Shardul Kulkarni
Papers
3
Total Citations
12
H-Index
2
About
Shardul Kulkarni is a robotics researcher advancing the frontiers of dexterous manipulation and tactile perception. His work centers on enabling robotic hands to interact with and understand the diverse physical properties of everyday objects—from shape and texture to deformability and mass. Kulkarni’s major contributions include pioneering the use of Graph Convolutional Networks (GCNs) for processing high-dimensional tactile data from multi-fingered hands, introducing novel topological segmentation methods to improve object recognition accuracy. His 2024 paper on “Tactile Object Property Recognition Using Geometrical Graph Edge Features” has already garnered 7 citations, reflecting its immediate impact on the field. He also developed a linear series clutch actuator with static balancing for safe human-robot collaboration, addressing critical force control challenges through passive mechanical design. With a growing citation record and multiple publications in 2024–2025, Kulkarni is establishing himself as a key voice in tactile sensing and compliant actuation—bridging the gap between robust perception and safe physical interaction in robotics.
Research Focus
Key Achievements
Top Papers
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