Papers
11
Total Citations
83
H-Index
5
About
Jamison Heard is a robotics and human-robot interaction researcher whose work centers on human workload assessment, adaptive human-robot teaming, and intelligent decision-making systems for high-stakes environments. His research addresses a critical challenge: how robots can intelligently perceive and respond to a human operator's internal state — including workload, stress, and fatigue — to optimize collaborative performance in domains ranging from space exploration to disaster response. Heard's most influential contribution is his diagnostic human workload assessment algorithm, which has accumulated 27 citations and laid the groundwork for real-time, multi-dimensional monitoring of operators in supervisory and collaborative human-robot paradigms. Building on this foundation, he developed reinforcement learning frameworks that enable robots to adaptively respond to human states, as well as comprehensive architectures like SAHRTA that integrate these capabilities into deployable teaming systems. More recently, his research has expanded into multimodal machine learning and inclusive human-robot interaction design, including pioneering work examining teaming dynamics for Deaf and hard-of-hearing individuals. With over 80 cumulative citations, Heard's body of work reflects a sustained commitment to making human-robot teams safer, more responsive, and more equitable — contributions of growing relevance as autonomous systems increasingly operate alongside humans in critical real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Human-Aware Reinforcement Learning for Adaptive Human Robot Teaming7 citations · 2022
- 4Regulating Modality Utilization within Multimodal Fusion Networks6 citations · 2024
- 5A Diagnostic Human Workload Assessment Algorithm for Human-Robot Teams6 citations · 2018
- 6
- 7A Human-Aware Decision Making System for Human-Robot Teams4 citations · 2022
- 8
- 9SAHRTA: A Supervisory-Based Adaptive Human-Robot Teaming Architecture3 citations · 2020
- 10