Research teams
Mathematics, Statistics and Modelling
MSM
- Head
- To be appointed
- Staff
- membership being entered
The MSM team answers the question: what is the model, and what can legitimately be concluded from it?
Overview
Mathematical modelling of complex phenomena and quantitative analysis of the data that describe them.
Research topics
M1 — Modelling and simulation of porous media
Flow and transport in porous and fractured media, reactive transport, multiphysics coupling, multi-scale approaches, two-phase flow, biofilm growth, underground hydrogen storage.
Methods: partial differential equations, lattice Boltzmann methods, finite volumes, finite elements, homogenisation.
M2 — Mathematical analysis and dynamical systems
Functional analysis, Laplacian-type systems, elliptic and parabolic problems, existence and uniqueness, stability analysis. Compartmental models of infectious disease spread, of SEIR and SEIJR type, and evaluation of intervention and vaccination strategies.
M3 — Optimisation and operations research
Continuous, combinatorial and multi-criteria optimisation, mathematical programming, planning and scheduling, resource allocation, transport and routing problems, optimal control, metaheuristics, multi-criteria decision support.
M4 — Statistics and uncertainty quantification
Applied and spatial statistics, inference, experimental and survey design, time series, sensitivity analysis, uncertainty propagation, calibration and validation of numerical models.
Contribution to the thematic axes
| Axis | Team's work |
|---|---|
| ERN | Pollutant transport in groundwater and surface water, reactive transport, environmental spatial statistics, hydrogen storage |
| SPE | Compartmental models, stability analysis, biostatistics, evaluation of intervention strategies |
| GIOSI | Optimisation of production and supply chains, scheduling, port optimisation, reliability, process control |
Skills and tools
Fortran, Python, MATLAB, R, OpenFOAM, optimisation solvers, scientific computing.
Work carried out with the IIA team
Parallelisation and scaling of simulation codes; machine learning applied to accelerating numerical models; processing pipelines for calibration data.
Members
The team's membership will be shown as soon as members have been assigned to it in the researcher area.
Contact
For any question about the team, write to contact@umr-ames.mr