Adrián Pérez-Suay obtained his B.Sc. degree in Mathematics (2007), Master degree in Advanced Computing and Intelligent Systems (2010) and the Ph.D. degree in Computational Mathematics and Computer Science (2015), all from the Universitat de València (UV). He was "profesor asociado" (spanish university level) from 2015 to 2019 in the Department of Mathematics and the Department of Mathematics Education, both at UV. Since 2019, he is a full time assistant professor at the Department of Mathematics Education in the Universitat de València. He has a total of 8 years of university teaching experience and more than 1,500 hours taught in official degrees in the area of Education, directed 6 master thesis and participated in 6 teaching innovation projects related to Mathematics Education (PI in 3 of them). His main research interests are on the application of Artificial Intelligence techniques to Mathematics Education and their study during the teaching-learning procedure. He is currently a Postdoctoral Researcher at the Image Processing Laboratory working on Fair learning, dependence estimation, kernel methods, causal inference and Machine Learning for remote sensing data analysis. He had published more than 20 journal articles in first and second quartile indexed at the Journal Citation Reports (JCR). He has published more than 50 international conference articles indexed at the CORE Rankings Portal. He has a 6-year (2012‐2018) stretch of research activity recognized by the national Spanish agency for Quality Assessment and Accreditation (ANECA). He holds an h-index of 10 according to google scholar, h-index of 9 in ResearchGate, and h-index of 8 according to Scopus. Among the most relevant and related merits, we can highlight the following, sorted by type and date: Publications: ------------------------------ Zhu Li, Adrián Pérez-Suay, Gustau Camps-Valls, Dino Sejdinovic. "Kernel dependence regularizers and Gaussian processes with applications to algorithmic fairness". Pattern Recognition 132, (2022). https://doi.org/10.1016/j.patcog.2022.108922 (Q1 JCR, Artificial Intelligence, 2022) Steven Van Vaerenbergh, Adrián Pérez-Suay. (2022). "A Classification of Artificial Intelligence Systems for Mathematics Education". In: Richard, P.R., Vélez, M.P., Van Vaerenbergh, S. (eds) Mathematics Education in the Age of Artificial Intelligence. Mathematics Education in the Digital Era, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-030-86909-0_5 (Book chapter, Springer 2022, 1st quartile SPI) Jordi Cortés-Andrés, Gustau Camps-Valls, Sebastian Sippel, Enikő Székely, Dino Sejdinovic, Emiliano Diaz, Adrián Pérez-Suay, Zhu Li, Miguel Mahecha and Markus Reichstein. "Physics-aware nonparametric regression models for Earth data analysis". Published 4 May 2022 by IOP Publishing Ltd Environmental Research Letters, Volume 17, Number 5. https://dx.doi.org/10.1088/1748-9326/ac6762 (Q1 JCR, Environmental Sciences, 2021. IF: 6.947) Adrián Pérez-Suay, Gustau Camps-Valls. "Sensitivity maps of the Hilbert-Schmidt independence criterion". Applied Soft Computing 70: 1054-1063 (2018). https://doi.org/10.1016/j.asoc.2017.04.024 (Q1 JCR, Artificial Intelligence, 2018) Steven Van Vaerenbergh, Adrián Pérez-Suay. (2022). "Intelligent Learning Management Systems: Overview and Application in Mathematics Education". In F. Almaraz-Menéndez, A. Maz-Machado, C. López-Esteban, & C. Almaraz-López (Eds.), Strategy, Policy, Practice, and Governance for AI in Higher Education Institutions (pp. 206-232). IGI Global. https://doi.org/10.4018/978-1-7998-9247-2.ch009 (Book Chapter, 1st quartile SPI) Adrián Pérez-Suay, Valero Laparra, Gonzalo Mateo-Garcia, Jordi Muñoz-Marí, Luis Gómez-Chova, Gustau Camps-Valls. "Fair Kernel Learning". ECML/PKDD (1) 2017: 339-355 https://doi.org/10.1007/978-3-319-71249-9_21 (Conference: CORE A, in CORE Rankings Portal) Adrián Pérez-Suay, Francesc J. Ferri, Miguel Arevalillo-Herráez. "Passive-aggressive online distance metric learning and extensions". Progress on Artificial Intelligence 2(1): 85-96 (2013) Research projects: ---------------------------- 2021-2023 (AICO/2021/019). Identificación de patrones de diferencias entre género en situaciones de enseñanza y aprendizaje de la resolución de problemas verbales aritmético-algebriacos mediante sistemas tutoriales inteligentes. Subvenciones para Grupos de investigación Consolidados - Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital de la Generalitat Valenciana. PIs: Arevalillo-Herráez, M. & Arnau, D. DEEPCLOUD: Deep learning tools for operational cloud detecteion in Earth observation satellite images. Spanish Ministry of Science, Innovation and Universities (MCIU/AEI/FEDER, UE), PID2019-109026RB-I00, L. Gomez-Chova, 2020-2024 SCALE: Causal inference in the human-biosphere coupled system (SCALE). Fundación BBVA, G. Camps-Valls, 2020-2022 SEDAL: Statistical Learning for Earth Observation Data Analysis. ERC Consolidator Grant, G. Camps-Valls, 01/09/15 - 31/08/20 Study on pattern recognition based cloud detection over landmarks. EUMETSAT European Organisation for the Exploitation of Meteorological Satellites, 01/15 - 11/15 Multimodal Interaction in Pattern Recognition and Computer Vision (MIPRCV). CONSOLIDER-INGENIO 2010 (CSD2007-00018). From 10/12/2007 to 9/12/2012 (4,500,000 €). IP: Enrique Vidal Ruiz.