Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Mathematics - Enrollment from 2025/2026The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
| Modules | Credits | TAF | SSD |
|---|
| Modules | Credits | TAF | SSD |
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| Modules | Credits | TAF | SSD |
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1 module between the following1 module between the following 3 modules among the followingLegend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Mathematical Modelling in the Applied Sciences (seminar course) (2020/2021)
Teaching code
4S008271
Teacher
Coordinator
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
MAT/05 - MATHEMATICAL ANALYSIS
Period
I semestre dal Oct 1, 2020 al Jan 29, 2021.
Learning outcomes
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.
Program
The entire course will be available online. In addition, a number of the lessons/all the lessons (see the course
schedule) will be held in-class.
Mathematical models and methods in biology, medicine and econophysics.
Variational methods for material science and image processing: theory and applications.
Optimization and learning methods in data analysis, applications to statistics and biomedicine.
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| DISPENSE | Dispense fornite dal docente | 2015 | |||
| J. Murray | Mathematical Biology | Springer | 2002 | 0-387-95223-3 |
Examination Methods
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
