Papers
13
Total Citations
415
H-Index
9
About
Tasbolat Taunyazov is a robotics researcher whose work sits at the intersection of tactile sensing, neuromorphic computing, and robot teleoperation. He is best known for pioneering event-driven sensory systems that bring biologically inspired perception to robotic platforms. His landmark contribution, the NeuTouch neuromorphic fingertip tactile sensor, introduced an event-based architecture that scales efficiently with taxel count and underpins a multi-modal visual-tactile learning framework — work that has garnered over 118 citations and established him as a leading voice in spike-based robot perception. Complementing this, his TactileSGNet framework applied spiking graph neural networks to event-based tactile object recognition (51 citations), while separate investigations into texture classification through hybrid touch strategies and neural coding further deepened the field's understanding of machine touch. Beyond sensing, Taunyazov has made notable contributions to robot teleoperation, developing model predictive control approaches for semi-autonomous manipulation with whole-body obstacle avoidance (73 citations) and open-source motion-tracking hardware to democratize robotics research. His more recent exploration of extended tactile perception — enabling robots to sense through held tools — points toward increasingly human-like robotic dexterity. Across roughly 400 cumulative citations, his body of work consistently bridges neuroscience-inspired design with practical robotic applications.
Research Focus
Key Achievements
Top Papers
- 1Event-Driven Visual-Tactile Sensing and Learning for Robots118 citations · 2020
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- 10Event-Driven Visual-Tactile Sensing and Learning for Robots6 citations · 2020