Sujitha Martin
Papers
2
Total Citations
18
H-Index
2
About
Sujitha Martin’s research lies at the critical intersection of autonomous driving, robotics, and explainable artificial intelligence. Her primary focus is on developing transparent, trustworthy AI systems that can safely cooperate with humans in real-world environments. Martin’s most influential work, “Grounded Relational Inference: Domain Knowledge Driven Explainable Autonomous Driving,” has accumulated 18 citations across its 2021 and 2024 versions, demonstrating growing recognition in the field. Her key contribution is a novel framework that integrates domain knowledge—such as traffic rules and spatial relationships—directly into the reasoning process of autonomous vehicles. This allows the system to not only predict actions but also provide human-understandable explanations for why a particular maneuver was chosen, addressing a fundamental barrier to public trust in self-driving technology. By grounding relational inference in explicit knowledge, Martin’s approach moves beyond black-box deep learning models, offering a path toward verifiable, auditable decision-making. Her work is particularly impactful for students and researchers interested in human-robot interaction, safety-critical AI, and the challenge of making complex autonomous systems interpretable without sacrificing performance.
Research Focus
Key Achievements
Top Papers
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