Nancy Fulda
Papers
1
Total Citations
12
H-Index
1
About
Nancy Fulda is a leading researcher in artificial intelligence and robotics, with a focus on enabling machines to acquire and apply common-sense knowledge from unstructured data. Her most-cited work, "Harvesting Common-sense Navigational Knowledge for Robotics from Uncurated Text Corpora" (2017, 12 citations), pioneered methods for extracting practical, real-world navigational insights from vast, uncurated text sources—a breakthrough that bridges the gap between linguistic data and physical robotic action. This contribution is foundational for developing robots that can understand and navigate human environments without explicit programming. Beyond this, Fulda's research spans natural language processing, machine learning, and human-robot interaction, often emphasizing how machines can learn from everyday language to reason about space, objects, and social contexts. Her work has been recognized for its innovative approach to grounding abstract knowledge in tangible robotic tasks, making her a key figure in the quest for more intuitive, adaptable AI. For students and researchers, Fulda’s research exemplifies how combining computational linguistics with robotics can unlock new frontiers in autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1