Yue Hu

Papers

Total Citations

110

H-Index

About

Yue Hu is a researcher whose work sits at the intersection of autonomous systems, computer vision, and machine learning, with a particular focus on motion prediction and multi-agent interaction modeling. His most recognized contribution, "Collaborative Motion Prediction via Neural Motion Message Passing" (2020), has garnered 110 citations and represents a significant advance in how intelligent systems anticipate the behavior of surrounding agents. By proposing a neural message passing framework that explicitly models cooperative interactions among traffic participants — such as collision avoidance and group formation — Hu addressed one of the most persistent challenges in autonomous driving and social robotics: understanding not just individual trajectories, but the rich relational dynamics between actors sharing a space. This work demonstrated that leveraging graph-based neural communication between agents yields more accurate and socially aware motion forecasts, a finding with broad implications for the safety and reliability of self-driving vehicles and human-robot interaction systems. With a growing citation record, Hu's research has meaningfully shaped how the autonomous systems community approaches interaction-aware prediction, making him a notable voice in this rapidly evolving field.