Nitesh Mor

University of California, Berkeley

Papers

2

Total Citations

88

H-Index

2

About

Nitesh Mor is a leading researcher in the intersection of robotics and distributed computing, with a primary focus on **Fog Robotics** and **deep robot learning**. His most influential work, a 2019 paper on "A Fog Robotics Approach to Deep Robot Learning," has garnered 81 citations, establishing him as a pioneer in addressing the limitations of centralized cloud robotics. Mor’s key contribution is the development of a distributed computing framework that tackles critical challenges in industrial, automotive, and service robotics—namely privacy, security, latency, bandwidth, and reliability. By shifting computation and storage from the cloud to the network edge (the "fog"), his approach enables more responsive and secure robot learning for tasks like object recognition and grasp planning in surface decluttering. This work is particularly notable for its practical application in real-time robotic manipulation, where low latency is essential. Mor’s research has significant implications for the future of autonomous systems, offering a scalable and robust alternative to cloud-dependent models. His achievements highlight a deep understanding of both hardware constraints and algorithmic demands, making his contributions highly relevant for students and researchers exploring edge intelligence in robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
88
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering
81 citations · 2019
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago