Darrin Howell
Papers
1
Total Citations
5
H-Index
1
About
Darrin Howell is a researcher whose work lies at the intersection of human sensorimotor learning, control theory, and cyber–physical systems (CPS). His key research areas include human–cyber–physical systems (HCPS), teleoperation, and the modeling of how humans form and use beliefs about system dynamics to control remote robots. In his most-cited paper, "Toward experimental validation of a model for human sensorimotor learning and control in teleoperation" (2017, 5 citations), Howell develops a theoretical framework for understanding how operators adapt their control strategies during tracking tasks in teleoperation. This work is notable for bridging the gap between computational models of human learning and real-world CPS applications, offering insights that could improve the design of intuitive interfaces and autonomous assistance systems. While his citation count is modest, Howell’s contributions are foundational for researchers exploring the human role in increasingly automated systems. His work highlights the importance of integrating human cognition into CPS design, making it relevant for students and engineers working on human–robot interaction, shared control, and adaptive automation.
Research Focus
Key Achievements
Top Papers
- 1