Jiawei Han’s lab focuses on discovering effective methods for mining structures from massive unstructured text data and has developed a set of effective and scalable methods. Since 1997, his research has focused on data mining, text mining, information network analysis, database systems, and the applications of these technologies, including biomedical text mining and biomedical data analysis. In the past two years, Dr. Han has developed tools and algorithms for the search and mining of PubMed. His leadership and unparalleled experience in text mining are crucial to the success of his work. Han leads the development of algorithms for automated information extraction and claim mining from biomedical and cancer research literature. He also provides leadership for algorithm assessment and application development.
Over the past 30 years, Han has established a successful research program on data mining and has demonstrated a strong track record of productivity with over 800 publications. Based on data from Microsoft Academic Search, Dr. Han is the most cited author in the Data Mining research field; his H-index is 162 (ranked top-3 among Computer Science researchers internationally) and i10-index is 712, according to Google Scholar.
Han is affiliated with the Carl R. Woese Institute for Genomic Biology, the Information Trust Institute, and the Beckman Institute for Advanced Science and Technology. He is also a Professor in Electrical and Computer Engineering.