Zhichao Hong

Jiangsu University of Science and Technology

Papers

Total Citations

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About

Zhichao Hong is a researcher at the forefront of applying artificial intelligence and deep learning to critical environmental and autonomous systems challenges. His primary research areas encompass computer vision for environmental monitoring, deep reinforcement learning for autonomous control, and underwater robotics. Hong’s most impactful contribution is the development of an improved underwater trash detection model based on YOLOv8, detailed in his highly cited 2024 paper (74 citations). This work addresses the pressing issue of anthropogenic waste in aquatic environments by enhancing detection accuracy and efficiency, directly supporting robotic clean-up efforts to mitigate pollution’s impact on human health and ecosystems. Additionally, Hong explores autonomous navigation through his 2025 research on ship trajectory control using deep reinforcement learning, tackling challenges in adaptive control for maritime applications. His work bridges the gap between advanced AI methodologies and real-world environmental and engineering problems, demonstrating significant potential for practical deployment. With a growing citation record and a focus on high-impact, application-driven research, Hong is establishing himself as a promising contributor to the fields of environmental AI and autonomous systems.