Du är inte inloggad på KTH så innehållet är inte anpassat efter dina val.
This course gives an insight into some current research area or some practical activity where methods of Scientific Computing have an important function. The course is designed individually depending on the prerequisites of the student and the teachers who are available at the school. It is the responsibility of the student to find an available supervisor and propose a project.
Sample projects from previous years
FSI Simulation of Arterial Stenoses (Fangkai Yang)
Computational Fluid Dynamics, Finite Element Methods
Application of Multirate Partitioned Runge–Kutta method in neuron modeling (Aleksei Iupinov)
Computational Biology, Ordinary Differential Equations
Discontinuous Galerkin FE and the incompressible Navier-Stokes equations (Lena Leitenmaier, Lorenz Hufnagel)
Computational Fluid Dynamics, Finite Element Methods
Numerical Differentiation of Sampled Data (Nathan Brack)
Methods for ill-posed problems, Cell biology
A study of internal pipe flows and the internal carotid artery (Emirhan Ilhan, Parikshit Upadhyaya)
Computational Fluid Dynamics, Computational Biology, Finite Element Methods
Hermite-Fourier spectral method for Vlasov-Poisson systems (Alexander Stramma)
Plasma Physics, Spectral Methods
Trajectory and parameter estimation using Sequential Monte Carlo methods and Expectation Maximizatio (Xavier Svensson Depraetere, Markus Meder)
Stochastic Optimization, Hidden Markov Models
Wind Power Forecasting using Deep Learning (Sebastian Haglund El Gaidi, Nicolas Roussel, Sebastian Bujwi)
Deep Learning, Green Energy
Comparison of BPA and Neuroevolution for Time Series Prediction (Prabhanjan Mutalik)
Neural networks, genetic algorithms
Modeling Framework to predict antibody glycan profile in a cell culture (Prem Anand Alathur Srinivasan, André Scheir Johansson)
Systems Biology, Ordinary Differential Equations
Simulation of Lithium-Ion Batteries with the Finite Element Method (Bernd Schwarzenbacher)
Computational Electrodynamics, Finite Element Methods
Wind Power Forecasting and the EEM17 competition (Sebastian Haglund El Gaidi, Nicolas Roussel, Sebastian Bujwid)
Deep Learning, Green Energy
Queuing Theory Project (Rémi Lacombe)
Queuing Theory, Markov processes
The project is carried out individually or within a group of 2 persons. There are weekly meetings with the project supervisor scheduled individually. The outcome of the project is a poster and a lecture at a final workshop.
The examination consists of
evaluation of the poster;
presentaion and discussion at a workshop.