Charles J. Doherty
Papers
1
Total Citations
6
H-Index
1
About
Charles J. Doherty is a leading researcher at the intersection of computer vision, robotics, and autonomous systems, with a particular focus on enabling uncrewed aircraft for naval operations. His most cited work, published in 2023, tackles a critical bottleneck in deep learning: the labor-intensive process of creating ground-truth image labels. Doherty’s innovative approach leverages industrial robotics and motion capture to automate this labeling, dramatically accelerating the training and evaluation of neural networks for real-world deployment. This contribution is especially vital for the U.S. Navy’s vision of integrating more uncrewed aircraft into carrier air wings, where robust autonomy is essential when human operators cannot be directly in the loop. With 6 citations already, his work is gaining traction for its practical impact on scalable AI training. Doherty’s research addresses the core challenge of trust and reliability in autonomous systems, making him a key figure in advancing machine learning for safety-critical, high-stakes environments.
Research Focus
Key Achievements
Top Papers
- 1