New Interested in a scientist / researcher / intern position @ Wipro AI! Drop me an email with your CV.
New Receipient of Outstanding Research paper Award @EMNLP 2023 for Counter Turing Test (CT2): AI-Generated Text Detection is Not as Easy as You May Think - Introducing AI Detectability Index (ADI)
New Our work on Hallucination (The Troubling Emergence of Hallucination in Large Language Models - An Extensive Definition, Quantification, and Prescriptive Remediations published @EMNLP 2023) got covered by The Washington Post -> link

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Research Experience at Samsung Research India

Context Sensitive Sentiment Analysis & Online Contextual Advertising using Sentiment Analysis

 

Duration
January, 2013-June, 2013
 
Position

Chief Engineer

Context Sensitive Sentiment Analysis

Aim
The aim of the in-house project is to develop sentimentally intelligent virtual agent for next generation Galaxy series. The agent will be capable to recognize multi-modal emotion from video/image, speech and text from social medias like twitter and Facebook.
Online Contextual Advertising using Sentiment Analysis
Aim
The aim of the project is to develop Android apps, will promote sentimentallycontextual ads particularly for Samsung products. (Write me for more information)

 

PostDoctoral Experience ERCIM "ALAIN BENSOUSSAN" FELLOWSHIP

ERCIM "ALAIN BENSOUSSAN" FELLOWSHIP @ Norwegian University of Science and Technology (NTNU), Trondheim, Norway

 

Duration
January, 2012-December, 2012
 
Host

Prof. Björn Gamback

 
Research

Current sentiment analysis systems rely on static (context independent) sentiment lexica with proximity based fixed-point prior polarities. However, sentiment orientation changes with context and these lexical resources give no indication of which value to pick at what context. The general trend is to pick the highest one, but which that is may vary at context. To overcome the problems of the present proximity-based static sentiment lexicon techniques, Dr. Das’s and Prof. Gamback proposed a new way to represent sentiment knowledge in a Vector Space Model. This model can store dynamic prior polarity with varying contextual information. The representation of the sentiment knowledge in the Conceptual Spaces of distributional Semantics is termed Sentimantics.

*** ERCIM Scientific Report of my fellowship work.

 
Research Visits
 
Teaching Course instructor for an elective course “The Sentimental Machine” for Masters Students at NTNU, Fall-2012, taught by Dr. Das with Prof. Björn Gamback.

 

The Research Projects I Worked For (During my PhD @ JU)

Sentiment Analysis Where AI Meets Psychology (SAAIP)-Indo-Japan Collaboration

 

Duration
16th September, 2011-31st December, 2011
 
Aim

Development of an application tool for Psychiatric Analysis for patients. This tool will help doctors to detect psychiatric sentiment analysis as well as general people will be benefited from this.

 
Partners
Prof. Manabu Okumura from Precision and Intelligence Laboratory, Advanced Information Processing Division: Okumura Group Tokyo Institute of Technology and Prof. Sivaji Bandyopadhyay from CSE Department, Jadavpur University are the Research Leaders of this project.
 
Activities

1 month (19th Feb-31st March, 2011) visit @ Precision and Intelligence Laboratory, Tokyo Institute of Technology

Organized Worksop: Sentiment Analysis Where AI Meets Psychology (SAAIP) held with JCNLP 2011, November13, 2011, Chiang Mai, Thailand

 

English to Indian Languages Machine Translation (EILMT)-National Consortia Project

 

Duration
1st July, 2010-31st August, 2010
 
Aim

The EILMT system aims to design and deploy a Machine Translation System from English to Indian Languages in Tourism and Healthcare Domains. The project is funded by Department of Information Technology, MCIT, Government of India. The chosen language pairs are listed below:

English--Tamil
English--Telugu
English--Marathi
English--Bengali (Responsible for)
English--Tamil
English--Urdu
English--Kannada
English--Punjabi
English--Malayalam

 
Partners
 
Activities

XMy institute was mainly responsible for Statistical Machine Translation (SMT) for English-Bengali language pair.

XI designed modules for automatic cross-linking of English and Bengali synsets. .

Indian Languages to Indian Language machine Translation Project (IL-ILMT)-National Consortia Project

 

Duration
16th October, 2006-30th June, 2010
 
Aim

The 'ILMT' system is a machine translation system which produces machine translation (MT) from one Indian language (IL) to another Indian language. The system is bi-directional and works in (a) general domain and (b) tourism and pilgrimage. This consortium project is funded by Ministry of Communication and Information Technology, Technology Development for Indian Languages. The chosen language pairs are listed below:

Tamil--Hindi
Telugu--Hindi
Marathi--Hindi
Bengali--Hindi (Responsible for)
Tamil--Telugu
Urdu--Hindi
Kannada--Hindi
Punjabi--Hindi
Malayalam--Tamil

 
Partners
 
Activities

My institute was mainly responsible for language