Zhenqiang Deng
Papers
2
Total Citations
25
H-Index
2
About
Zhenqiang Deng is a rising researcher in marine engineering and autonomous systems, whose work focuses on the hydrodynamic optimization of autonomous underwater vehicles (AUVs). His primary research areas include multi-objective optimization, shape design, and evolutionary algorithms applied to underwater robotics. Deng’s most significant contribution lies in pioneering the use of advanced computational methods to improve AUV performance. His landmark 2019 paper, "Optimal shape design of an autonomous underwater vehicle based on multi-objective particle swarm optimization," has earned 23 citations, demonstrating its influence in the field. In this work, he introduced a novel approach that balances competing design objectives—such as drag reduction and stability—using particle swarm optimization, setting a benchmark for efficient AUV hull design. Earlier, in 2018, he explored gene expression programming for shape optimization, laying foundational groundwork. Deng’s research is notable for bridging theoretical optimization algorithms with practical engineering challenges, offering tools that reduce design time and enhance vehicle endurance. His achievements are particularly relevant for students and researchers interested in computational design, marine robotics, and sustainable ocean exploration technologies.
Research Focus
Key Achievements
Top Papers
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