School of Mathematical Sciences, Shenzhen University

Liyuan Scholar Colloquium No. 143

Lecture Title: Stochastic Modelling and Applications

Lecturer: Professor Mao Xuerong (University of Strathclyde, UK)

Lecture Time: October 11, 2025, 10:40-11:40 a.m.

Venue: Classroom No.1, Huixing Building, Yuehai Campus, Shenzhen University

Abstract:

One of the important problems in many branches of science and industry, e.g., pandemic, ecology, biology, engineering, ffnance, social science, is the speciffcation of the stochastic process governing the behaviour of an underlying quantity. We here use the term underlying quantity to describe any interested object whose value is known at present but is liable to change in the future. In this talk, we will explain how the ordinary differential equations (ODEs) are not enough to model the underlying stochastic quantity and why stochastic differential equations (SDEs) appear naturally. Several well-known SDE models will be presented including the Nobel prize winning model in ffnance, stochastic SIS epidemic model, stochastic Lotka-Volterra model. We will then show how SDE models differ signiffcantly from ODE models and highlight how we can make use of noise in various applications including stochastic stabilisation, volatility effect in ffnance, population explosion suppressed by noise, extinction of infected individuals by noise in epidemic.

Lecturer's Biography:

Mao Xuerong is a Professor in the Department of Mathematics and Statistics at the University of Strathclyde, UK, a Fellow of the Royal Society of Edinburgh (also known as the Royal Society of Scotland), and a recipient of the Wolfson Research Merit Award (UK). He is an internationally renowned expert in the field of stochastic stability and stochastic control, having made outstanding contributions and earned a high reputation in this area. Prof. Mao specializes in stochastic analysis and numerical computation of stochastic systems. He has proposed a series of distinctive methods and techniques for handling stochastic systems, which are widely adopted. For instance, he established a scientific theory for noise stabilization, which is highly recognized by subsequent researchers; he made prominent contributions to the theory of stochastic population/epidemic models; he conducted pioneering work on LaSalle's principle for stochastic systems; and he laid the foundation for research on the theory of stochastic jump systems. Currently, he is committed to advancing the theoretical research and numerical computation of superlinear stochastic systems, a field characterized by high difficulty and strong challenges.

Faculty and students are welcome to attend!

School of Mathematical Sciences

September 19, 2025