Keke Long
Papers
1
Total Citations
6
H-Index
1
About
Keke Long is a leading researcher in the field of connected and automated vehicles (CAVs), with a primary focus on intelligent transportation systems and adaptive control. Her most notable contribution is the development of online adaptive platoon control strategies that integrate physics-enhanced residual learning, enabling real-time coordination and safety optimization for vehicle platoons. This work, published in 2025 and already garnering 6 citations, demonstrates her ability to bridge theoretical control frameworks with practical, data-driven solutions—a critical step toward realizing fully autonomous, cooperative driving. Long’s research addresses key challenges in CAV platooning, such as robustness to dynamic traffic conditions and communication delays, by leveraging hybrid models that combine physical principles with machine learning. Her achievements highlight a commitment to advancing safe, efficient, and scalable autonomous systems, making her a rising voice in the transportation engineering community. For students and researchers, Long’s work exemplifies how integrating domain knowledge with modern AI can yield transformative solutions for real-world mobility challenges.
Research Focus
Key Achievements
Top Papers
- 1