Papers
5
Total Citations
17
H-Index
3
About
Shakra Mehak is a rising researcher at the forefront of human-robot collaboration, specializing in the critical intersection of safety, productivity, and human factors in industrial robotics. Her work focuses on developing frameworks that enable effective human-robot teaming (HrT) and collaborative intelligence (CI), addressing the complex dynamics of how humans and machines can work together safely and efficiently. Mehak’s major contributions include a safety-driven deep reinforcement learning framework for cobots, which integrates ISO 10218 velocity constraints directly into simulation training using a Sim2Real approach, and a roadmap for improving data quality standards in collaborative intelligence applications. She has also explored mutual performance monitoring in human-robot teams and the quantification of human factors in programming by demonstration (PbD). With her most-cited paper (5 citations) published in 2024, her work is gaining traction in the rapidly evolving field of Industry 4.0. Mehak’s research is particularly notable for its practical focus on balancing safety with productivity, offering actionable insights for deploying collaborative robots in real-world factory environments.
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