About Håkon A. Hoel Håkon A. Hoel Visiting Researcher, Stochastic Numerics Research Group numerical analysis Mathematical modeling data assimilation Håkon Hoel was a visiting researcher in the Stochastic Numerics Group at KAUST. He holds an MSc degree in Computational Science from the University of Oslo (2016) and a Ph.D. in Numerical Analysis from KTH Royal Institute of Technology (2012). His main research interests are numerical analysis of stochastic differential equations, nonlinear filtering, and multilevel Monte Carlo (MLMC) methods. His research interests also include different aspects of implementation and error estimation of stochastic models in the following areas: adaptive weak approximation of stochastic differential equations Projects Related Projects 2015 Multilevel ensemble Kalman filtering Thu, Jan 1 - Mon, Jun 1 2015 Kalman filter Filtering is a method for sequentially estimating the state of an evolving dynamical system in settings where only partial and possibly inaccurate measurements of the history of the state are available. 2011 Adaptive Multi Level Monte Carlo (MLMC) Wed, Jun 1 2011 - Fri, Nov 1 2013 stochastic differential equations Stochastic differential equations (SDEs), both ordinary time-dependent equations and partial differential equations with random coefficients, are common mathematical tools to model natural processes with uncertainty.
Multilevel ensemble Kalman filtering Thu, Jan 1 - Mon, Jun 1 2015 Kalman filter Filtering is a method for sequentially estimating the state of an evolving dynamical system in settings where only partial and possibly inaccurate measurements of the history of the state are available.
Adaptive Multi Level Monte Carlo (MLMC) Wed, Jun 1 2011 - Fri, Nov 1 2013 stochastic differential equations Stochastic differential equations (SDEs), both ordinary time-dependent equations and partial differential equations with random coefficients, are common mathematical tools to model natural processes with uncertainty.
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