Department of Mathematical Sciences
Finn Lindgren


4 West 5.15

Dept of Mathematical Sciences


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Finn Lindgren


My research interests are in stochastic modelling and computational methods for spatial process data.

Enviromental applications, such as climate science, pollution monitoring, and ecology, involve data measured with random measurement variability at irregular points in space and time. This necessitates the use of statistical models and methods to quantify the uncertainty about the underlying spatial and spatio-temporal processes, for example historical global temperatures. In my research, I am interested both in methods for modelling these processes as structured random quantities, and in computationally efficient methods for estimation of model parameters, spatial reconstruction, and temporal prediction based on incomplete but large data sets. A important aspect is development of general software, allowing applied scientists to apply these methods to their own problems. This requires combining methods and techniques from several branches of the mathematical sciences, in particular probability theory for stochastic processes, Bayesian statistics, and numerical analysis.


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