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).

Honors and Awards

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

Kaust Affiliations

  • Computer, Electrical and Mathematical Sciences & Engineering Division (CEMSE).​​
  • Stochastic Numerics Research Group (STOCHNUM).
  • SRI Center for Uncertainty Quantification in Computer Science and Engineering (SRI).

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., Nobile, F., Tamellini, L. and Tempone, R., 2014. A quasi-optimal sparse grids procedure for groundwater flows. In Spectral and High Order Methods for Partial Differential Equations-ICOSAHOM 2012 (pp. 1-16). Springer International Publishing. 
  • J. Beck, F. Nobile, L. Tamellini, R. Tempone, Convergence of quasi-optimal stochastic Galerkin methods for a class of PDEs with random coefficients, Computers & Mathematics with Applications. Volume 67, Issue 4, March 2014, Pages 732–751.
  • Brown, S., Beck, J., Mahgerefteh, H. and Fraga, E.S., 2013. Global sensitivity analysis of the impact of impurities on CO 2 pipeline failure. Reliability Engineering & System Safety, 115, pp.43-54.
  • Beck, J., Tempone, R., Nobile, F. and Tamellini, L., 2012. On the optimal polynomial approximation of stochastic PDEs by Galerkin and collocation methods. Mathematical Models and Methods in Applied Sciences, 22(09), p.1250023.
  • 2011, Stochastic spectral Galerkin and collocation methods for PDEs with random coefficients: a numerical comparison. In Spectral and High Order Methods for Partial Differential Equations (pp. 43-62). Springer Berlin Heidelberg.
  • Beck, J., Nobile, F., Tamellini, L. and Tempone, R., 2011, November. Implementation of optimal Galerkin and collocation approximations of PDEs with random coefficients. In ESAIM: Proceedings (Vol. 33, pp. 10-21). EDP Sciences.