Parisa Kordjamshidi
Papers
3
Total Citations
45
H-Index
3
About
Parisa Kordjamshidi is a leading researcher in artificial intelligence, specializing in natural language understanding, spatial reasoning, and structured machine learning. Her work bridges the gap between human language and spatial ontologies, enabling machines to interpret and reason about spatial relationships described in text. She is best known for pioneering the field of spatial role labeling (SpRL), introducing both the foundational annotation scheme and the multimodal Spatial Role Labeling task at CLEF 2017, which has garnered over 21 citations. Her research has significantly advanced how AI systems process location and movement descriptions, with applications ranging from geographical information systems to robotics. Kordjamshidi's structured machine learning approach for mapping natural language to spatial ontologies, published in 2013, remains a cornerstone of spatial language understanding. Her contributions have been widely recognized, establishing her as a key figure in making AI more spatially aware and linguistically competent. Through her work, she continues to shape how machines comprehend and interact with the physical world.
Research Focus
Key Achievements
Top Papers
- 1CLEF 2017: Multimodal Spatial Role Labeling (mSpRL) Task Overview21 citations · 2017
- 2Spatial Role Labeling Annotation Scheme18 citations · 2017
- 3