Mike Prieto

Papers

Total Citations

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About

Mike Prieto is a leading researcher at the intersection of self-adaptive systems and human-machine teaming (HMT). His primary research areas include autonomous systems, cyber-physical systems, and the design of feedback loops that enable effective collaboration between humans and intelligent machines. Prieto’s most notable contribution is his seminal work extending the MAPE-K (Monitor, Analyze, Plan, Execute, Knowledge) feedback loop—long established as the standard reference model for self-adaptive and autonomous systems in domains like autonomous driving and robotics—to explicitly support human-machine teaming. His 2022 paper on this topic, which has already garnered 28 citations, redefines how autonomous systems can dynamically integrate human input, shifting from simple automation to true partnership. This work is critical for advancing safety and trust in high-stakes environments where humans and machines must coordinate seamlessly. Prieto’s research not only bridges a gap in existing autonomous system architectures but also provides a practical framework for designing next-generation cyber-physical systems that prioritize collaborative intelligence. His contributions are shaping how researchers and engineers approach the future of human-autonomy interaction.