FQM201: Bifurcation theory and dynamical systems

Submitted by francisco.grimaldi on Tue, 08/25/2020 - 11:10
University
University of Cadiz
Faculty/school/department
SCIENCE FACULTY/MATHEMATICS/ APPLIED MATHEMATICS
Size of the team
number of researchers number of supporting staff number of PhD students
15
0
0
Composition of Joint Unit of Research, if relevant

Seven  doctors 3 seniors 4 juniors
The research has been focussed in mathematical models of diffusion, tumour evolution etc. The methods used  have been: Group transformations. Reductions. Conservation laws . etc

Journal papers 189
Conferences 175
Grants 75
Chapterss 72
Deva Evaluation  2017 : 20,50
.Scientific Quality
From 0 to  18: 17
 Transfer
From  0 to 3,5: 3,5

 2018-2020
34 journal papers
6 chapters
32 conferences
Grants:
 Recaida 0 PR-214  FECYT
 DIV201-002
ITI-0038-2019

PI
PI name
Mª Luz Gandarias Nuñez
PI email
marialuz.gandarias@uca.es
PI bio

ORCI ID: 0000-0001-8604-

Her research has been focussed in mathematical models of diffusion, tumour evolution etc. The methods used  have been: Group transformations. Reductions. Conservation laws . etc
She started methods such as nonclassical potential symmetries  and Weak- selfadjointness  J of Phys. A: Math  Theor. (2011) 110 cites.
 -Adviser of 6 Doctoral thesis
-5  research autonomic steps last 2005
-4 research steps last 2016.
-Index h 22 and 1831 cites in  Google academic.
-Index  h 16 in Web of Science with  155 publications  and  1031 cites.
- Scopus  among  Uca Authors with more publications    2013-2017.
Member of the editorial board of four international journals

Contact person and e-mail
Contact person
Mª Luz Gandarias Nuñez
Contact person e-mail
marialuz.gandarias@uca.es
WWW
https://fqm201.uca.es/
Short description of research profile

Group transformations:symmetries and equivalence transformations.
Conservation laws.
Nonclassical method. Potential symmetries.
Mathematical modelling of chemotherapy resistance in tumor development.
Exact solutions,Quañitative analysis.
Nonlinear waves and solitons.
Nonlocal symmetries and nonlocal related systems.
Diffusion systems: bacterial growth, tumor evolution. Other models from physics, medicine, engineering and economy.

Research area
NATURAL SCIENCES » Mathematics » (PN) MATHEMATICS, APPLIED
Scientific Themes (keywords)
Groups of transformations
Symmetries
Conservation laws
Differential equations. Mathematical models
Publications

Representative publications

1. Application of Lie point symmetries to the resolution of an interface problem in a generalized Fisher equation M Rosa, S Chulián, ML Gandarias, R Tracinà Physica D: Nonlinear Phenomena 405, 132411 (2020) Q1   (2020) Vol: 405. Pgs: 132411- 
2. Conservation laws for a generalized seventh order KdV equation MS Bruzón, A. Márquez, T. Garrido, E. Recio  R. dela Rosa Journal of Computational and Applied Mathematics
3. Conservation laws, symmetries, and exact solutions of the classical Burgers-Fisher equation in two dimensions M Rosa, JC Camacho, MS Bruzón, ML Gandarias Journal of Computational and Applied Mathematics 354, 545-550 (2019) Q1
4. Equivalence transformations and conservation laws for a generalized variable-coefficient Gardner equation R De la Rosa, ML Gandarias, MS Bruzón Communications in Nonlinear Science and Numerical Simulation Volumen 40 Páginas 71-79  (2016) 22citas
5. Weak self-adjoint differential equations ML Gandarias Journal of Physics A: Mathematical and Theoretical Volumen 44 Número 26 Páginas 262001 (2011) 110citas

Link to extended list of publication

https://fqm201.uca.es/publicaciones-en-revistas/
Technology Expertise
  • Symmetry transformation groups applied to PDEs and ODEs: reductions.
  • Generalizations: non-classical methods and potential symmetries.
  • Direct methods to obtain exact solutions.
  • Non-linear waves studies and solitons.
  • Qualitative analysis.
  • Conservation laws.
  • Non-local symmetries and non-locally-related systems.
  • Diffusion systems. Model studies.
  • Mathematical modelling of hematopoiesis and leukemia: dynamics and treatments.
  • Data analysis (clustering techniques, heterogeneity of spatially distributed data, etc.) and machine learning strategies.