About the Author
Biography
Francisco Javier Falcó Benavent (Javier Falcó) is a Professor in the Department of Mathematical Analysis at the Universidad de Valencia (University of Valencia), Spain, a position he has held since 2017.
His academic work focuses on functional analysis and the geometry of Banach spaces, where he has made significant contributions to various fields of mathematical research. Beyond his research in pure mathematics, he is deeply committed to science education and outreach.
Teaching & Outreach
Professor Falcó teaches mathematical analysis courses across different degree programs at the University of Valencia. In addition to his regular academic teaching, he is actively involved in science communication through the university's Extension Service (Servicio de Extensión Universitaria), where he delivers public courses on scientific topics, making complex concepts accessible to broader audiences.
His passion for education extends to artificial intelligence literacy. Through the Artificial Brains trilogy, he combines rigorous technical content with engaging narrative storytelling, making AI concepts understandable to both technical and non-technical readers.
Research Focus
His research centers on:
- Functional Analysis
- Geometry of Banach Spaces
- Mathematical foundations relevant to machine learning and AI
Contact
- Email: artibrains@gmail.com
- Academic Profile: https://franjfal.github.io/
- Institutional Page: Universidad de Valencia
- Office: Department of Mathematical Analysis, C/ Dr. Moliner, 50, 46100 Burjassot, Valencia, Spain
About the Artificial Brains Trilogy
The trilogy represents a unique approach to AI education, blending:
- Technical Rigor: Mathematical foundations and accurate technical details
- Narrative Fiction: Engaging stories with relatable characters
- Practical Applications: Real-world contexts and implementation challenges
- Educational Philosophy: Building intuition before diving into formulas
Each book in the trilogy addresses different aspects of artificial intelligence, from supervised learning to unsupervised and reinforcement learning, to multimodal AI and generative systems.
Philosophy
"AI education should not be about memorizing algorithms or blindly using tools. It's about understanding how machines learn, why they make certain decisions, and how we can responsibly integrate them into society. Mathematics is not a barrier—it's the language that makes AI understandable."