Nils Exibard

About

Nils Exibard is a leading researcher in energy-efficient artificial intelligence hardware, with a focus on AI-enabled Internet-of-Things (AI-IoT) systems. His most cited work, a 2023 paper with 34 citations, introduces a groundbreaking AI-IoT System-on-Chip (SoC) that achieves 12.4 TOPS/W at 136 GOPS, integrating 16 RISC-V cores with precision-scalable DNN acceleration supporting 2-to-8-bit operations. This design incorporates adaptive body biasing for a 30% boost in efficiency, addressing the critical challenge of running diverse tasks—from augmented reality to nano-robotics—within a power envelope of tens of milliwatts. Exibard’s major contribution lies in bridging the gap between compute-intensive DNNs and ultra-low-power edge devices, enabling real-time inference without sacrificing accuracy. His work has significant implications for personalized healthcare and autonomous systems, demonstrating how precision-scalable architectures can optimize both performance and energy consumption. With a citation count reflecting growing influence, Exibard continues to push boundaries in adaptive hardware design, making him a key figure in the next generation of sustainable AI systems.

Research Focus

Key Achievements

Top Papers

1. 1
   22.1 A 12.4TOPS/W @ 136GOPS AI-IoT System-on-Chip with 16 RISC-V, 2-to-8b Precision-Scalable DNN Acceleration and 30%-Boost Adaptive Body Biasing

   34 citations · 2023

Key Collaborators

Contact & Links