Biography:
David Roch Dupré obtained the PhD (with International Mention) in Engineering Systems Modeling from Pontifical Comillas University (Madrid, Spain) in 2020. He also obtained the Master's Degree in Industrial Engineering (2016), the Master's Degree in Research in Engineering Systems Modeling (2016) and the Degree in Electromechanical Engineering (2014). During his doctoral studies he worked as Assistant Researcher at the Institute for Research In Technology (IIT), where he combined his research activity with teaching, giving classes in the Department of Electronic and Control Engineering of ICAI Scholl of Engineering. In 2020 he joined the Faculty of Economics and Business Administration (ICADE) as an Assistant Professor in the Department of Quantitative Methods, where he teaches Operations Research and Algebra for Business Analytics. He is also a researcher at IIT, participating in publicly and privately funded research projects.
Areas of interest:
Socioeconomic indicators. Longevity Economy. Modeling, simulation, and optimization. Energy efficiency in electrified railway systems.
Experience:
Professor David Roch Dupré, in recent years has taught the following subjects: Operations Research, Control Engineering, Dynamic Systems, Algebra, and Final Degree Projects. From the research point of view, after developing his thesis in the area of railway systems, he has started to carry out quantitative research on different socioeconomic realities, specializing in the development of indicators and applying it to realities as diverse as the Longevity Economy, labor market in Spain or vulnerability.
Skills:
Measurement methodologies. Tools for assessing decision-making. Nature-inspired optimization algorithms. Simulation.
Current research interests:
Development of socioeconomic indicators. Measurement of leadership models. Longevity Economy.
Roch Dupré, D., Aracil, E., Calvo-Báscones, P., Monitoring socioeconomic readiness for the demographic transition: Introducing the Senior Economy Tracker. Structural Change and Economic Dynamics. Vol. 71, pp. 430 - 443, December 2024. [Online: August 2024] 
JCR: 5,000 Q1 (2023) - SJR: 1,344 Q1 (2023) 
Aracil, E., Diaz-Aguiluz, E., Gomez-Bengoechea, G., Mota, R., Roch Dupré, D., Regional socioeconomic assessments with a genetic algorithm: an application on income inequality across municipalities. Social Indicators Research. Vol. 173, pp. 499 - 521, June 2024. [Online: May 2024]
JCR: 2,800 Q1 (2023) - SJR: 0,965 Q1 (2023) Portela, J., Roch Dupré, D., Figuerola-Ferretti Garrigues, I., Yéboles, C., Salazar, A., Monitoring the green transition in the power sector with the electricity generation emissions (EGE) tracker. Energy Strategy Reviews. Vol. 50, pp. 101236-1 - 101236-15, November 2023. [Online: October 2023]
JCR: 7,900 Q1 (2023); - SJR: 1,899 Q1 (2023);
JCR: 7,802 Q1 (2021); 7,500 Q1 (2023) - SJR: 1,734 Q1 (2021); 1,749 Q1 (2023) Roch Dupré, D., Camacho-Gómez, C., Cucala, A.P., Jiménez-Fernández, S., López López, A.J., Portilla-Figueras, A., Pecharromán, R.R., Fernández-Cardador, A., Salcedo-Sanz, S., Optimal location and sizing of energy storage systems in DC-electrified railway lines using a coral reefs optimization algorithm with substrate layers. Energies. Vol. 14, nº. 16, pp. 4753-1 - 4753-19, August 2021. [Online: August 2021]
JCR: 3,252 Q3 (2021); 3,000 Q3 (2023) - SJR: 0,653 Q1 (2021); 0,651 Q1 (2023) Roch Dupré, D., Gonsalves, T., Cucala, A.P., Pecharromán, R.R., López López, A.J., Fernández-Cardador, A., Determining the optimum installation of energy storage systems in railway electrical infrastructures by means of swarm and evolutionary optimization algorithms. International Journal of Electrical Power & Energy Systems. Vol. 124, pp. 106295-1 - 106295-15, January 2021. [Online: July 2020]
JCR: 5,659 Q1 (2021); 5,000 Q1 (2023) - SJR: 1,544 Q1 (2021); 1,711 Q1 (2023)
JCR: 4,630 Q1 (2020); 5,000 Q1 (2023) - SJR: 1,050 Q1 (2020); 1,711 Q1 (2023)
JCR: 4,418 Q1 (2018); 5,000 Q1 (2023) - SJR: Q1 (2018); 1,711 Q1 (2023)
JCR: 3,610 Q1 (2017); 5,000 Q1 (2023) - SJR: Q1 (2017); 1,711 Q1 (2023) 
