Research
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Net0Morph
Ultra–low-power, carbon-aware, "Net-Zero" oriented neuromorphic computing platform designed for edge AI.
Focused on energy-efficient inference using event-driven architectures and 3D integration. -
HYMEX
Hybrid Memory Architecture for NeXt-Generation AI systems, combining high bandwidth and low latency.
Enables scalable data movement for memory-bound workloads in AI accelerators. -
3D-IC Design
Advanced 3D-stacked architectures for high-density and high-bandwidth computing.
Explores vertical integration, memory-logic co-design, and thermal-aware optimization for next-generation AI and data-intensive workloads. -
Robotics & Autonomous Systems
Intelligent control and perception for robotics and drone platforms.
Focuses on real-time sensing, adaptive control, and energy-efficient onboard computing for reliable autonomous operation. -
Always-On AI
Continuous, energy-efficient AI systems designed for real-time perception and decision-making.
Focuses on resilient operation under noise, variability, and intermittent faults while maintaining low power and high responsiveness. -
UCT×E3C Collaboration
Joint research initiative with the University of Transport and Communications.
Advancing hardware-software co-design for energy-efficient and scalable computing systems.
Funders
