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.