ functions or even $L^p$ functions. It is only logical to expect that the “better” space the solution lives in, the more rigid its properties will be.

Measure solutions lie just at a comfortable half of this threshold: it is a sufficently large space which allows for a rich range of new structures; but is sufficiently rigid to preserve a meaningful geometrical pattern. For example, have you ever wondered how gradients look like in the space of measures? What about other PDE structures? In this talk I will discuss these general questions, a few examples of them, and a new theoretical approach to its understanding via PDE theory, harmonic analysis, and geometric measure theory methods.

In Formula 1 engineers strive to produce the fastest car possible for their drivers. A lap simulation provides an objective evaluation of the performance of the car and the subsequent lap time achieved. Using this information, engineers aim to test new car concepts, determine performance limitations or compromises, and identify the sensitivity of performance to car setup parameters.

The latest state of the art lap simulation techniques use optimal control approaches. Optimisation methods are employed to derive the optimal control inputs of the car that achieve the fastest lap time within the constraints of the system. The resulting state trajectories define the complete behaviour of the car. Such approaches aim to create more robust, realistic and powerful simulation output compared to traditional methods.

In this talk we discuss our latest work in this area. A dynamic vehicle model is used within a free-trajectory solver based on direct optimal control methods. We discuss the reasons behind our design choices, our progress to date, and the issues we have faced during development. Further, we look at the short and long term aims of our project and how we wish to develop our mathematical methods in the future.

We study the small Deborah number limit of the Doi-Onsager equation for the dynamics of nematic liquid crystals. This is a Smoluchowski-type equation that characterizes the evolution of a number density function, depending upon both particle position and its orientation vector, which lies on the unit sphere. We prove that, in the low temperature regime, when the Deborah number tends to zero, the family of solutions with rough initial data near local equilibria will converge to a local equilibrium distribution prescribed by a weak solution of the harmonic map heat flow into the sphere. This flow is a special case of the gradient flow to the Oseen-Frank energy functional for nematic liquid crystals and the existence of its global weak solution was first obtained by Y.M Chen, using Ginzburg-Landau approximation.  The key ingredient of our result is to show the strong compactness of the family of number density functions and the proof relies on the strong compactness of the corresponding second moment (or the Q-tensor), a spectral decomposition of the linearized operator near the limiting local equilibrium distribution, as well as the energy dissipation estimates.  This is a joint work with Wei Wang in Zhejiang university.