The rapid evolution of intelligent systems is driving a renewed focus on hardware that mirrors the efficiency, adaptability, and resilience of biological brains. This track invites original contributions that explore architectures, circuits, devices, and integrated platforms inspired by neural, cognitive, and adaptive processes. We aim to bring together researchers and practitioners working at the intersection of neuromorphic engineering, cognitive computing, emerging devices, and system‑level integration to advance the next generation of intelligent hardware.
Scope and Topics of Interest
Submissions are encouraged in, but not limited to, the following areas:
- Neuromorphic and Brain‑Inspired Architectures
Spiking neural processors, event‑driven computing, massively parallel architectures, and hardware models of cognition and learning. - Adaptive and Self‑Organizing Hardware Systems
On‑chip learning, plasticity mechanisms, real‑time adaptation, and hardware‑embedded intelligence for dynamic environments. - Emerging Devices and Materials for Cognitive Computing
Memristive technologies, phase‑change devices, ferroelectric components, spintronics, and other novel devices enabling synaptic and neuronal functions. - Hardware Acceleration for Cognitive Workloads
Architectures optimized for perception, reasoning, decision‑making, and multimodal processing. - Energy‑Efficient and Ultra‑Low‑Power Designs
Architectures and circuits targeting edge intelligence, IoT, robotics, and autonomous systems. - Brain‑Inspired System Integration
3D integration, heterogeneous packaging, sensor‑processor co‑design, and bio‑inspired communication fabrics. - Applications and Demonstrators
Robotics, autonomous systems, smart sensing, human–machine interaction, and real‑world deployments of cognitive hardware.
Audience and Impact
This track is designed for researchers, engineers, and innovators working on the foundations and applications of brain‑inspired hardware. It provides a platform to showcase breakthroughs that push the boundaries of adaptive, efficient, and cognitively capable computing systems.
Paper Submission
For paper submission instructions and deadlines, please access the paper submission page.
Former Chairs
- Prof. Gianvito Urgese, Politecnico di Torino, Italy (16th IEEE MCSoC 2023)
- Prof. Khanh Dang, University of Aizu, Japan (17th IEEE MCSoC 2024)
