IMDEA Networks
Dr. Juan Marcos RAMIREZ
Investigador Postdoc
- PhD: Doctor en Ciencias Aplicadas - Universidad de Los Andes. Mérida, Venezuela
- MSc: Máster en Ingeniería Biomédica - Universidad de Los Andes. Mérida, Venezuela
- BSc: Ingeniero Electricista - Universidad de Los Andes. Mérida, Venezuela
- Puesto anterior: Becario postdoctoral Marie Curie del programa Got Energy Talent (GET) en la Universidad Rey Juan Carlos, Madrid.
- Fecha de incorporación: Noviembre 2021
- Website: https://juanmarcosramirez.github.io/
- Email: juan.ramirez@imdea.org
- Tel: +34 91 481 6947
Publicaciones
Middle-Output Deep Image Prior for Blind Hyperspectral and Multispectral Image Fusion
Jorge Bacca, Cristian Arcos, Juan Marcos Ramirez, Henry Arguello
Signal Processing: Image Communication. 10.1016/j.image.2024.117247. Volumen 132 , Elsevier. ISSN: 0923-5965. Marzo 2025
Performance Analysis of NSUM Estimators in Social-Network Topologies
Sergio Díaz Aranda, Jose Aguilar, Juan Marcos Ramirez, David Rabanedo, Antonio Fernández Anta, Rosa Elvira Lillo
The American Statistician. Taylor & Francis on behalf of the American Statistical Association (United States). ISSN: 0003-1305. Diciembre 2024
An In-Depth Analysis of COVID-19 Symptoms Considering the Co-Occurrence of Symptoms Using Clustering Algorithms
Diego Javier Benito, Jesús Rufino, Juan Marcos Ramirez, Antonio Fernández Anta, Jose Aguilar
IEEE Access. 10.1109/ACCESS.2024.3456246. Volumen 12 , IEEE Society. ISSN: 2169-3536. Septiembre 2024
COVID-19 seroprevalence estimation and forecasting in the USA from ensemble machine learning models using a stacking strategy
Gontzal Sagastabeitia, Josu Doncel, Jose Aguilar, Antonio Fernández Anta, Juan Marcos Ramirez
Expert Systems with Applications. 10.1016/j.eswa.2024.124930. Volumen 258 , Elsevier. ISSN: 0957-4174. Agosto 2024
A Stacking Ensemble Machine Learning Strategy for COVID-19 Seroprevalence Estimations in the USA Based on Genetic Programming
Gontzal Sagastabeitia, Josu Doncel, Antonio Fernández Anta, Jose Aguilar, Juan Marcos Ramirez
IEEE Congress on Evolutionary Computation. Yokohama, Japan. Agosto 2024