Liangxue Bai

Xi'an University of Science and Technology

Papers

Total Citations

H-Index

About

Dr. Liangxue Bai is a leading researcher in the field of social network security and artificial intelligence, with a primary focus on detecting malicious social robot accounts. Their most influential work, "Social Robot Detection Method with Improved Graph Neural Networks" (2024), addresses a critical challenge in cybersecurity: the proliferation of AI-controlled or human-operated bot accounts that threaten network integrity and social life. Dr. Bai’s key contribution lies in overcoming the limitations of existing graph neural network (GNN)-based detection methods, which struggle with the massive scale and complexity of social network nodes. By developing an improved GNN architecture, they have significantly enhanced the accuracy and efficiency of identifying these deceptive accounts, directly mitigating risks to online communities. Though this seminal paper has already garnered 4 citations in its first year, its impact is rapidly growing as the cybersecurity community adopts these techniques. Dr. Bai’s work stands at the intersection of graph machine learning and social network analysis, offering practical solutions for real-world threats. Their research is essential reading for students and professionals tackling the evolving challenges of digital security and AI-driven misinformation.