This special session focuses on recent advances in spiking neural networks (SNNs) and neuromorphic computing for real-time, energy-efficient, and adaptive intelligence in autonomous systems. By bringing together contributions spanning learning algorithms, event-based perception, hardware co-design, and embodied control, the session highlights breakthroughs that enable robust and scalable spiking-based AI in dynamic environments.
 List of Topics (preferred, but not restricted to)
Training and optimization methodologies for SNNs
Continual, online, and neuromodulated learning in SNNs
Surrogate gradient learning and biologically inspired training principles
Hybrid analog-digital neuromorphic substrates for embedded AI
Energy-efficient spiking inference for edge and robotic platforms
Event-based sensing and neuromorphic perception for real-time control
Spatio-temporal coding strategies and neural dynamics in SNNs
Hardware-aware co-design of spiking architectures and compilers
Reliability, robustness, and security in spiking-based systems
Benchmarking tools, datasets, and standardized evaluation protocols for SNNs
Neuromorphic cognition for UAVs, mobile agents, and field robots
Cross-layer optimizations spanning algorithms, hardware, and sensor modalities
Bio-inspired computing for collective/swarm autonomy and coordination
Explainability and interpretability in spiking neural computation
Integration with large-scale neuromorphic platforms and open-source toolchains
Dr. Alberto Marchisio, Research Team Lead at eBRAIN Lab, New York University Abu Dhabi, UAE.
Prof. Muhammad Shafique, Director of eBRAIN Lab, New York University Abu Dhabi, UAE.
Prof. Maurizio Martina, VLSI Lab, Politecnico di Torino, Turin, Italy.
Dr. Hadjer Benmeziane, Research Scientist, IBM Zurich, Switzerland.
Dr. Arnab Raha, Senior Research Scientist, Advanced Architecture Research, Intel AI, USA.