Huangyuan Su

Carnegie Mellon University

Papers

1

Total Citations

2

H-Index

1

About

Huangyuan Su is a rising researcher in autonomous driving, with a focus on bridging the gap between trajectory forecasting and real-world planning. His most cited work, "Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving" (2024), tackles a critical challenge: how to integrate multimodal prediction models with downstream planners and model-based control. While many approaches treat prediction and planning as separate tasks, Su’s work proposes a tractable framework that jointly reasons over discrete behavior modes, enabling more coherent and safe urban driving decisions. Though early in his career—with his top paper garnering 2 citations—the work addresses a foundational problem in the field: the disconnect between state-of-the-art forecasting models and their practical deployment in closed-loop systems. Su’s contributions are particularly relevant for researchers working on integrated autonomy stacks, behavior prediction, and motion planning. His approach signals a shift toward more holistic, end-to-end reasoning in autonomous vehicle systems, making him a researcher to watch as the field moves from isolated benchmarks to deployable, interactive driving solutions.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Carnegie Mellon University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago