Björn Engquist

    The 2015 ICIAM Pioneer Prize is awarded to Björn Engquist (The University of Texas at Austin, USA). Björn Engquist received his PhD from Uppsala University in1975. He has been Professor of Mathematics at UCLA, and the Michael Henry Stater University Professor of Mathematics and Applied and Computational Mathematics at Princeton University. He was Director of the Research Institute for Industrial Applications of Scientific Computing and of the Centre for Parallel Computers at the Royal Institute of Technology, Stockholm. Currently he is Professor of Mathematics and Computational and Applied Mathematics at the University of Texas at Austin.

    Björn Engquist has made fundamental contributions in the field of applied mathematics, numerical analysis and scientific computing which have had long lasting impact in the field as well as successful applications in science, engineering and industry. Some of his most important pioneering contributions include seminal work on absorbing boundary conditions (ABC), first proposed by Engquist and Majda, for numerical computation of wave propagation. These boundary conditions can be used at the boundary of the computational domain to reduce the artificial reflection of waves effectively. Owing to its simplicity and effciency, it has been one of the most successful and widely used numerical techniques in the past 30 years and has had significant impact in practical applications such as geophysics, seismology and petroleum industry.

    In a second direction, Engquist, with his collaborators, is responsible for the development and analysis of shock capturing methods for nonlinear hyperbolic conservation laws, including the well-known essentially non-oscillatory (ENO) method. These numerical methods have been widely used in computational fluid dynamics, aerospace engineering, combustion and other applications.

    For the past twenty years, Engquist has been a leader in the field of multi-scale modeling and analysis, where his contributions include numerical homogenization, and the heterogeneous multi-scale method (HMM), among other results.

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