Regular biography
Kijung Shin is a faculty member in the Department of Computer Science at KAIST. Their research is associated with the Kim Jaechul Graduate School of AI, and they are affiliated with the Data Mining Lab. Shin's work focuses on data mining and related areas. Their contact information includes an email address: kijungs@kaist.ac.kr, and their personal website can be found at http://kaistdata.github.io.
Scholar-generated biography
Kijung Shin is an Associate Professor at KAIST, specializing in Data Mining, Graph Mining, and Network Science. His research focuses on detecting anomalies, patterns, and structural properties in complex networks and hypergraphs. He has developed methods for fraud detection, efficient graph mining, and scalable tensor factorization. His work includes algorithms for k-core analysis, hypergraph neural networks, and incremental dense-subtensor detection. Shin's contributions address challenges in dynamic graphs, camouflage in fraud detection, and the analysis of high-dimensional data. His research emphasizes both theoretical advancements and practical applications in large-scale data analysis.