Teaching

Courses

The links above will lead you to the course slides in the Lecturenotes repository. Passwords and logins are provided in the first lecture.
For further information e.g. seminar paper see the German website of the work group.

Undergraduate Courses:

Graduate Courses:

Thesis Topics

I accepted and appreciate thesis topics in my field of interest like Machine Learning and Data Ming. Beyond this related topics from data visualization and mathematical are welcome.

Furthermore especially for engineering student’s topics concerning modelling and simulation are possible: among other FEM, CFD, Modelica, Model-based design and Real-time simulation.

Software used for Teaching and/or Research

  • GNU Octave or MATLAB
  • Python 3.x with
    • NumPy
    • Scipy
    • Matplotlib
    • Pandas
    • Kivy
  • Open Modelica
  • ROS (Robot Operating System)
  • C/C++

Old Courses:

Beyond this there are some old or related courses I have been involved in during the last years, e.g. as a substitute for a collgegue on research sabbatical:

  • Analysis 1 (bachelor course)
  • Lineare Algebra (bachelor course)
  • Numeric (bachelor course)