Papers
2
Total Citations
10
H-Index
2
About
Hind Gacem is a researcher whose work sits at the intersection of human-robot interaction, spatial cognition, and augmented reality. Her research focuses on how projection-based guidance systems can help users locate objects more efficiently in dense, complex environments—such as supermarkets, libraries, or control rooms—and how these technologies affect human learning and memory. In her most-cited paper, "Finding Objects Faster in Dense Environments Using a Projection Augmented Robotic Arm" (2015, 7 citations), Gacem demonstrated how a robotic arm equipped with a projector can guide users to target objects more quickly than traditional methods. Her follow-up work, "Impact of Motorized Projection Guidance on Spatial Memory" (2016, 3 citations), critically examined how such external guidance systems may inadvertently impair users' ability to learn and remember object locations, raising important questions about the trade-off between immediate efficiency and long-term spatial learning. Though her citation counts are modest, Gacem’s contributions are notable for their thoughtful integration of robotics, perception, and cognitive science—offering valuable insights for designing assistive technologies that support rather than replace human memory.
Research Focus
Key Achievements
Top Papers
- 1
- 2Impact of Motorized Projection Guidance on Spatial Memory3 citations · 2016