Pranav Singh Chib
Papers
1
Total Citations
2
H-Index
1
About
Pranav Singh Chib is a researcher advancing the safety and reliability of autonomous systems, with a core focus on pedestrian trajectory prediction, robotics, and self-driving vehicle technologies. His most-cited work, "Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking" (2024), addresses a critical yet underexplored challenge in the field: the prevalence of incomplete or missing trajectory data in real-world environments. By introducing novel datasets, imputation techniques, and comprehensive benchmarking, Chib provides a foundational framework that enables more robust and accurate prediction models. This contribution is vital for ensuring that autonomous vehicles and robots can anticipate human movement even under imperfect sensing conditions, directly enhancing safety and operational efficiency. While his citation count is still growing—reflecting the recency and emerging impact of his work—Chib’s research stands out for its practical relevance and methodological rigor. His efforts are helping to bridge the gap between idealized prediction models and the messy realities of deployment, making him a promising voice in the ongoing effort to create truly reliable autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1