Zekai Zhang

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About

Zekai Zhang is an emerging researcher specializing in unmanned underwater vehicles (UUVs), autonomous systems, and marine robotics. His work addresses the critical challenges posed by complex and time-varying underwater environments, with a particular focus on developing robust simulation platforms and intelligent autonomy frameworks for UUV applications. Zhang's most notable contribution is his design and implementation of a modular UUV simulation platform (2022), which has garnered 11 citations and represents a significant step forward in enabling researchers to repeatedly evaluate and refine autonomy schemes without the cost and risk of real-world testing. More recently, his development of UPEGSim (2025), a reinforcement learning-enabled simulator dedicated to the underwater pursuit-evasion game, demonstrates his commitment to advancing multi-agent coordination and strategic decision-making in underwater settings — capabilities fundamental to exploration, surveillance, and data collection missions. By bridging simulation technology with reinforcement learning, Zhang is helping to accelerate the development of smarter, safer autonomous underwater systems. His growing body of work, with a combined 15 citations across just two key publications, signals a promising research trajectory with meaningful implications for the future of ocean robotics and autonomous marine intelligence.