Adam Andersson

  • Visiting Researcher, Applied Mathematics and Statistics, Mathematical Sciences

My current research topic conserns the use of deep learning to obtain accelerated and scalable algorithms for computationally challenging problems. More precisely, I work on deep learning for non-linear filtering, optimal control, Bayesian statistics, solving PDE and radar signal processing. In my previous research I worked on stochastic differential equations, in particular numerical analysis, solution theory and Malliavin calculus for stochastic partial differential equations. When I define new research topics I try to find synergies with my old research field. My primary employment is at Saab.