Industrial Mathematics, interpreted broadly, is mathematics driven by real applications, ranging from the more traditional manufacturing sector to the modern financial industry. The faculty members at York are firmly imbedded in the international community of industrial mathematics and deeply involved in many ongoing activities and research projects. It is strongly linked to mathematical finance, mathematical biology, optimization and scientific computing, but not restricted to these research areas. Many members had and have MITACS industry research projects in financial mathematics, disease modeling, medical imaging, and crystal growth. There is also a strong connection with the ongoing Industrial Problem Solving Workshops held at the Fields Institute regularly and the Springer open-access ejournal: Mathematics-in-Industrial Case Studies.
FACULTY: Chen, Huang, Liang, Salisbury, Wu and Zhu
Using tools drawn from the theories of partial differential equations, stochastic calculus, and probability, Mathematical Finance is the study of derivative pricing, risk management, and optimal decision making in finance. The field took off in the 1970s with the famous Black-Scholes-Merton formula, and now underpins much of international finance. York’s financial mathematicians work on a variety of topics, covering both theory and applications. They have strong connections to colleagues in the Schulich School of Business, to research partners in the financial sector, and to York’s actuarial program. They also support York’s Diploma in Financial Engineering, through which many York students have gone on to careers in quantitative finance.
FACULTY: Huang, Ku, Kuznetsov, Salisbury
Mathematical Biology and Disease Modeling: York’s disease modellers form the centre node of the national Centre for Disease Modelling, with collaborations and ties to public health agencies, government, immunologists, virologists, epidemiologists, pharmaceutical developers and global health initiatives. The collective goal is to understand the effects of infectious disease within host, between hosts and in populations, including the effects of drug therapies, vaccines, social behaviour, climate, insect control, and many others. Research is conducted using a diverse set of tools, including dynamical systems, stability analysis, statistical inference, probability theory, computer simulations, and agent-based models.