What if the figures of speech we barely notice also preserve evidence of how we think? We say ideas take root, love is a journey, and memories fade because abstract experience becomes manageable through patterns borrowed from familiar worlds. Metaphorical Cognition turns this everyday phenomenon into a rigorous object of inquiry, asking how language can disclose the conceptual frameworks of individuals, communities, and intelligent systems.

Bringing together cognitive science, linguistics, neuroscience, philosophy, and artificial intelligence (AI), Rui Mao and Erik Cambria show how metaphor can be examined computationally and evaluated empirically. The methodological core is MetaPro, an end-to-end system that moves from detecting metaphorical wording to recovering contextual meaning and forming concept mappings. Neural, behavioral, and AI-based studies test the significance of these representations, while applications across finance, health, politics, culture, social bias, philosophy, and large language models demonstrate their value for investigating cognitive differences across domains, populations, and time.

Accessible to newcomers yet substantial for specialists, the book advances the broader idea of concept projection: drawing on experience, the mind establishes projection relations between concepts and uses them to interpret what it encounters. Once activated, these projections organize meaning, guide judgment, and shape what can be imagined as possible. By connecting cognitive theory with computational practice, the book offers researchers and students a foundation for investigating the mind while setting out an ambitious agenda for more interpretable, human-centered AI.

Rui Mao is a Research Scientist and Lead Investigator in the College of Computing and Data Science at Nanyang Technological University. His research spans computational linguistics, cognitive computing, and human-centered AI. He is best known for pioneering computational approaches to metaphor processing and metaphor-based cognitive analysis. Building on MetaPro, an end-to-end system for metaphor identification, interpretation, and concept mapping generation, his research investigates how concept mappings reveal latent patterns in individual and collective cognition and how these insights can inform more interpretable and human-centered AI systems. He has authored over 130 publications in leading AI and cognitive science venues, including ICML, ICLR, ACL, AAAI, IJCAI, SIGIR, SIGKDD, CogSci, and npj Artificial Intelligence. His work has received four international best paper awards from IEEE Transactions on Affective Computing, IEEE SSCI, IEEE BIBM, and ACM ICAIF. Since 2025, he has also been included in Stanford University and Elsevier’s list of the world’s top 2% scientists. He serves as an associate editor for IEEE Transactions on Affective Computing, Information Fusion, and Neurocomputing and contributes to major AI conferences, workshops, and journal special issues as a senior area chair, guest editor, reviewer, and organizer.

Erik Cambria is a Professor at Nanyang Technological University, where he also holds the appointment of Provost Chair in Computer Science and Engineering, and Founder of several AI companies, such as SenticNet, offering B2B sentiment analysis services, and finaXai, providing fully explainable financial insights. Prior to moving to Singapore, he worked at Microsoft Research Asia (Beijing) and HP Labs India (Bangalore), after earning his PhD through a joint program between the University of Stirling (UK) and MIT Media Lab (USA). Today, his research focuses on neurosymbolic AI for interpretable, trustworthy, and explainable affective computing in domains like social media monitoring, financial forecasting, and AI for social good. He is ranked in Clarivate’s Highly Cited Researchers List of World’s Top 1% Scientists, is recipient of many awards, e.g., IEEE Outstanding Early Career, was listed among the AI’s 10 to Watch, and was featured in Forbes as one of the 5 People Building Our AI Future. He is an IEEE Fellow, Associate Editor of various top-tier AI journals, e.g., Information Fusion and IEEE Transactions on Affective Computing, and is involved in several international conferences as keynote speaker, program chair and committee member.