Shaukat Abidi

University of Technology Sydney, Centre for Quantum Computation and Communication Technology

Papers

Total Citations

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About

Shaukat Abidi’s research lies at the intersection of human-robot interaction and computer vision, with a focus on how robots can interpret and direct human attention through natural gestures. His most influential work, “Human pointing as a robot directive” (2013, 22 citations), established foundational insights into how people naturally use pointing gestures to communicate—a skill Abidi has worked to translate into robotic systems for more intuitive collaboration. He further explored this in “Directing human attention with pointing” (2014, 7 citations), investigating how robot-generated pointing behaviors can effectively guide human focus during joint tasks. Beyond gesture-based interaction, Abidi has contributed to bipedal locomotion, evolving dynamic walking gaits using Partial Fourier Series (2012), and to action recognition from still images—a challenging computer vision problem with applications in robotic navigation and surveillance. His work on latent superpixel classification (2015) and efficient greedy inference (2016) advances the ability to recognize human actions without relying on motion cues. With over 40 total citations, Abidi’s research bridges the gap between human communication and robotic perception, making strides toward robots that can understand and respond to our most natural directives.