Papers
12
Total Citations
185
H-Index
7
About
Ming Hou is a prominent researcher whose work sits at the intersection of autonomous systems, human-machine interaction, and cognitive computing. Best known for his foundational contributions to the theoretical underpinnings of autonomous and symbiotic autonomous systems (SAS), Hou has helped shape how the research community understands intelligence, cognition, and machine autonomy working in concert. His most-cited paper, "Towards a Theoretical Framework of Autonomous Systems Underpinned by Intelligence and Systems Sciences" (2021, 46 citations), established critical mathematical and structural foundations for a field that is rapidly transforming artificial intelligence. Alongside this, his work on symbiotic autonomous systems explores how human-machine collaboration can give rise to collective intelligence in hybrid societies. Beyond autonomous systems theory, Hou has made meaningful contributions to adaptive collaboration modelling, biometric-enabled decision support, and robotics control, including hierarchical sliding mode approaches for trajectory tracking. His research on risk, trust, and bias in decision support systems reflects a broader commitment to responsible AI development. A recurring presence at major IEEE conferences — including as a plenary panelist at the inaugural IEEE ICAS'21 — Hou is recognized as both a theorist and a convener of ideas shaping the next generation of intelligent systems research.
Research Focus
Key Achievements
Top Papers
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- 2Adaptive Collaboration Based on the E-CARGO Model36 citations · 2012
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