Study of mathematical models and methods (from both the theoretical and the numerical point of view) with applications to econophysics, biomedicine, statistics, data science and image processing. At the end of the course it is expected that the student has the ability to construct, develop and implement mathematical models for the applied sciences and to analyze their limits and applicability.
Variational methods for image processing: theory and applications.
Optimization methods in data analysis and machine learning, applications to statistics and biomedicine.
Mathematical models and methods for biology and econophysics.
|J. Murray||Mathematical Biology||Springer||2002||0-387-95223-3|
In order to successfully pass the exam the student is expected to be able to mathematically describe a problem arising in different scientific disciplines, using, adapting and developing models and methods studied during the course.
The exam will consist in an in-depth study of some of the course topics, with the implementation of a numerical project (in MATLAB) and a final expository talk
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