C. Alexander Hirst
Papers
1
Total Citations
9
H-Index
1
About
C. Alexander Hirst is a researcher at the forefront of autonomous systems and human-robot interaction, with a particular focus on building trust between humans and intelligent machines. His work centers on developing frameworks for autonomous vehicles and robots to accurately communicate their own competency, enabling safer and more effective human oversight. Hirst’s most cited paper, “Generalizing Competency Self-Assessment for Autonomous Vehicles Using Deep Reinforcement Learning” (2022), introduces a novel method for robots to evaluate and report their own performance in real-time, a critical step toward calibrated human trust in automation. This work, which has garnered 9 citations and includes a video presentation, demonstrates his ability to bridge deep reinforcement learning with practical human factors engineering. By tackling the challenge of self-assessment generalization, Hirst is helping to shape a future where autonomous systems can operate alongside humans with transparency and reliability. His research is particularly valuable for students and engineers working on human-autonomy teaming, offering both theoretical insight and applied solutions for next-generation robotics.
Research Focus
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Top Papers
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