The main objective of this area is to develop and apply models able to predict the behavior of systems in science and engineering.
- Parallel processing of models of systems in science and engineering.
- Numerical methods of partial differential equations.
- Specific applications for modelling oil deposits for their efficient explotation and flow and transport modelling of underground water.
- Category theory with applications to languages, programming, and data. Multilevel systems, multigraph. Information systems. Petri nets.
- Scientific computing with Matematica, Maple, for automating deduction for computing differential forms (differential equations as exterior, ideal, and Cartan systems), in areas such as physics and engineering. Symbolic computing.
- Quantic computing, quantic algoritms.
- Multivalued fuzzy logic, rough sets, evidence theory, confidence theory, posibility theory.
- Algorithmic problems of algebra theory and integer number theory.
- Symbolic computing for associative algebras and Lie algebras.
- Quantifications of Lie algebras and their applications in quantic group theory with computational methods.
- Theory of Galois for associative algebras with computational methods.
- Free algebras ant their automorphisms with computational methods.
- Ring theory with computational methods.
- Computational models and algorithms for fractal structure generation.
- Computational model of the bi-color DLA.
- Computational models in natural science.
- Computational algorithms and multi-thread programming in Windows and Linux.
- Advanced programming in C++ and its application implementing computational algorithms.
- Scientific visualization with C++ Builder, OpenGL and other computer packages.
¤ Masters and Doctoral