Zengbao Zhang

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Total Citations

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About

Dr. Zengbao Zhang is a leading researcher at the forefront of intelligent mining and sustainable resource processing, with a primary focus on deep learning applications in mineral sorting and green coal technology. His most impactful work, the "Design and application of coal gangue sorting system based on deep learning" (2024), has already garnered 11 citations, reflecting its timely contribution to the industry’s shift toward intelligent, information-based, and professional sorting systems. Dr. Zhang’s major contribution lies in advancing the modernization of coal-washing plants, integrating artificial intelligence to enhance sorting accuracy while promoting green and low-carbon development. By accelerating the transition from traditional methods to smart, eco-friendly systems, his research directly supports the construction of a modern economic system aligned with sustainable development goals. Dr. Zhang’s work is notable for bridging cutting-edge AI technology with practical industrial applications, offering a scalable solution to reduce environmental impact and improve resource efficiency. For students and researchers exploring the intersection of deep learning and environmental engineering, Dr. Zhang’s profile exemplifies how innovative research can drive both technological progress and ecological responsibility.