The research in the Scientific Computing section is related to numerical algorithms and scientific computing, with emphasis on analysis, development and implementation of algorithms for engineering applications (modelling, simulation, design, data analysis, etc) on modern computer architectures. Currently the research focuses on numerical methods related to optimization, dynamical simulation, differential equations, geoscience, inverse problems, and high-performance computing.
Optimization. This research focuses on algorithms for solving optimization problems in engineering design, parameter estimation and data analysis, as well as algorithms for advanced control systems.
Dynamical Simulation. This work involves design of efficient and accurate methods for modelling, simulation, and analysis of nonlinear dynamical systems.
Computational Geoscience. This research focuses on models and computational methods for simultaneous analysis of data from several different sources. Of particular interest is nonlinear inverse problems with complex a priori information.
Inversion Algorithms. The focus here is on the development and implementation of regularization algorithms for large-scale inverse problems in, eg, tomography and acoustics.
Scientific Computing. This research involves the interplay between modeling, algorithm development, and implementation on modern computer architectures.