Samantha L. Connolly
Papers
1
Total Citations
2
H-Index
1
About
Samantha L. Connolly is a leading researcher in autonomous robotics and explainable artificial intelligence (XAI), with a focus on developing trustworthy decision-making systems for unmanned vehicles. Her most-cited work, "A novel explainable AI-based situation recognition for autonomous robots with partial unlabeled data" (2023), addresses a critical challenge in robotics: enabling autonomous systems to interpret complex environments even when training data is incomplete or unlabeled. Connolly’s approach integrates XAI techniques with deep neural networks, enhancing transparency in robotic path planning and navigation—an area where traditional black-box models often fail. With 2 citations in a short time, this paper has already sparked interest in bridging the gap between AI reliability and real-world deployment. Her contributions are particularly vital for safety-critical applications, such as disaster response and autonomous transport, where understanding a robot’s reasoning is essential. Connolly’s work stands out for its practical focus on partial data scenarios, a common hurdle in field robotics. As a rising voice in the field, she is shaping the future of explainable, resilient autonomous systems.
Research Focus
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Top Papers
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