Dr. Charu Aggarwal is a Distinguished Research Staff Member at IBM, and a Fellow of the ACM, IEEE, and SIAM. Dr. Aggarwal has made pioneering contributions to the field of data mining. He is noted for the unusual breadth and versatility of his contributions to data mining across many different topics. His major areas of research contribution include high-dimensional data, privacy, data streams, uncertain data, graphs, text mining, and social networks. In addition, he has authored or edited several books, including a comprehensive textbook on data mining.
Several of Dr. Aggarwal's ideas are seminal in terms of their impact, which is reflected in the tens of thousands of citations he has received in the aggregate over the years. In particular, his work on the use of projected/subspace frameworks for high dimensional analysis has been adopted in several problems like nearest neighbor search and outlier detection. He has made significant research contributions to the field of data streams during its nascent years, long before the importance of the big-data paradigm was realized. He has also made seminal contributions to the field of privacy, and has received an EDBT Test-Of-Time Award. His significant contributions to outlier analysis include the creation of the new area of subspace outlier detection and a well-known book on the topic. Several of his ideas have also been implemented by third parties in open-source packages and many of his algorithms are included in graduate-level textbooks.
In addition to his fundamental technical contributions, Dr. Aggarwal has also made extensive contributions to services in the field of data mining through journal editorships and conference organization.
2015 IEEE ICDM Nomination and Evaluation Committees