Håkon Andreas Hoel

Image of Håkon Andreas Hoel
Norwegian version of this page
Email haakonah@math.uio.no
Room 904
Username
Visiting address Moltke Moes vei 35 Niels Henrik Abels hus 0851 Oslo
Postal address Postboks 1053 Blindern 0316 Oslo
Other affiliations Institutt for pedagogikk (Student)

Academic interests

My background is in numerical methods for stochastic and partial differential equations, Monte Carlo methods and data assimilation. I also like to study more computational aspects of mathematics, for instance to develop efficient and robust computational methods for solving stochastic problems.  

Education

  • 2007 – 2012: PhD student in Numerical Analysis at the Royal Institute of Technology, KTH, Stockholm, Sweden.
  • 2006: Master in Computational Science at the University of Oslo, Norway.
  • 2004: Bachelor in Computational Science at the University of Oslo, Norway.

Positions held

  • 2012 -- 2014 Postdoc in the Stochastic numerics research group at KAUST university, Thuwal, Saudi Arabia.
  • 2014 -- 2016 Postdoc at the Department of Mathematics, UiO.
  • 2016 -- 2017 Postdoc at the Department of Mathematics, EPFL. 
  • 2017 -- 2018 Guest lecturer at Chalmers and University of Gothenburg. 
  • 2019 -- 2022 Junior professor at the Department of Mathematics, RWTH Aachen.
Tags: Mathematics, Partial Differential Equations, computational mathematics, stochastic differential equations, data assimilation.

Selected publications

  • A. Chernov, H. Hoel, K. J. Law, F. Nobile, and R. Tempone. Multilevel ensemble Kalman filtering for spatio-temporal processes. Numerische Mathematik, 2021, 147(1), 71-125
  • H, Hoel, and S. Krumscheid. Central limit theorems for multilevel Monte Carlo methods. Journal of Complexity, 2019, 54, 101407.
  • H. Hoel, K. J. Law, and R. Tempone. Multilevel ensemble Kalman filtering. SIAM Journal on Numerical Analysis, 2016, 54(3), 1813-1839.
  • H. Hoel, E. von Schwerin, A. Szepessy, and R. Tempone. Implementation and Analysis of an Adaptive Multilevel Monte Carlo Algorithm. Monte Carlo Methods Appl. 2014, 20 (1):1-41.
  • C. Bayer, H. Hoel, E. von Schwerin, and R. Tempone. On nonasymptotic optimal stopping criteria in Monte Carlo simulations. SIAM Journal on Scientific Computing 2014, 36:2, A869-885.
Published Nov. 5, 2014 5:47 PM - Last modified Aug. 28, 2023 5:17 PM

Research groups