Aparajit Venkatesh

University of Washington

Papers

3

Total Citations

11

H-Index

2

About

Aparajit Venkatesh is an emerging researcher specializing in robotic tactile sensing, haptic perception, and intelligent manipulation systems. His work sits at the intersection of machine learning and robotics, with a particular focus on enabling robots to handle objects with human-like dexterity and reliability. Venkatesh's most significant contribution lies in developing novel approaches to slip detection during robotic grasping and manipulation. His research demonstrates how tactile sensing, combined with contact force field estimation and entropy-based analysis, can provide robots with the nuanced feedback necessary to prevent object slippage — a capability long considered a hallmark of human dexterity. Rather than relying solely on visual information, his methodology integrates artificial tactile sensors with learning algorithms, pushing the boundaries of what robotic hands can perceive and respond to in real time. His publications have collectively garnered over a dozen citations since 2023, reflecting rapidly growing interest in the community. Notably, his work addresses a critical gap in robotic manipulation research: the transition from vision-dependent systems toward truly multi-modal sensory integration. For students and researchers exploring embodied AI and dexterous robotics, Venkatesh's contributions represent a meaningful step toward machines that can interact with the physical world as fluidly as humans do.

Research Focus

Key Achievements

2
H-Index
3
Papers
11
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Learning to detect slip through tactile estimation of the contact force field and its entropy properties
7 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: University of Washington

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago