Mathematical modeling is the art of interpreting issues from an application territory or a real- world problem into tractable mathematical formulations whose theoretical and numerical analyses provide understanding, clarifications and useful guidance for the original application. Learning about mathematical modeling is a significant advance from a hypothetical scientific preparing to an application-situated numerical skill, and makes the student fit for acing the difficulties of our innovative technological culture. Our team use several classification criteria for mathematical models according to their structure: Linear vs. Nonlinear, Explicit vs. Implicit, Discrete vs. Continuous, Deterministic vs. Stochastics. We focus on these areas, while collaborating with academics in local and foreign Universities.

Latest publications

1. Chandani Dissanayake, Lourdes Juan, Kevin R. Long, Angela Peace, Md Masud Rana, “Genotypic Selection in Spatially Heterogeneous Producer-Grazer Systems Subject to Stoichiometric Constraints”, Bulletin of Mathematical Biology, 2019 (https://doi.org/10.1007/s11538-018-00559-9).