Josué Pagán obtained his doctorate in Computer Science from the Complutense University of Madrid in 2018 with honors ‘cum laude’ and extraordinary doctorate award. His work focuses on the development of robust methodologies for information acquisition, modeling, simulation and optimization in biophysical scenarios. He has worked on the development of models for early crisis prediction and classification of neurological and oncological diseases. In 2016 he worked as visiting researcher at the Embedded Pervasive Systems Lab at Washington State University and in the Pattern Recognition Lab at the Friedrich Alexander Universität in 2015. He obtained the Telecommunications Engineering degree from the Polytechnic University of Madrid in 2013 with honors. He also obtained a degree in Tech. Eng. in Telecom. Esp. Image y Sound from the Public University of Navarra in 2010.
He is proactive in the field of technology transfer, and founder of a start-up. His teaching is focused on HW-SW systems for IoT. He is member of the Quality Committee of the Health Research Institute of Madrid Hospitals, and he has participated as a member of the program committee of international congresses.
Ana Gago-Veiga, Josué Pagán, Kevin Henares, Patricia Heredia, Nuria González-Garc\’ıa, Mar\’ıa-Irene De Orbe, Jose Ayala, Mónica Sobrado, and Jose Vivancos. To what extent are patients with migraine able to predict attacks? Journal of Pain Research, Volume 11:2083–2094, sep 2018. URL: https://doi.org/10.2147%2Fjpr.s175602, doi:10.2147/jpr.s175602.
J. Pagan, R. Fallahzadeh, M. Pedram, J. L. Risco-Martin, J. M. Moya, J. L. Ayala, and H. Ghasemzadeh. Toward ultra-low-power remote health monitoring: an optimal and adaptive compressed sensing framework for activity recognition. IEEE Transactions on Mobile Computing, ():1–1, 2018. doi:10.1109/TMC.2018.2843373.
J. Pagán, M. Zapater, and J.L. Ayala. Power transmission and workload balancing policies in ehealth mobile cloud computing scenarios. Future Generation Computer Systems, 2016.
Josué Pagán, M. Irene De Orbe, Ana Gago, Mónica Sobrado, José L. Risco-Martín, J. Vivancos Mora, José M. Moya, and José L. Ayala. Robust and accurate modeling approaches for migraine per-patient prediction from ambulatory data. Sensors, 15(7):15419, 2015. URL: http://www.mdpi.com/1424-8220/15/7/15419, doi:10.3390/s150715419.
J. Pagan, R. Fallahzadeh, H. Ghasemzadeh, J.M. Moya, J.L. Risco-Martin, and J.L. Ayala. An optimal approach for low-power migraine prediction models in the state-of-the-art wireless monitoring devices. Proceedings of the 2017 Design, Automation and Test in Europe, DATE 2017, pages 1297–1302, 2017.
R. Fallahzadeh, J. P. Ortiz, and H. Ghasemzadeh. Adaptive compressed sensing at the fingertip of internet-of-things sensors: an ultra-low power activity recognition. In Design, Automation Test in Europe Conference Exhibition (DATE), 2017, 996–1001. March 2017. doi:10.23919/DATE.2017.7927136.
Josué Pagán, José L Risco-Martín, José M Moya, and José L Ayala. Grammatical evolutionary techniques for prompt migraine prediction. In Proceedings of the Genetic and Evolutionary Computation Conference 2016, 973–980. 2016.
M.D. Santambrogio, J.L. Ayala, S. Campanoni, R. Cattaneo, G.C. Durelli, M. Ferroni, A. Nacci, J. Pagan, M. Zapater, and M. Vallejo. Power-awareness and smart-resource management in embedded computing systems. 2015 International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS 2015, pages 94–103, 2015.
Kevin Henares, Josué Pagán, José L. Ayala, and José L. Risco-Mart\’ın. Advanced migraine prediction hardware system. In Proceedings of the 50th Computer Simulation Conference, SummerSim ’18, 7:1–7:12. San Diego, CA, USA, 2018. Society for Computer Simulation International. URL: http://dl.acm.org/citation.cfm?id=3275382.3275389.
Josué Pagán, José M. Moya, José L. Risco-Mart\’ın, and José L. Ayala. Advanced migraine prediction simulation system. In Proceedings of the Summer Simulation Multi-Conference, SummerSim ’17, 24:1–24:12. San Diego, CA, USA, 2017. Society for Computer Simulation International. URL: http://dl.acm.org/citation.cfm?id=3140065.3140089.
Josué Pagán, José L. Risco-Mart\’ın, José M. Moya, and José L. Ayala. A Real-Time Framework for a DEVS-based Migraine Prediction Simulator System. In XI Congreso Español de Metaheur\’ısticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2016). sep 2016. URL: https://www.researchgate.net/publication/305318506\_A\_Real-Time\_Framework\_for\_a\_DEVS-based\_Migraine\_Prediction\_Simulator\_System.