Zhenhua Yu

Xi'an University of Science and Technology

Papers

Total Citations

H-Index

About

Zhenhua Yu is a leading researcher in artificial intelligence and network security, with a primary focus on detecting malicious social robot accounts in online social networks. His most cited work, "Social Robot Detection Method with Improved Graph Neural Networks" (2024), addresses a critical cybersecurity challenge: the proliferation of AI-controlled or human-operated bot accounts that threaten network integrity and social trust. Yu identified that existing graph neural network (GNN)-based detection methods struggle with the massive scale and complexity of social network nodes. In response, he developed an improved GNN architecture that enhances detection accuracy and efficiency, achieving 4 citations in a short time—a strong indicator of its timely relevance. His contributions are vital for safeguarding digital ecosystems, as social robots can spread misinformation, manipulate public opinion, and compromise user privacy. Yu’s research bridges advanced machine learning and practical cybersecurity, offering scalable solutions for real-world social platforms. His work is particularly notable for tackling the scalability bottleneck in GNNs, making it a valuable reference for students and researchers in AI, network science, and security.