Monodeep Kar

Intel (United States)

Papers

1

Total Citations

8

H-Index

1

About

Monodeep Kar is a leading researcher in energy-efficient hardware acceleration for emerging computing paradigms, with a primary focus on 3D scene reconstruction, edge robotics, and augmented reality. His most cited work introduces a pioneering ray-casting accelerator fabricated in 10nm CMOS, which simultaneously processes multiple spatially proximate rays to exploit voxel data-locality—a critical innovation for real-time 3D mapping in resource-constrained devices. This design incorporates a near-memory search mechanism for efficient voxel address overlap detection and opportunistic approximate trilinear interpolation, achieving significant energy savings while maintaining accuracy. The accelerator’s measured performance demonstrates robust ray-casting capabilities, directly addressing the computational bottlenecks of edge robotics and AR applications. With 8 citations, this work has influenced subsequent research in specialized hardware for spatial computing. Kar’s contributions exemplify a deep understanding of the intersection between algorithm design and VLSI architecture, positioning him as a key figure in advancing efficient, real-time 3D perception systems. His research continues to push boundaries in making complex computer vision tasks viable for low-power, mobile platforms.

Research Focus

Key Achievements

1
H-Index
1
Papers
8
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
A Ray-Casting Accelerator in 10nm CMOS for Efficient 3D Scene Reconstruction in Edge Robotics and Augmented Reality Applications
8 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Intel (United States)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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