Ilias Sourikopoulos

Centre National de la Recherche Scientifique, Université de Lille

Papers

Total Citations

286

H-Index

About

Ilias Sourikopoulos is a pioneering researcher in ultra-low-power neuromorphic computing, specializing in the design of analog circuits that mimic biological neural behavior. Working at the intersection of microelectronics and bio-inspired computing, his research addresses one of the most pressing challenges in modern computing: energy efficiency as Moore's law approaches its fundamental limits. His most celebrated contribution, "A 4-fJ/Spike Artificial Neuron in 65 nm CMOS Technology" (2017), garnered over 211 citations and demonstrated a remarkable breakthrough in spiking neural network hardware, achieving extraordinary energy consumption figures that set new benchmarks for neuromorphic circuit design. This work established him as a leading voice in exploring post-Von Neumann computing architectures. His subsequent research, including "A Sub-35 pW Axon-Hillock Artificial Neuron Circuit" (2019), further pushed the boundaries of low-power analog neuron design, attracting 62 additional citations and reinforcing the trajectory of his contributions. Across his body of work, Sourikopoulos consistently champions bio-inspired processing as a viable pathway toward cognitively capable, energy-conscious computing systems, making his research highly relevant to students and engineers navigating the future of artificial intelligence hardware.