Jingzehua Xu
Papers
2
Total Citations
7
H-Index
2
About
Jingzehua Xu is an emerging researcher specializing in unmanned underwater vehicles (UUVs) and reinforcement learning-based simulation systems for autonomous underwater robotics. His work focuses on bridging the gap between theoretical algorithm development and real-world underwater applications by creating sophisticated simulation environments that address the practical challenges facing UUV development, including high hardware costs, safety constraints, and insufficient training data. Among his most notable contributions is UPEGSim, a reinforcement learning-enabled simulator dedicated to underwater pursuit-evasion games, which has garnered 4 citations since its 2025 publication. This work demonstrates his commitment to tackling complex multi-agent underwater scenarios that are foundational to broader ocean tasks such as exploration and data collection. His complementary platform, UUVSim, an intelligent modular simulation framework published in 2024 with 3 citations, further establishes his expertise in building flexible, learning-oriented environments for UUV training and verification. Though early in his career, Xu's focused contributions to underwater autonomous systems simulation represent meaningful advances in making UUV research more accessible, safer, and data-rich — a foundation that positions him as a promising voice in marine robotics and intelligent systems research.
Research Focus
Key Achievements
Top Papers
- 1
- 2