Kazuyuki Tasaka

Papers

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About

Kazuyuki Tasaka is a researcher whose work bridges the critical gap between 3D perception and human-robot interaction. His primary research areas include object detection in point cloud data and the design of telepresence systems for remote collaboration. Tasaka’s most notable contribution is a novel framework for 2D-to-3D label propagation, which enables efficient object detection and classification in LiDAR point clouds by leveraging pre-labeled 2D images. This approach addresses the fundamental challenge of costly and time-consuming manual annotation in 3D datasets, a bottleneck for training robust classifiers in robotic systems. With 6 citations, this work has provided a practical pathway for advancing autonomous navigation and scene understanding. In parallel, Tasaka has explored the socio-technical challenges of remote work, authoring an invited paper on using telepresence robots to facilitate informal communication—such as impromptu meetings—in long-term telework scenarios. His proposed system, drawing on the concept of an always-on media space, aims to recreate the spontaneous interactions lost when working from home. Through these dual contributions in perception and collaboration, Tasaka is shaping more capable robots and more connected remote teams.