Joakim Beck is a Research Scientist at Professor Raul F. Tempone's Stochastic Numerics Research Group (STOCHNUM) at King Abdullah University of Science and Technology (KAUST). Joakim obtained an MSc (Eng.) in Engineering Physics at the Royal Institute of Technology [KTH] in Stockholm, Sweden, and completed a Ph.D. in Engineering at University College London (UCL), England. He held a position as a Research Associate from April 2013-2016, joint between the Department of Statistical Science and the Institute of Risk and Disaster Reduction at UCL. He worked as a Postdoctoral Fellow at Stochastic Numerics Research Group (STOCHNUM) at the Computer, Electrical and Mathematical Sciences & Engineering (CEMSE) Division at KAUST, and a member of the KAUST SRI Center for Uncertainty Quantification in Computer Science and Engineering.

Selected Publications

• Beck, J., Liu, Y., von Schwerin, E. and Tempone, R. Goal-oriented adaptive finite element multilevel Monte Carlo with convergence rates, Computer Methods in Applied Mechanics and Engineering, Article No. 115582, In Press, 2022
• Salmanidou, D.M., Beck, J. and Guillas, S. Probabilistic, high-resolution tsunami predictions in North Cascadia by exploiting sequential design for efficient emulation, Natural Hazards and Earth System Sciences, Vol. 21, No. 12, 3789--3807 , 2021 
• Beck, J., Dia, B.M., Espath, L. and Tempone, R. Multilevel Double Loop Monte Carlo and Stochastic Collocation Methods with Importance Sampling for Bayesian Optimal Experimental Design, International Journal for Numerical Methods in Engineering, Vol. 121, No. 15, 3482-2503, 2020
• Beck,J., Tamellini, L. and Tempone, R. IGA-based Multi-Index Stochastic Collocation for random PDEs on arbitrary domains, Computer Methods in Applied Mathematics and Engineering, Vol. 351, 330-350, 2019
• Beck, J., Wolfers, S. and Roberts, G.P. Bayesian earthquake dating and seismic hazard assessment using chlorine-36 measurements (BED v1), Geoscientific Model Development, Vol. 11, No. 11, 4383-4397, 2018
• Beck, J., Dia, B.M., Espath, L., Long, Q. and Tempone, R. Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain, Computer Methods in Applied Mechanics and Engineering, Vol. 334, 523-553, 2018
• Beck, J. and Guillas, S. Sequential Design with Mutual Information for Computer Experiments (MICE): Emulation of a Tsunami Model, SIAM/ASA Journal on Uncertainty Quantification, Vol. 4, No. 1, 739-766, 2016
• Beck, J., Friedrich, D., Fraga, E.S. and Brandani, S. Multi-Objective Optimisation using Surrogate Models for the Design of VPSA systems, Computers & Chemical Engineering, Vol. 82, 318-329, 2015
• Beck, J., Nobile, F., Tamellini, L. and Tempone, R. A quasi-optimal sparse grids procedure for groundwater flows. In Spectral and High Order Methods for Partial Differential Equations. Springer International Publishing, pp. 1-16, 2014
• Brown, S., Beck, J., Mahgerefteh, H. and Fraga, E.S. Global sensitivity analysis of the impact of impurities on CO2 pipeline failure. Reliability Engineering & System Safety, 115, pp. 43-54, 2013
• Beck, J., Tempone, R., Nobile, F. and Tamellini, L. On the optimal polynomial approximation of stochastic PDEs by Galerkin and collocation methods. Mathematical Models and Methods in Applied Sciences, 22(09), 2012
• Beck, J., Nobile, F., Tamellini, L. and Tempone, R. Stochastic spectral Galerkin and collocation methods for PDEs with random coefficients: a numerical comparison, in Spectral and High Order Methods for Partial Differential Equations, Editors Hesthaven, J.S., and Ronquist, E.M., Vol. 76 of Lecture Notes in Computational Science and Engineering, pp. 43–62. Springer, 2011.

Awards and Distinctions

• EPSRC Ph.D. Scholarship Award, 2009-2014.
• EPSRC NCSML Award for PDRA Collaboration, May 2015.

Education Profile

• Ph.D. in Chemical Engineering, University College London, UK (2014).
• M.Sc. (Eng.) in Engineering Physics, Royal Institute of Technology, Stockholm, Sweden (2009).