Zukhraf Jamil

National University of Sciences and Technology

Papers

Total Citations

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About

Zukhraf Jamil is a researcher whose work lies at the intersection of human motion analysis and human-robot interaction. Her primary research focuses on developing computational models that enable robots to understand and predict human behavior, with a particular emphasis on head motion tracking for interactive applications. In her notable 2019 paper, "Human Head Motion Modeling Using Monocular Cues for Interactive Robotic Applications," Jamil introduced generalized 2D trajectory models for human motion during walking and running. By mapping head motion trajectories through monocular cues, she developed a method to compute instantaneous displacement and velocity—a critical step toward creating more intuitive, user-centered human-computer interfaces. This work has garnered 2 citations, reflecting its foundational role in advancing non-invasive motion tracking for robotics. Jamil's contributions are particularly valuable for designing assistive robots and interactive systems that require real-time, naturalistic human motion prediction. Her research demonstrates a commitment to bridging the gap between raw sensory data and meaningful robotic responses, making her a promising voice in the field of human-centered robotics.