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About

Payman Shakouri is an engineering educator and researcher whose work sits at the intersection of control systems theory and hands-on pedagogical practice. His research primarily focuses on making advanced control concepts accessible to students through real-world robotic implementations, with a particular emphasis on fuzzy logic control, model predictive control, and adaptive cruise control systems. Shakouri's most impactful contribution — his 2013 paper on teaching fuzzy logic control via robotic implementation, which has garnered 12 citations — exemplifies his core philosophy: that complex control algorithms are best understood when demonstrated on physical hardware rather than confined to abstract modeling. This approach extends across a series of interconnected works in which the NI Starter Kit Robot serves as a versatile educational platform, enabling students at both undergraduate and master's levels to engage meaningfully with sophisticated control strategies. Beyond pedagogy, Shakouri has made notable contributions to applied control engineering, particularly in the domain of adaptive cruise control systems, exploring switching controllers and comparing competing control methodologies through robotic prototyping. With a cumulative citation count of approximately 28 across his key works, his research has established a meaningful reference base for engineering educators seeking to bridge the gap between theory and practical experimentation in the classroom.