P Samuel

Draper Laboratory

Papers

1

Total Citations

11

H-Index

1

About

P Samuel is a leading researcher in edge computing and machine learning (ML) systems for resource-constrained platforms, with a particular focus on small unmanned aerial vehicles (UAVs). His pioneering work challenges the conventional assumption that ML workflows require resource-rich environments, instead demonstrating how sophisticated inferencing can be pushed to the edge. His most-cited paper, "Machine Learning on Small UAVs" (2020, 11 citations), details the concept of operations, design parameters, and constraints faced by his team at Draper Laboratory when implementing ML on small UAVs. This work has established foundational principles for deploying artificial intelligence in size, weight, and power (SWaP)-limited systems, enabling real-time autonomous decision-making in the field. Samuel's contributions are critical for advancing defense, surveillance, and environmental monitoring applications where onboard intelligence is essential. His research continues to shape how engineers approach edge ML, balancing computational efficiency with algorithmic performance in the most demanding operational environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
11
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Machine Learning on Small UAVs
11 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Draper Laboratory

Top Papers

  1. 1
    Machine Learning on Small UAVs
    11 citations · 2020

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago