Joakim Beck

February 2024

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  StochNum Alumni Joakim Beck

  1 min read · Mon, Feb 12 2024

  News

  Alumni Dr. Joakim Beck served in our Stochastic Numerics group at KAUST from 2016 to January 2024, first as a Postdoctoral Fellow and later as a Research Scientist. He has recently accepted a faculty position at the Center for Integrative Petroleum Research (CIPR) at King Fahd University of Petroleum and Minerals (KFUPM), and started in February 2024. With a solid background in chemical engineering, stochastics, uncertainty quantification, numerical methods, and statistical science, Dr. Beck is well-equipped to contribute to CIPR's research initiatives. His expertise is expected to support the

August 2023

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  Research Scientist Erik von Schwerin participation at ADMOS 2023 Conference in Gothenburg, Sweden

  1 min read · Wed, Aug 23 2023

  News

  Erik von Schwerin participated in the conference ADMOS 2023 with a talk based on the paper Goal-Oriented Adaptive Finite Element Multilevel Monte Carlo with Convergence Rates. This 11th iteration of the ADMOS conferences was held in Gothenburg, Sweden, on 19-21 June 2023. It attracted a strong international group of researchers and practitioners in adaptive modeling and simulation. Abstract: In this study, we present an adaptive multilevel Monte Carlo (AMLMC) algorithm for approximating deterministic, real-valued, bounded linear functionals that depend on the solution of a linear elliptic PDE

August 2022

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  Ph.D. student Yang Liu attended WCCM-APCOM 2022

  1 min read · Sat, Aug 6 2022

  News

  Ph.D. student Yang Liu attended the WCCM-APCOM Yokohama 2022 and presented the work Goal-oriented adaptive MLMC method for elliptic random PDEs by Joakim Beck, Yang Liu, Erik von Schwerin, and Prof. Raul Tempone. Abstract: Multilevel Monte Carlo methods (MLMC) can dramatically reduce the computational cost of Monte Carlo simulations where each sample is computed using a discretization based numerical method, for example, when computing the expected value of a quantity of interest (QoI) depending on the solution to a partial differential equation with stochastic data. Goal-oriented adaptive
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  Post-Doc André Carlon participation at MCQMC2022 in Linz

  1 min read · Mon, Aug 1 2022

  News

  bayesian inference Stochastic Methods and Algorithms

  Between July 17 to 22 of 2022, the 15th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing was held in Linz, Austria. A postdoctoral fellow of our group, André Carlon, presented a joint work with Joakim Beck and Prof. Raúl Tempone named "Adaptive stochastic gradient descent for Bayesian optimal experimental design." Abstract: Experiments play a central role in many fields of science. Usually, it is of the interest of the investigators to perform experiments as efficiently as possible. However, finding the optimal design for an experiment can be a

July 2022

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  Manuscript accepted in Computer Methods in Applied Mechanics and Engineering

  1 min read · Wed, Jul 27 2022

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  The manuscript entitled “ Goal-Oriented Adaptive Finite Element Multilevel Monte Carlo with Convergence Rates” written by Joakim Beck, Yang Liu, Erik von Schwerin, and Prof. Raul Tempone, is accepted in Computer Methods in Applied Mechanics and Engineering, “A Special Issue in Honor of the Lifetime Achievements of J. Tinsley Oden”. Abstract: In this study, we present an adaptive multilevel Monte Carlo (AMLMC) algorithm for approximating deterministic, real-valued, bounded linear functionals that depend on the solution of a linear elliptic PDE with a lognormal diffusivity coefficient and

June 2022

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  Ph.D. student Yang Liu attended ECCOMAS Congress 2022 in Oslo

  1 min read · Mon, Jun 13 2022

  News

  Ph.D. Student Yang Liu attended the ECCOMAS Congress 2022 from June 5 – June 9, 2022, in Oslo, Norway. He presented the work “ Goal-Oriented Adaptive Finite Element Multilevel Monte Carlo with Convergence Rates”, written by Joakim Beck, Yang Liu, Erik von Schwerin, and Prof. Raul Tempone.

December 2019

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  Multilevel Monte Carlo Acceleration of Seismic Wave Propagation under Uncertainty

  1 min read · Sun, Dec 8 2019

  News

  Seismic Wave Propagation Multilevel Monte Carlo

  We interpret uncertainty in a model for seismic wave propagation by treating the model parameters as random variables and apply the Multilevel Monte Carlo method to reduce the cost of approximating expected values of selected, physically relevant, quantities of interest (QoI) with respect to the random variables.

March 2017

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  Prof. Raul Tempone will be doing research collaboration with Dr. Abdul-Lateef Haji-Ali and Dr. Joakim Beck at the Mathematical Institute

  1 min read · Thu, Mar 23 2017

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  Prof. Raul Tempone will be doing research collaboration with Dr. Abdul-Lateef Haji-Ali and Dr. Joakim Beck at the Mathematical Institute, University of Oxford, UK, March 23 - 26, 2017.
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  Dr. Joakim Beck will visit and give a seminar talk at NADA Department, KTH Royal Institute of Technology

  1 min read · Fri, Mar 10 2017

  News

  Dr. Joakim Beck will visit and give a seminar talk at NADA Department, KTH Royal Institute of Technology, and KAUST Student exchange program talk, Karolinska Institute - Stockholm, Sweden, March 10 - 19, 2017.

February 2017

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  Alexander Litvinenko, Sören Wolfers, and Joakim Beck to present their work at the 7th Workshop on High-Dimensional Approximation

  1 min read · Mon, Feb 13 2017

  News

  Alexander Litvinenko, Sören Wolfers, and Joakim Beck will present their work at the 7th Workshop on High-Dimensional Approximation, February 13 – 17, 2017, The University of New South Wales, Sydney, Australia.

May 2016

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  Welcome New Postdoctoral Fellow: Dr. Joakim Beck

  1 min read · Sun, May 15 2016

  News

  Joakim Beck has joined as a Post Doctoral Fellow the Stochastic Numerics Group and SRI Uncertainty Quantification Center at KAUST. Joakim is an applied mathematician specializing in computational science and uncertainty quantification.