Sai Kiran Narayanaswami

The University of Texas at Austin

Papers

1

Total Citations

3

H-Index

1

About

Sai Kiran Narayanaswami is a researcher at the intersection of computer vision and robotics, with a primary focus on developing efficient, real-time perception systems for autonomous agents. His most notable contribution is the design of a low-resource, end-to-end object detection pipeline specifically tailored for robot soccer, a domain demanding both high speed and minimal computational overhead. This work, published in 2023, has already garnered 3 citations, signaling early interest from the robotics and embedded vision communities. By prioritizing real-time performance without sacrificing accuracy, Narayanaswami addresses a critical bottleneck in deploying deep learning models on resource-constrained platforms—a challenge central to field robotics, drone navigation, and edge AI. His approach demonstrates how to bridge the gap between state-of-the-art detection algorithms and the stringent latency requirements of competitive robotics. As autonomous systems increasingly operate in dynamic, unstructured environments, Narayanaswami’s research offers a practical blueprint for making vision-based control both responsive and accessible. His work is particularly relevant for students and engineers seeking to implement robust perception on limited hardware, and it positions him as a rising voice in the push toward truly autonomous, real-world robot intelligence.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Towards a Real-Time, Low-Resource, End-to-End Object Detection Pipeline for Robot Soccer
3 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: The University of Texas at Austin

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago