Fu Luoyi

Fu Luoyi is a faculty member in the Department of Computer Science at Shanghai Jiao Tong University. His research focuses on social and academic network analysis, including the study of evolving network topology, information transmission, user privacy protection, and knowledge discovery in academic big data. He has contributed to the development of data spectrum analysis, inspired by Newton's prism theory, to visualize and interpret complex data. Fu has held visiting scholar positions at Texas A&M University and the University of California, Los Angeles, and has received several awards, including the National Natural Science Foundation Excellent Youth Fund and the ACM China Outstanding Doctoral Thesis Award. His work spans theoretical and applied research in computer science, with a focus on graph theory, machine learning, and data analysis.

Fu Luoyi is a researcher at Shanghai Jiao Tong University with expertise in social networks, random graphs, wireless sensor networks, and scaling laws. Their work explores the dynamics of social interactions, the structural properties of complex networks, and the optimization of communication in distributed systems. Fu's research includes topics such as VANETs, rumor influence minimization, and geoscience knowledge understanding. They have contributed to the development of models for temporal knowledge graph reasoning, spatio-temporal graph learning, and uncertainty-based hallucination detection. Their studies also address challenges in mobile edge computing, UAV-assisted VANET systems, and indoor localization using iBeacon and inertial sensors.