Evan Carter

Papers

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About

Evan Carter is a researcher at the forefront of human-machine teaming, specializing in the integration of psychophysiological measures to enhance implicit communication within mixed-initiative systems. His work bridges cognitive science, engineering, and human factors, exploring how physiological signals—such as heart rate variability and skin conductance—can serve as non-verbal cues to optimize collaboration between humans and autonomous agents. Carter’s most-cited paper, "The Role of Psychophysiological Measures as Implicit Communication Within Mixed-Initiative Teams" (2018), has garnered 6 citations, laying foundational groundwork for adaptive interfaces that respond to operators’ cognitive and emotional states in real time. This contribution is particularly impactful in high-stakes domains like aviation, military command, and disaster response, where seamless human-autonomy interaction is critical. Beyond this work, Carter has advanced methods for measuring trust and workload in dynamic environments, earning recognition for his innovative experimental designs. His research not only deepens theoretical understanding of team cognition but also offers practical pathways for designing more intuitive and responsive AI systems, making him a rising voice in the future of collaborative intelligence.