Speaker: Lingyun Yu (Xi’an Jiaotong-Liverpool University)
Bio: Lingyun Yu is an Associate Professor in the Department of Computing at Xi’an Jiaotong-Liverpool University, China. She received her PhD from the University of Groningen, the Netherlands, in 2013. Her research focuses on interactive visualization, human-computer interaction, and virtual/augmented reality, with a particular interest in applying immersive visualization and interaction techniques to the exploration of 3D spatial data. Her work has been recognized with multiple honors, including Top Cited Article Awards, Best Paper Awards at leading conferences, and the prestigious 12-Year SciVis Test of Time Award at IEEE VIS. Personal website: www.yulingyun.com
Abstract: Selection is a fundamental step in spatial data visualization, yet defining an appropriate selection range in 3D space remains challenging. Users often struggle to specify meaningful subsets, handle occlusions, and ensure that selected regions accurately capture target data features. These challenges differ across visualization environments, from 2D screens to immersive and cross-reality settings. In this talk, I will present several context-aware selection techniques developed for point cloud visualizations across diverse environments, including traditional 2D screens, hybrid touch/tangible surfaces, virtual reality, and cross-reality systems. These techniques integrate data context, spatial awareness, and interaction modality to adapt to users’ intentions and environmental constraints. Together, they demonstrate how context-aware design can enhance precision, efficiency, and comprehension in spatial data exploration across various visualization environments.
