Department of Information Technology

Ken Mattsson

senior lecturer at Department of Information Technology, Division of Scientific Computing

Email:
ken.mattsson[AT-sign]it.uu.se
Telephone:
+4618-471 2975
Mobile phone:
+46 73 6171953
Visiting address:
Room POL 2307 ITC, Lägerhyddsv. 2, hus 2
752 37 UPPSALA
Postal address:
Box 337
751 05 UPPSALA

Short presentation

I am an associate professor in scientific computing (numerical analysis) with focus on efficient and reliable numerical methods for time-dependent partial differential equations. Application’s where this is of importance is found in for example quantum mechanics, geoscience and fluid mechanics.

Keywords: högre ordningens finita differens metoder randvillkor för pde numerisk vågutbredning numerisk kvantmekanik numerisk optimering

Also available at

My courses

Biography

Born in  Stockholm and moved to Uppsala 1992 to study chemistry at Uppsala University. I have M.Sc in astronomy (1996) and finished my Ph.D in scientific computing 2003. My main interest (in science) since 1997 is on efficient finite difference methods for time-dependent PDE. I have previously been employed at Stanford University, Vattenfall and FOI.

In my spare time I like skiing (alpine) or spend time in nature. I have a big interest in food (both making it and eating it) and like to watch science fiction or science programs. 

Research

My research has mainly focused on higher order finite difference methods for time-dependent partial differential equations (PDE), in particular with the influence of wave-propagation. The typical applications where these methods have been employed are (but not restricted to): CFD, Quantum Mechanics, Geophysics, in collaboration with scientist from Uppsala University, Stanford University and NASA.  

An recent project together with researchers from Stanford University is on the development on reliable numerical models concerning infrasound from active volcanoes.  Another project concerns advanced models in computational quantum mechanics. Another recent focus is on numerical methods for PDE constrained optimization (such as inverse problems)

Publications

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Updated  2016-06-10 20:08:12 by Ken Mattsson.