Zemin Eitan Liu
Papers
2
Total Citations
44
H-Index
2
About
Zemin Eitan Liu is a rising force in the field of intelligent transportation systems, with a focused expertise in multi-agent reinforcement learning (MARL) for connected and automated vehicles (CAVs). His research addresses one of the most pressing challenges in autonomous mobility: how to coordinate multiple CAVs to achieve safe, efficient, and eco-friendly traffic flow. Liu’s most-cited work, a comprehensive survey published in 2025, has already garnered 37 citations, reflecting the timely importance of his synthesis of MARL advancements for CAV control. In this paper, he systematically reviews how decentralized learning algorithms can overcome the complexity of interconnectivity and coordination among autonomous agents—a critical step toward real-world deployment. An earlier version of this work (2023, 7 citations) laid the groundwork, establishing Liu as a key voice in this niche. His contributions are particularly notable for bridging theoretical reinforcement learning with practical vehicular applications, offering a roadmap for future research. As a researcher, Liu is shaping the next generation of traffic systems, where vehicles learn to cooperate autonomously, promising safer roads and reduced emissions.
Research Focus
Key Achievements
Top Papers
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- 2