Biography:
Sara Lumbreras is a professor at the ICAI School of Engineering of the Universidad Pontificia Comillas. She is currently deputy director of Research Results at the Technological Research Institute and manages the chair of Science, Tecnology and Religion together with Jaime Tatay. She is the author of more than fifty academic publications and has directed or participated in more than twenty projects with private companies and public institutions. Her research focuses on the development and application of decision support techniques to complex problems. She works with classical optimization techniques such as Benders decomposition, heuristics and Artificial Intelligence. It operates in the energy sector (mainly in network design), in the health sector and in finance. She also has five years of experience in the private sector (JPMorgan London). She develops a line of research in philosophy of technology and the implications of artificial intelligence in anthropology. She is a Global Shaper of the World Economic Forum and a Marshall Memorial Fellow.
Areas of interest:
Decision methods applied to complex problems.
---Tecniques:--- decision under uncertainty, stochastic optimization, Benders’ decomposition, risk analysis, heuristics, metaheuristics, genetic algorithms, ordinal optimization.
---Areas of application:--- power systems, planning, network design, transmission expansion planning, wind energy, offshore windfarm design, finance, risk analysis, derivatives.
Experience:
Transmission Expansion Planning, Transmission Expansion Planning at a European level, Wind Energy, Offshore Wind, Corporate finance, Financial derivatives, Algorithmic trading, Sustainable Finance, Transhumanism, Predictive models in healthcare
Skills:
Optimization, Classical optimization, Stochastic Optimization, Benders Decomposition, Metaheuristics, Genetic Algorithms, Ordinal Optimization, Machine Learning, Interpretable Machine Learning, GAMS, Matlab, French (basic)
Current research interests:
Optimization applied to complex problems, Predictive modeling in healthcare, Interpretable Machine Learning, Humility in Science and Responsbile Science, Exploiting the structure of problems for more efficient and interpretable solutions.
Laviña, E., Lumbreras, S., Bravo, L., Soriano, Joan B., Izquierdo, Jose L., RG-Moro, J.M., Alpha-1 antitrypsin gene variants in patients without severe deficiency diagnosed with pulmonary emphysema on chest CT. International Journal of Chronic Obstructive Pulmonary Disease. Vol. 19, pp. 353 - 361, 2024. [Online: February 2024]
Lumbreras, S., Tejada, D.A., Elechiguerra, D., Explaining the solutions of the unit commitment with interpretable machine learning. International Journal of Electrical Power & Energy Systems. Vol. 160, pp. 110106-1 - 110106-13, September 2024. [Online: June 2024]
Santos Oliveira, D., Lumbreras, S., Álvarez, E. F., Ramos, A., Olmos, L., Model-based energy planning: a methodology to choose and combine models to support policy decisions. International Journal of Electrical Power & Energy Systems. Vol. 159, pp. 110048-1 - 110048-22, August 2024. [Online: May 2024]
Lumbreras, S., The synergies between understanding belief formation and artificial intelligence. Frontiers in Psychology. Vol. 13, pp. 868903-1 - 868903-4, 2022. [Online: April 2022]
Gomollón, F., P. Gisbert, J., Guerra, I., Plaza, R., Pajares Villarroya, R., Moreno Almazán, L., López Martín, M.C., Domínguez Antonaya, M., Vera Mendoza, M.I., Aparicio, J., Martínez, V., Tagarro, I., Fernández-Nistal, A., Lumbreras, S., Maté, C., Montoto, C., Clinical characteristics and prognostic factors for Crohn’s disease relapses using natural language processing and machine learning – a pilot study. European Journal of Gastroenterology & Hepatology. Vol. 34, nº. 4, pp. 389 - 397, April 2022. [Online: December 2021]
Izquierdo, Jose L., Soriano, Joan B., González, Y., Lumbreras, S., Ancochea, J., Echeverry, C., RG-Moro, J.M., Use of N-Acetylcysteine at high doses as oral treatment for patients hospitalized with COVID-19. Science Progress. Vol. 105, nº. 1, pp. 1 - 11, January 2022. [Online: January 2022]
Lumbreras, S., Oviedo, Ll., Angel, H.F., The missing piece in sustainability indices: accounting for the human factor. Sustainability. Vol. 13, nº. 21, pp. 11796-1 - 11796-11, November 2021. [Online: October 2021]
Ciller, P., Lumbreras, S., González-García, A., Network cost estimation for mini-grids in large-scale rural electrification planning. Energies. Vol. 14, nº. 21, pp. 7382-1 - 7382-21, November 2021. [Online: November 2021]
Vestrucci, A., Lumbreras, S., Oviedo, Ll., Can AI help us to understand belief? Sources, advances, limits, and future directions. International Journal of Interactive Multimedia and Artificial Intelligence. Vol. 7, nº. 1, pp. 24 - 33, September 2021. [Online: August 2021]
Moradi, M., Abdi, H., Lumbreras, S., Metaheuristics and transmission expansion planning: a comparative case study. Energies. Vol. 14, nº. 12, pp. 3618-1 - 3618-23, June 2021. [Online: June 2021]
Ancochea, J., Izquierdo, Jose L., Medrano, I. H., Porras, A., Serrano, M., Lumbreras, S., del Río-Bermúdez, C., Marchesseau, S., Salcedo, I., Zubizarreta, I., González, Y., Soriano, Joan B., Evidence of gender differences in the diagnosis and management of coronavirus disease 2019 patients: an analysis of electronic health records using natural language processing and machine learning. Journal of Women's Health. Vol. 30, nº. 3, pp. 393 - 404, March 2021. [Online: December 2020]
Izquierdo, Jose L., Almonacid, C., González, Y., del Río-Bermúdez, C., Ancochea, J., Cárdenas, R., Lumbreras, S., Soriano, Joan B., The Impact of COVID-19 on patients with asthma. European Respiratory Journal. Vol. 57, nº. 3, pp. 2003142-1 - 2003142-9, March 2021. [Online: March 2021]
Lumbreras, S., Inteligencia artificial y medicina. La necesidad de modelos interpretables. TECHNO REVIEW. International Technology, Science and Society Review / Revista Internacional de Tecnología, Ciencia y Sociedad. Vol. 9, nº. 2, pp. 97 - 102, January 2021. [Online: January 2021]
Espejo, R., Mestre, G., Postigo Marcos, F., Lumbreras, S., Ramos, A., Huang, T., Bompard, E., Exploiting graphlet decomposition to explain the structure of complex networks: the GHuST framework. Scientific Reports. Vol. 10, pp. 12884-1 - 12884-14, December 2020. [Online: July 2020]
Izquierdo, Jose L., Ancochea, J., Medrano, I. H., Tello, J., Porras, A., Serrano, M., Lumbreras, S., del Río-Bermúdez, C., Marchesseau, S., Salcedo, I., Martínez, A., Maté, C., Collazo, S., Barea, J., Villamayor, M., Urda, A., de la Pinta, C., Zubizarreta, I., González, Y., Menke, S., Soriano, Joan B., Clinical characteristics and prognostic factors for icu admission of patientswith covid-19: a retrospective study using machine learning and natural language processing. Journal of Medical Internet Research. Vol. 22, nº. 10, pp. e21801-1 - e21801-13, October 2020. [Online: June 2020]
Graziani, D., Soriano, Joan B., del Río-Bermúdez, C., Morena, D., Díaz, T., Castillo, M., Alonso, M., Ancochea, J., Lumbreras, S., Izquierdo, Jose L., Characteristics and prognosis of COVID-19 in patients with COPD. Journal of Clinical Medicine. Vol. 9, nº. 10, pp. 3259-1 - 3259-11, October 2020. [Online: October 2020]
Soriano, Joan B., Fernández, E., de Astorza, A., Pérez de Llano, L.A., Fernández Villar, J.A., Carnicer-Pont, D., Alcázar-Navarrete, B., García, A., Morales, A., Lobo, M., Maroto, M., Ferreras, E., Soriano, C., del Río-Bermúdez, C., Vega-Piris, L., Basagaña, X., Muncunill, J., G. Cosío, B., Lumbreras, S., Catalina, C., Alzaga, J.M., Gómez Quilón, D., Valdivia, C.A., de Lara, C., Ancochea, J., Hospital Epidemics Tracker (HEpiTracker): description and pilot study of a mobile app to track COVID-19 in hospital workers. JMIR Public Health and Surveillance. Vol. 6, nº. 3, pp. e21653-1 - e21653-13, September 2020. [Online: June 2020]
Corzo Santamaría, T., Lazcano, L., Márquez, J., Gismera, L., Lumbreras, S., A common risk factor in global credit and equity markets: An exploratory analysis of the subprime and the Sovereign-Debt crises. Heliyon. Vol. 6, nº. 6, pp. e03980-1 - e03980, June 2020. [Online: June 2020]
Ciller, P., de Cuadra, F., Lumbreras, S., Optimizing off-grid generation in large-scale electrification-planning problems: a direct-search approach. Energies. Vol. 12, nº. 24, pp. 4634-1 - 4634-22, December 2019. [Online: December 2019]
Marge, T., Lumbreras, S., Ramos, A., Hobbs, B.F., Integrated offshore wind farm design: optimizing micro-siting and cable layout simultaneously. Wind Energy. Vol. 22, nº. 12, pp. 1684 - 1698, December 2019. [Online: September 2019]
Lumbreras, S., Wogrin, S., Navarro, G., Bertazzi, I., Pereda, M., A decentralized solution for transmission expansion planning: getting inspiration from nature. Energies. Vol. 12, nº. 23, pp. 4427-1 - 4427-16, December 2019. [Online: November 2019]
Lumbreras, S., Commodification separated us from nature, from each other and from ourselves. Can technology bring us back together?. Pensamiento: Revista de Investigación e Información Filosófica. Vol. 75, nº. 283 S. Esp nº 9, pp. 375 - 385, April 2019. [Online: April 2019]
Gorenstein Dedecca, J., Lumbreras, S., Ramos, A., Hakvoort, R.A. , Herder, P. M., Expansion planning of the North Sea offshore grid: simulation of integrated governance constraints. Energy Economics. Vol. 72, pp. 376 - 392, May 2018. [Online: April 2018]
Correa-Posada, C.M., Sánchez, P., Lumbreras, S., Security-constrained model for integrated power and natural-gas system. Journal of Modern Power Systems and Clean Energy. Vol. 5, nº. 3, pp. 326 - 336, May 2017. [Online: April 2017]
Lumbreras, S., The limits of machine ethics. Religions. Vol. 8, nº. 5, pp. 100-1 - 100-10, May 2017. [Online: May 2017]
Lumbreras, S., Moreno Barrado, A., Latorre, J.M., Impact of information and communication technologies on human cognitive processes. Implications for human nature. Pensamiento: Revista de Investigación e Información Filosófica. Vol. 71, nº. 269 S. Esp nº 7, pp. 1375 - 1382, December 2015.
Pache, C., Maeght, J., Seguinot, B., Zani, A., Lumbreras, S., Ramos, A., Agapoff, S., Warland, L., Rouco, L., Panciatici, P., New methodology for long-term transmission grid planning–general description. Project: e-highway2050 / WP8-T8.3. Funded by Deutsche Energie-Agentur GmbH (dena) whitin "FP7-ENERGY". Dec/2014.