Nanda Kambhatla has nearly 17 years of research experience in the
areas of Natural Language Processing (NLP), text mining, information
extraction, dialog systems, and machine learning. He holds 6 U.S
patents and has authored over 30 publications in books, journals, and
conferences in these areas. Nanda holds a B.Tech in Computer Science
and Engineering from the Institute of Technology, Benaras Hindu
University, India, and a Ph.D in Computer Science and Engineering from
the Oregon Graduate Institute of Science & Technology, Oregon, USA.
Currently, Nanda is the manager of the Data Analytics Group at IBM's
India Research Lab (IRL), Bangalore. The group is focused on research
on machine translation, Natural Language Processing, text analysis and
machine learning techniques for developing analytics solutions to help
IBM's services divisions. Most recently, Nanda was the manager of the
Statistical Text Analytics Group at IBM's T.J. Watson Research Center,
the Watson co-chair of the Natural Language Processing PIC, and the
task PI for the Language Exploitation Environment (LEE) subtask for
the DARPA GALE project. He has been leading the development of
information extraction tools/products and his team has achieved top
tier results in successive Automatic Content Extraction
(ACE) evaluations conducted
by NIST for extracting entities, events and relations from text from
multiple sources, in multiple languages and genres.
Earlier in his career, Nanda has worked on natural language web-based
and spoken dialog systems at IBM. Before joining IBM, he has worked on
information retrieval and filtering algorithms as a senior research
scientist at WiseWire Corporation, Pittsburgh and on image compression
algorithms while working as a postdoctoral fellow under Prof. Simon
Haykin at McMaster University, Canada.
Nanda's research interests are focused on NLP and technology solutions
for creating, storing, searching, and processing large volumes of
unstructured data (text, audio, video,
etc.) and specifically on applications of statistical learning
algorithms to these tasks.