Soumen Chakrabarti

Professor, Computer Science & Engineering

Soumen Chakrabarti received his B.Tech in Computer Science from the Indian Institute of Technology, Kharagpur, in 1991 and his M.S. and Ph.D. in Computer Science from the University of California, Berkeley in 1992 and 1996. At Berkeley he worked on compilers and runtime systems for running scalable parallel scientific software on message passing multiprocessors. He was a Research Staff Member at IBM Almaden Research Center from 1996 to 1999, where he worked on the Clever Web search project and led the Focused Crawling project. In 1999 he joined the Department of Computer Science and Engineering at the Indian Institute of Technology, Bombay. In Spring 2004 he was Visiting Associate professor at Carnegie-Mellon University. During 2014-2016 he was Visiting Scientist at Google, Mountain View.

He has published in the WWW, ACL, SIGIR, SIGKDD, EMNLP, NeurIPS, ICLR, ICML, SIGMOD, VLDB, ICDE, SODA, STOC, SPAA and other conferences as well as Scientific American, IEEE Computer, VLDB and other journals. He won the best paper award at WWW 1999. He was a coauthor on the best student paper at ECML 2008. His work on keyword search in databases got the 10-year influential paper award at ICDE 2012. He won the Jagadis Bose National Fellowship in 2019, the Shanti Swarup Bhatnagar prize in 2014, and is a fellow of the Indian National Academies of Engineering and Science. He holds thirteen US patents on Web-related inventions. He is also the author of one of the earliest books on Web search and mining.

He has served as technical advisor to search companies and vice-chair or program committee member for WWW, SIGIR, SIGKDD, NeurIPS, ICML, VLDB, ICDE, SODA and other conferences, and guest editor or editorial board member for DMKD and TKDE journals. He has served as inaugural program chair for WSDM 2008 and program chair for WWW 2010.

His current research interests include integrating, searching, and mining text and graph data models, exploiting types and relations in search, and knowledge graph representation.