I am currently work as an Associate Professor at the Department of Mathematics, University of Oslo. My main research interests are numerical analysis of stochastic differential equations, nonlinear filtering and Monte Carlo methods. For further details, here is my CV.

• Hoel, Håkon A. (2007). A numerical scheme using multi-shockpeakons to compute solutions of the Degasperis-Procesi equation. Electron. J. Differential Equations, No. 100, 22 pp. (electronic).

• Hoel, Håkon, Erik von Schwerin, Anders Szepessy, and Raúl Tempone (2012). Adaptive multilevel Monte Carlo simulation”. In: Numerical analysis of multiscale computations. Vol. 82. Lect. Notes Comput. Sci. Eng. Springer, Heidelberg, pp.217–234.


• Bayer, Christian, Håkon Hoel, Erik von Schwerin, and Raúl Tempone (2014). On nonasymptotic optimal stopping criteria in Monte Carlo simulations. SIAM J. Sci. Comput. 36(2), A869–A885.


• Hoel, Håkon and Henrik Nyberg (2014). An Extension of Clarke’s Model With Stochastic Amplitude Flip Processes. IEEE Transactions on Communications 62(7), 2378–2389.


• Hoel, Håkon, Erik von Schwerin, Anders Szepessy, and Raúl Tempone (2014). Implementation and analysis of an adaptive multilevel Monte Carlo algorithm. Monte Carlo Methods Appl. 20(1), 1–41.


• Bayer, Christian, Håkon Hoel, Ashraful Kadir, Petr Plecháč, Mattias Sandberg, and Anders Szepessy (2015). Computational error estimates for Born-Oppenheimer molecular dynamics with nearly crossing potential surfaces. Appl. Math. Res. Express. AMRX (2), 329–417.



• Hall, Eric Joseph, Håkon Hoel, Mattias Sandberg, Anders Szepessy, and Raúl Tempone (2016). Computable Error Estimates for Finite Element Approximations of Elliptic Partial Differential Equations with Rough Stochastic Data. SIAM Journal on Scientific Computing 38(6), A3773–A3807.


• Hoel, Håkon, Juho Häppölä, and Raúl Tempone (2016). Construction of a Mean Square Error Adaptive Euler–Maruyama Method With Applications in Multilevel Monte Carlo. In: Monte Carlo and Quasi-Monte Carlo Methods: MCQMC, Leuven, Belgium, April 2014. Cham: Springer International Publishing, pp. 29– 86.


• Hoel, Håkon, Kody J. H. Law, and Raul Tempone (2016). Multilevel ensemble Kalman filtering. SIAM J. Numer. Anal. 54(3), 1813–1839.


• Hoel, Håkon, Kenneth H. Karlsen, Nils H. Risebro, and Erlend B. Storrøsten (2018). Path-dependent convex conservation laws. Journal of Differential Equations 265(6), 2708–2744.


• Hoel, Håkon, Kenneth Hvistendahl Karlsen, Nils Henrik Risebro, and Erlend Briseid Storrøsten (2020). Numerical methods for conservation laws with rough flux. Stochastics and Partial Differential Equations: Analysis and Computations, 1–76. Click here for a post-print.


• Hoel, Håkon and Sebastian Krumscheid (2019). Central limit theorems for multilevel Monte Carlo methods. J. Complexity 54, 101407, 16. Click here for a post-print.


• Hoel, Håkon and Anders Szepessy (2020). Classical Langevin dynamics derived from quantum mechanics. Discrete & Continuous Dynamical Systems-B 22, no. 11 (2017): 0. Click here for a preprint.


• Chernov, A., H. Hoel, K. J. H. Law, F. Nobile, and R. Tempone (2020) Multilevel ensemble Kalman filtering for spatio-temporal processes. Accepted for publication in Numerische Mathematik.


• Hoel, Håkon, Gaukhar Shaimerdenova, and Raul Tempone (2020). Multilevel Ensemble Kalman Filtering with local-level Kalman gains. Accepted for publication in Foundations of Data Science (currently published online).

• Hoel, Håkon (2006). Constructible DP solutions. MSc thesis. Univeristy of Oslo.


• Hoel, Håkon (2012). Complexity and Error Analysis of Numerical Methods for Wireless Channels, SDE, Random Variables and Quantum Mechanics. PhD thesis. KTH, Royal Institute of Technology.