Datos de contacto

Facultad de Ciencias Económicas y Empresariales

Despacho 221-N Edificio de 1º (Prefabricado)

Tel: 91 394 29 15

Campus de Somosaguas




Dedicación Docente

   Business Statistics I (Doble Grado en Derecho-ADE)

 Horario de tutorías segundo cuatrimestre 2023-2024

   Jueves: 9:30-10:30 y 12:30 a 13:30
   Viernes: 12:30-13:30


Associate Professor (Profesora Titular) in UCM since 2023. PhD in Applied Mathematics (2011). Visiting scholar at Max Planck Institute from 2005-2006 and at Laboratorio sui Sistemi Complessi della Scuola Superiore di Catania from 2007-2008. From 2013-2014 she was senior researcher at Commissariat à l'énergie atomique et aux énergies alternatives in Paris. She has participated in many different research founded projects.



Profesora excelente periodo curso 2019/20-2220/21-2021/22


Research interests

Mathematical Modelling, Big data, Applied Mathematics, Complex Systems, Opinion Prediction. Higher Education and TIC’s.

Publications: Google Scholar, ResearchGateScopus, ORCID, Producción Científica UCM


Latest Publications

  • A. B. Kubik,  M. R. Ferrández, M. Vela-PérezB. Ivorra,  A. M. RamosModelling the COVID-19 pandemic: variants and vaccines. In Proceedings of The 8th European Congress on Computational Methods in Applied Sciences and Engineering ECCOMAS Congress 2022, 5-9 June 2022, Oslo, Norway.
  • A.M. Ramos, M.R.  Ferrández, M. Vela-Pérez, A.B.  Kubik, B. Ivorra. A simple but complex enough θ-SIR type model to be used with COVID-19 real data. Application to the case of Italy: Nonlinear Phenomena, 2021, 421, 132839.

    A.M. Ramos, M. Vela-Pérez, M.R.  Ferrández, A.B. Kubik, B. Ivorra. Modeling the impact of SARS-CoV-2 variants and vaccines on the spread of COVID-19. Communications in Nonlinear Science and Numerical Simulation 2021, 102, 105937.


    B.Ivorra, M.R. Ferrández, M. Vela-Pérez, A.M. Ramos. Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China. Communications in Nonlinear Science and Numerical Simulation, 2020, 88, 105303.

  • A. M. Ramos, M.R. Ferrández, M. Vela-Pérez, A. B. Kubik and B. Ivorra. A simple but complex enough θthetaθ-SIR type model to be used with COVID-19 real data. Application to the case of Italy. Accepted for publication in Physica D: Nonlinear Phenomena. DOI link: Research Gate Preprint, 2020. DOI link:
  • E. García-Cuesta, D. Gómez-Vergel, L. Gracia-Expósito, J. M. López-López, M. Vela-Pérez. Prediction of Opinion Keywords and Their Sentiment Strength Score Using Latent Space Learning Methods. Appl. Sci. 2020, 10(12), 4196.
  • García-Cuesta, D. Gómez-Vergel, L. Gracia-Expósito, J.M. López-López, M. Vela-Pérez. Prediction of opinion keywords and their sentiment strength score using latent space learning methods.  Applied Sciences (Switzerland), 2020, 10(12), 4196.
  • M. Bodnar, M. Vela Pérez. Mathematical and numerical analysis of low-grade gliomas model and the effects of chemotherapy. Communications in Nonlinear Science and Numerical Simulation. Volume 72, 2019, Pages 552-564.