Enrico De Santis received his Master’s degree cum laude and Ph.D. in Information and Communication Engineering from Sapienza University of Rome. During his doctoral studies, he carried out research at the Department of Computer Science of Toronto Metropolitan University, Canada, first as a research assistant and subsequently as a postdoctoral researcher.

He is currently a researcher and lecturer at the Department of Information Engineering, Electronics and Telecommunications (DIET) of Sapienza University of Rome, where he teaches Pattern Recognition and Computational Intelligence. His research activity is conducted within CIPAR Labs and the Artificial Intelligence for Electrical Engineering — AI4EE research group.

His research lies at the intersection of Artificial Intelligence, Complexity Science, Computational Intelligence, and Pattern Recognition. A central strand of his work investigates artificial learning systems through concepts and methods derived from complex systems science, with particular attention to information, multiscale organization, long-range dependencies, nonlinear dynamics, emergent structures, and representation. This perspective currently extends to natural language processing, Transformer architectures, Large Language Models, generative and agentic AI, explainability, and the study of internal representations. His broader scientific agenda is presented in the Research Program, while a curated overview of representative works is available in Selected Publications.

A parallel and long-standing research line concerns the application of Computational Intelligence and machine learning to complex engineering and energy systems, including Smart Grids, Renewable Energy Communities, energy management, high-power lithium-ion battery modelling, forecasting, fault diagnosis, and predictive maintenance. Across these domains, his work combines data-driven modelling with interpretable methods and the analysis of complex dynamical behaviour.

He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and has contributed to the IEEE eXplainable AI standardization activities. His research also extends toward the theoretical foundations and epistemology of artificial intelligence, exploring connections with language theory, cognitive science, meaning, human–AI interaction, and the attribution of agency to generative systems.

In 2021, he published the interdisciplinary book Umanità, complessità e intelligenza artificiale. Un connubio perfetto with Aracne, devoted to the relationship between artificial intelligence, complex systems, knowledge, and the human condition. He has subsequently developed this interdisciplinary line through academic and public scholarship. In 2023, he published in Prometeo the essay Apocalissi digitali e alchimie artificiali. Il linguaggio nell’era della sua riproducibilità tecnica, devoted to Large Language Models and language theory. In 2025, he introduced the concept of noosemia, a cognitive and phenomenological framework for studying how artificial signs may be experienced as manifestations of mind, agency, or interiority. He also contributed the chapter L’Intelligenza Artificiale e gli strumenti di indagine to the volume Intelligenza Artificiale e Indagini Penali, addressing the transformation of investigative methods in the contemporary data-intensive and AI-mediated environment.

His activity also includes technology transfer and research-driven innovation. After his experience with the Sapienza innovative startup SisterPomos, he co-founded TensorLoops, which develops AI solutions for complex systems and industrial applications, and TensorLoops Energy, established in 2026 to develop AI and machine-learning technologies for forecasting, energy management, Smart Grids, and Renewable Energy Communities.

Sapienza University of Rome