R. Karthi
Papers
1
Total Citations
5
H-Index
1
About
R. Karthi is a researcher in spatial data mining and trajectory analysis, with a focus on developing novel feature representations for clustering moving-object data. Their key contributions center on transforming complex trajectory data—from humans, robots, taxis, and animals—into string-based representations that capture movement patterns more effectively than traditional geometric approaches. This work, exemplified in their most-cited paper "String-Based Feature Representation for Trajectory Clustering" (2019, 5 citations), addresses the challenge of grouping trajectories with similar spatiotemporal behaviors, enabling more accurate cluster formation. By rethinking how movement features are encoded, Karthi’s research has implications for applications in urban mobility, wildlife tracking, and autonomous systems. Though early in their career, Karthi’s focus on interpretable and efficient trajectory representation marks a meaningful step toward scalable analysis of dynamic spatial data, offering a foundation for future work in pattern recognition and location-based services.
Research Focus
Key Achievements
Top Papers
- 1String-Based Feature Representation for Trajectory Clustering5 citations · 2019