Deepak R. Karuppiah

University of Massachusetts Amherst

Papers

9

Total Citations

127

H-Index

8

About

Deepak R. Karuppiah is a robotics and computer vision researcher whose work spans distributed sensor systems, cooperative mobile robotics, and intelligent humanoid control. Working primarily in the early 2000s, his research tackled fundamental challenges in building adaptive, fault-tolerant robotic systems capable of operating in dynamic, unpredictable environments. His most cited contribution, a fault-tolerant distributed vision architecture for object tracking in smart rooms (28 citations), laid groundwork for robust multi-camera sensing systems. Karuppiah made significant strides in panoramic stereovision, developing adaptive cooperative robot frameworks that enabled dynamic mutual calibration and 3D human tracking and localization — work reflected across several publications accumulating over 40 citations collectively. His cascaded filter approach to multi-objective robot control offered an elegant solution to preventing destructive control interactions, while his framework for humanoid intelligence addressed how robots could continuously acquire perceptual and control knowledge in unknown environments. A recurring theme throughout his portfolio is smart resource reconfiguration — optimizing when and where sensory resources are deployed to maximize information value. Conducted largely at the University of Massachusetts Amherst, his research contributed meaningfully to the foundations of sensor network planning, adaptive robotics, and intelligent vision systems that continue to inform modern autonomous robot design.

Research Focus

Key Achievements

8
H-Index
9
Papers
127
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
A Fault-Tolerant Distributed Vision System Architecture for Object Tracking in a Smart Room
28 citations · 2001
📈 Most Prolific Year: 2004 (4 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: University of Massachusetts Amherst

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago