Neuromorphic circuits, systems, and technologies—rooted in the principles underlying the structure, dynamics, and functionality of the biological nervous system—are emerging as a key paradigm in advanced electronic design. By integrating brain-inspired concepts directly into hardware, neuromorphic engineering enables new approaches to sensing, computation, and information processing that go beyond traditional circuit and system design methodologies. This special session aims to highlight recent advances and emerging trends in neuromorphic circuits and systems, emphasizing their growing relevance, technological impact, and the unique challenges and opportunities they present to the electronic design community. 

The session will bring together contributions that span multiple topics, including:

• Neuromorphic sensors for efficient low-power acquisition of real-world signals and efficient sparse codification,

• Analog and mixed-signal circuit designfor implementing neuron and synapse models,

• Emerging memory technologies(e.g., memristors, phase-change memory) that support synaptic plasticity,

• Digital neuromorphic processors and system architecturesfor scalable, efficient deployment,

• Computational neuroscience and algorithmic frameworksthat inform hardware design,

• Applications in edge AI, autonomous systems, biomedical interfaces, and real-time sensing.

The cross-disciplinary nature of neuromorphic systems fosters collaboration between electrical engineering, computer science, neuroscience, and materials science, making this topic especially timely and valuable for the electronic design community.

ORGANIZERS:

Teresa Serrano-Gotarredona(Senior Member, IEEE) is currently a CSIC Full Research Professor and Director of the Institute of Microelectronics of Sevilla (IMSE-CSIC-US). Since January 2006, she is also part-time professor at the Department of Computer Architecture and Technology of the University of Seville. Her research interests include analogcircuit design of linear and nonlinear circuits, VLSI neural based pattern recognition systems, VLSI implementations of neural computing and sensory systems, transistor parameter mismatch characterization, learning systems with nanoscale memristor-type devices, and real-time vision sensing and processing chips. She has done important contributions in the field of low power low current analog circuits and also in architecture design of bioinspired vision sensors, and neural computing and learning bioinspired systems.

Koldo Basterretxea is currently an Associate Professor at the Department of Electronics Technology,  University of the Basque Country (UPV/EHU). He is the Director of the Master in Advanced Electronic Systems and member of the Advisory Committee of the SoC4sensing Business-University Chair, both at the UPV/EHU. His research interest include the design of domain-specific digital processors for edge AI/ML, the real-time processing of hyperspectral imaging with application to autonomous navigation,and the use of neuromorphic event-based vision sensors (DVS) in the development of intelligent vision systems.

Antonio Rubiois currently an Emeritus Professor at the Universitat Politècnica de Catalunya (UPC) and a Visiting Professor at the Barcelona Supercomputing Center (BSC).He is a member of, and served as its first director until September 2025, of the PERTE Chip Chair at UPC, titledAdvanced Architectures and Photonic Systems. His researchinterests focus on the topics of the chair, as well as emerging and unconventional computing technologies.