Team of University of A Coruña

Oscar Fontenla Romero (PhD) is a Full Professor at the University of A Coruña (Spain) and a researcher at the CITIC Research Center. His research career has been primarily devoted to the development of novel machine learning and data mining methodologies, as well as to their application in a wide range of domains, with particular emphasis on engineering and biomedicine. These research activities have led to the publication of 45 articles in international peer-reviewed journals, 90 papers in scientific conference proceedings, and 10 book chapters. He has participated in 25 competitively funded research projects awarded through public calls, including three projects funded by European Union programs (the Seventh Framework Programme and Horizon 2020), as well as projects financed by prominent industrial partners. He has served as principal investigator in nine of these projects. Furthermore, he has co-supervised seven doctoral dissertations in the field of Artificial Intelligence. In addition to his research contributions, he has been actively involved in the evaluation and peer-review of scientific publications for international conferences and for several journals indexed in the Journal Citation Reports (JCR), including IEEE Transactions on Neural Networks, Information Sciences, Neurocomputing, IEEE Transactions on Biomedical Engineering, Artificial Intelligence in Medicine, Neural Processing Letters, and Soft Computing, among others.

Amparo Alonso Betanzos is a Full Professor in  Computer Science and Artificial Intelligence at CITIC-University of A Coruña (UDC), where she coordinates the LIDIA group (Artificial Intelligence R&D Laboratory). Her research lines are the development of Scalable Machine Learning models, Reliable and Explainable Artificial Intelligence, and Green and Frugal AI, among others. She has published more than 200 articles in journals, international conferences, books, and book chapters, participating in more than 30 competitive European, national and local research projects.   She was formerly President of the Spanish Association of Artificial Intelligence (2013-21). She is a Senior Member of IEEE and ACM. She has participated as a member of the Working Group which collaborated in drafting the Spanish R&D&I Strategy in Artificial Intelligence in 2018, and  a member of CAIA, the Advisory Council on Artificial Intelligence of the Ministry of Digital Transformation and Public Function of the Government of Spain, since 2020, as well as a Member of the Spanish Research Ethics Committee of the Ministry of Science, Innovation and Universities of the Government of Spain, since 2023. She is also Member of the Advisory Board of the Chair on Artificial Intelligence and Democracy.Since October 2023, she has been a corresponding member of the Royal Spanish Academy of Exact, Physical, and Natural Sciences.

Bertha Guijarro-Berdiñas received the Ph.D. in Computer Science in 1998 from University of A Coruña (Spain). She is currently Tenure Professor at the Faculty of Informatics of this University and member of its Laboratory of R&D in Artificial Intelligence (LIDIA-UDC) and the Center for Research in Information and Communication Technologies (CITIC- http://citic-research.org/). Her main research interests are in both applied and theoretical aspects of machine learning (large scale learning, online learning, distributed and federated learning, Frugal AI), knowledge-based systems and agent-based modeling. She has participated in more than 30 research projects funded by European, national and regional agencies, as well as in several agreements with companies; she has registered a system for fetal monitoring and diagnosis, and has co-authored more than 100 publications in books, international journals and conferences in the field of Artificial Intelligence.

Elena Hernandez-Pereira is an Associate professor in the Computer Science and Information Technology Department, at the University of A Coruña and a researcher at the CITIC Research Center. In relation to her research experience, she has focused on the development of knowledge-based systems, mainly in biomedicine. In this sense, she has developed an expert system for sleep apnea diagnosis from raw signal processing to reasoning about a diagnosis. She worked in the validation and usability of intelligent systems and in the machine learning area too. Because of these works, she has published 18 articles in international scientific journals, 16 of them indexed in the JCR and with a relevant impact index. She has also made 42 contributions to scientific congresses, most of them of an international nature and has published 2 book chapters on his research work. Likewise, she has participated in 34 research projects granted in competitive public calls and some of them funded by important companies. Two of these projects were financed in European Union programs (POCTEP and SUDOE programs) and she has been the principal investigator of them. Moreover, she has also participated in activities of evaluation and review of scientific articles for various conferences and journals, and she has supervised two doctoral theses in the field of Artificial Intelligence.

Beatriz Pérez-Sánchez received the M.S. and Ph.D. degrees in Computer Science from the University of A Coruña (UDC), Spain, in 2005 and 2010, respectively. Since 2007, she has been teaching and researching in the area of knowledge of Computer Science and Artificial Intelligence of the UDC where she is currently an Associate Professor at Computer Science and Information Technology department. Moreover, since 2020 she is the gender equality representative of Faculty of Computer Sciences (UDC). Her doctoral dissertation was focused on supervised learning methods for feedforward neural networks. In particular, she researched in new online learning algorithms that allowed their application in stationary and non stationary contexts. This dissertation received different mentions as the prize for the best scientific article of the Doctoral Consortium in the 2009 edition of the CAEPIA conference granted by Spanish Association of Artificial Inteligence (AEPIA) and the Doctorate Extraordinary Award granted by University of A Coruña. Regarding her current research interests, she is focused on theoretical aspects of machine learning such as, distributed, online and scalable learning as well as their application in various fields, such as engieneering and biomedine. As a result of her research, she has published different articles in international scientific journals all of them indexed in the JCR, several contributions to scientific conferences, most of them of an international nature and indexed in the CORE ranking, and different book chapters. In relation to the research experience, she has participated in several research projects funded throught competitive public calls European, national or regional agencies as well as different agreements with relevant companies such as PRISA Digital or INDRA Sistemas. She has also participated as reviewer of scientific articles for various conferences and different journals indexed in the JCR such as Artificial Intelligence Review and IEEE Transactions on Neural Networks and Learning Systems.

Noelia Sánchez Maroño received her M.Sc. and Ph.D. degrees in Computer Science from the University of A Coruña (UDC), Spain, where she is currently a tenured Associate Professor in the Department of Computer Science and Information Technology and member of the Laboratory for R&D in Artificial Intelligence (LIDIA). Building on her doctoral work in dimensionality reduction for neural and functional networks, her research spans methodological developments in high-dimensional data analysis, including feature selection, with broad interdisciplinary applications. She has also contributed to agent-based modeling within European research projects funded by FP7 and H2020, aimed at supporting policies for a more sustainable Europe. She has authored 25 papers in international journals, more than 50 conference papers, and several book chapters. She has participated in 25 competitively funded research projects at European, national, and regional levels, as well as in industry-funded R&D contracts.

Laura Morán-Fernández holds a degree in Computer Engineering and a PhD in Computing from the University of A Coruña. She has been a member of the LIDIA research group (Laboratory for Research and Development in Artificial Intelligence) since 2015. During her predoctoral stage, she completed two research stays at the University of Manchester. She defended her doctoral thesis in July 2020, entitled “Simple but not simplistic: reducing the complexity of machine learning methods,” which received the distinction of Cum Laude and International Mention. In 2021, she was awarded the Frances Allen Prize by the Spanish Association for Artificial Intelligence (AEPIA). She is currently an Assistant Professor at the University of A Coruña and Deputy Director of the UDC-Inditex Chair in Green AI Algorithms. Her research focuses on feature selection, machine learning, and sustainable AI, with particular emphasis on reducing the complexity and improving the efficiency of intelligent systems. She has published more than fifteen articles in international JCR-indexed journals, co-authored five book chapters, and presented numerous peer-reviewed contributions at national and international conferences. In addition, she has participated in more than twenty research projects, contracts, and collaborative networks related to AI.

Brais Cancela Barizo (PhD) is a postdoctoral researcher at the University of A Coruña (Spain) and a member of the LIDIA (Laboratory for Research and Development in Artificial Intelligence) research group. He obtained his B.S. and Ph.D. degrees in Computer Science from the University of A Coruña, where his doctoral dissertation received the Doctorate Extraordinary Award. His research has focused on the development of advanced machine learning and deep learning methodologies, particularly in the areas of computer vision, pattern recognition, and explainable artificial intelligence. Throughout his career, he has combined academic and applied research experience, contributing to international collaborations and participating in competitive research projects funded by public institutions and industry. His work has resulted in publications in leading international journals and conferences in Artificial Intelligence and Computer Vision, as well as contributions to book chapters. He is currently the Principal Investigator for a project titled "Ethic Deep Learning," which aims to develop novel Deep Learning architectures with a focus on explainability and low energy consumption while maintaining state-of-the-art performance.

Alejandro Dopico-Castro received his B.Sc. in Computer Science (2023) and his M.Sc. in Artificial Intelligence (2025) in Universidade da Coruña, Spain. He is currently pursuing his Ph.D. in Computer Science under the direction of Prof. Óscar Fontenla-Romero and Prof. Bertha Guijarro-Berdiñas. His thesis revolves around research into Frugal and Sustainable AI, an area that encompasses fields of Machine Learning such as Continuous Learning and Federated Learning.