Yuqing Tang

About

Yuqing Tang’s research lies at the intersection of cognitive modeling, human-automation interaction, and formal verification of cyber-physical systems. Her primary contributions involve developing and validating computationally tractable models of human decision-making—grounded in the ACT-R cognitive architecture—to enable rigorous analysis of human control in complex, dynamic environments. In her most cited work (2015, 13 citations), Tang introduced a method to abstract analytical models from cognitive models of human control of robotic swarms, addressing the critical challenge of over-fitting and poor generalization when relying solely on limited human data. This work enables formal validation of human-automation systems, a key step toward safe and reliable cyber-physical systems. She further advanced this line of research by validating cognitive models for collaborative hybrid systems with discrete human input (2016, 5 citations), using K-choice games as a proxy for real-world decision-making tasks. Tang also contributed to tool development through the ACT-R Unity Interface (2015, 2 citations), integrating a leading cognitive architecture with a popular game engine to support richer, more ecologically valid simulations. Her work is foundational for researchers seeking to build trustworthy autonomous systems that account for human cognitive constraints.

Research Focus

Key Achievements

Top Papers

1. 1
   Abstraction of analytical models from cognitive models of human control of robotic swarms

   13 citations · 2015
2. 2
   Validation of cognitive models for collaborative hybrid systems with discrete human input

   5 citations · 2016
3. 3
   The ACT-R Unity Interface: Integrating ACT-R with the Unity Game Engine

   2 citations · 2015

Key Collaborators

Contact & Links