Charu Aggarwal

Charu C. Aggarwal is a Distinguished Research Staff Member (DRSM) at the IBM T. J. Watson Research Center in Yorktown Heights, New York. He received his undergraduate degree in computer science from the Indian Institute of Technology at Kanpur in 1993 and his PhD from the Massachusetts Institute of Technology in 1996.

Charu has published hundreds of papers and patents in data mining, machine learning, and artificial intelligence. He has authored nine books, including graduate textbooks in the areas of machine learning, linear algebra, and artificial intelligence. Due to the commercial value of his patents, he has thrice been designated a Master Inventor at IBM. He is a recipient of the IBM Outstanding Innovation Award for his scientific contributions to privacy technology and a recipient of two IBM Outstanding Technical Achievement Awards for his research on data streams and high-dimensional data. Charu’s foundational work on high-dimensional data analysis and outlier ensembles spawned new research areas within data mining. He also made several pioneering contributions to data stream research during its nascent years, long before big data became a technological reality. He received the EDBT 2014 Test-of-Time Award for his work on condensation-based privacy-preserving data mining, which according to the award citation, is “a prime example of how far a simple idea can carry a whole line of original research .” He is also a recipient of the IEEE ICDM Research Contributions Award and the ACM SIGKDD Innovation Award, which are the two most prestigious awards for influential research contributions in data mining.

Charu has served as the general/program co-chair and associate editor of several top-tier journals and conferences. He was the editor-in-chief of ACM SIGKDD Explorations and is currently the editor-in-chief of ACM Transactions on Knowledge Discovery from Data as well as a co-editor-in-chief of ACM Books. He is a SIAM, ACM, and IEEE fellow for “contributions to knowledge discovery and data mining algorithms.”