UPR 2151 LMA - Mathematics Laboratory

Activities

The Laboratoire de Mathématiques d'Avignon (formerly the Laboratoire d'Analyse non linéaire et Géométrie) was created in 1989 from two research groups in convex analysis and geometry. It is recognized as a Young Team, then as a Host Team and gathers all the mathematicians of the University of Avignon. In 2009 the laboratory opened up to a third research group: statistics.

It currently has nineteen permanent teacher-researchers divided into three teams: optimisation, geometry and dynamic systems, and statistics.

Its main aim is to bring together and support researchers active in the research themes of these three teams, to encourage national and international collaborations and to promote the reception of doctoral students.

On the Internet http://math.univ-avignon.fr/

Direction
Céline Lacaux

Deputy Director
Philippe Bolle

Research activities

The research themes of this laboratory are articulated around three main axes:

• non-linear analysis and optimisation to deal in particular with various applications (localisation, multi-product transport networks, medical imaging, etc.);
• Dynamical systems and differential geometry which allow the study of different problems from physics (celestial mechanics, general relativity...);
• Statistics: with a focus on process statistics (functional estimation, spatial statistics, spatiotemporal point processes, etc.) and its applications (forecasting, rupture detection, spatial econometrics, epidemiology, precision agriculture, etc.).

Partnerships

Research Federation of Mathematics Units of Aix-Marseille (FR2291 of CNRS)

Further information

Skills and know-how

• Solving complex problems involving variational methods, evolutionary equations and statistical methods.
• Modelling and solution of optimisation problems related to multi-criteria decision making.
• Statistical modelling, forecasting and risk calculation.
• Popularisation of mathematical concepts, contribution to the advancement of research in fundamental and applied mathematics at international level.
• Mastery of scientific computing methods in the field of optimisation.
• Processing of real data. Development of R packages.