Biography

Fernando Boto holds a degree in Computer Engineering (2001) and a PhD in Computer Science (2006) from the University of the Basque Country (UPV-EHU). He received a pre-doctoral scholarship (2001-2005), during which he initiated his research in Pattern Recognition and Machine Learning applied to fraud detection and optical character recognition. Subsequently, he worked as a researcher on e-Health projects at Vicomtech, contributing to innovative Bioimaging projects and developing impactful applications for industry companies.
In 2010, Fernando joined Tecnalia, where he expanded his expertise in Artificial Intelligence, Machine Learning, and Metaheuristics for industrial processes. His work included condition-based monitoring in manufacturing components, the wind energy sector, the railway industry, and machining. With over 20 years of experience in R&D projects, particularly in Industry 4.0 and biomedical applications, Fernando has been involved in numerous competitively funded projects. He served as the principal investigator and held technical responsibilities in European and Spanish government funded projects such as i-Bosp, Learnform, Top-Ref, COCOP, CIRMET, and more.
Fernando's research focuses on evolutionary metaheuristic techniques, ensemble models, metamodels or gray-box models, hybrid models, signal processing, etc. He is a co-author of over 20 scientific articles presented at international conferences and published in journals. He has collaborated with various universities, including UPV/EHU, Mondragón, and DEUSTO, co-supervising master's and doctoral students. Additionally, Fernando has conducted training courses and lectures on artificial intelligence for companies and public entities. He served as a postgraduate professor at the University School of Dual Engineering of the IMH (Elgoibar).
In February 2023, Fernando joined the University of Deusto as a teaching and research staff member, where he contributes to the Faculty of Engineering in the Department of Computer Science.