Heidelberg short course 

title
Goal-oriented adaptivity for PDEs with random data

lecturer
David Silvester
https://personalpages.manchester.ac.uk/staff/david.silvester/

logistics
four-day course (10 hours in total)
2 x 50 minute lectures + 1 x 50 minute computer lab session
on first three days, 1 x 50 minute wrap-up lecture on final day

outline of lectures
day 1 (Motivation)
 I.  Review of FEM error estimation and adaptivity for elliptic PDEs
II.  Adaptive timestepping for parabolic PDES

day 2 (Spatial adaptivity)
 I. Error reduction estimates; marking strategies; proof of convergence
II. Goal-oriented adaptivity; dual problems; numerical experiments

day 3 (Parametric enhancement)
 I. Stochastic Galerkin approximation; solver ingredients
II. Combining spatial and parametric adaptivity; numerical experiments

day 4 (Extensions)
 I. Solutions to exercises; open issues; lessons learned

tutorial classes
Students will need to have access to a computer or laptop
with MATLAB or Octave installed. The exercises will be based on 
the T-IFISS software package which can be downloaded from
http://www.manchester.ac.uk/ifiss/tifiss.html