A. Prieto

University of Amsterdam, Universidad de Granada, Cisco Systems (United States)

Papers

Total Citations

H-Index

About

A. Prieto’s research lies at the intersection of evolutionary computation, neuromorphic engineering, and autonomous systems. Their most influential work, “Is situated evolution an alternative for classical evolution?” (2009, 11 citations), proposes a novel evolutionary method tailored to the demands of adaptivity, scalability, and robustness—critical requirements in pervasive computing, autonomic systems, and collective robotics. This contribution challenges traditional evolutionary paradigms by embedding evolution within the operational environment, enabling real-time adaptation. Prieto also advanced computational neuroscience with “Spiking Neurons Computing Platform” (2005, 8 citations), a foundational framework for implementing biologically plausible neural networks. More recently, their work “Software-defined operations” (2016, 2 citations) addresses the automation gap in carrier networks, advocating for programmable, software-driven management to align telecommunications with broader ICT efficiency gains. Though citation counts are modest, the breadth of Prieto’s contributions—from situated evolution to spiking neural hardware and network automation—demonstrates a sustained commitment to bridging biological inspiration with practical engineering. Their research continues to influence emerging fields where decentralized, adaptive, and efficient computation is paramount.