A central research challenge for the mathematical sciences in the 21st century is the development of principled methodologies for the seamless integration of (often vast) data sets with (often sophisticated) mathematical models. Such data sets are becoming routinely available in almost all areas of engineering, science and technology, whilst mathematical models describing phenomena of interest are often built on decades, or even centuries, of human knowledge creation. Ignoring either the data or the models is clearly unwise and so the issue of combining them is of paramount importance. In this talk we will give a historical perspective on the subject, highlight some of the current research directions that it leads to, and describe some of the underlying mathematical frameworks begin deployed and developed. The ideas will be illustrated by problems arising in the geophysical, biomedical and social sciences.
Professor Stuart’s work within applied and computational mathematics has focused on the numerical analysis of dynamical systems, applications of stochasitic ordinary and partial differences, Bayesian inverse problems and data assimilation.
Professor Stuart has won numerous awards including the 1989 Leslie Fox Prize for Numerical Analysis, the Monroe H. Martin Prize from IPST Maryland, the SIAM James Wilkinson Prize and Germund Dahlquist Prize in 1997, the Whitehead Prize from the London Mathematical Society in 2000, and the J.D. Crawford Prize in 2007. [1] He has been an invited speaker at the International Council for Industrial and Applied Mathematics (ICIAM) in Zurich, 2007, and at the International Congress of Mathematicians (ICM) in Seoul, 2014.
Further information about Professor Stuart’s research can be found here. The departmental colloquium webpage can be accessed here.