Gargi Sharma


BITS Pilani, Pilani Campus
B.E.(Hons.) Computer Science (2013 - 2017)

Work Experience

July 2017 - September 2017

Linux Kernel Foundation
May 2017 - July 2017

Google CodeU
March 2016 - August 2016

eBay Inc.
May 2016 - July 2016

Quant One Technologies(formerly Hedge Capital Quants Advisory, LLC)
May 2015 - July 2015

Research Experience

Web Intelligence and Social Computing(WiSoc) Lab

Teaching Experience

Computer Networks CS F303
First Degree teaching Assistant

Parallel Computing CS F422
First Degree Teaching Assistant


ATSSI: Abstractive Text Summarization Using Sentiment Infusion
In this paper, we proposed a graph based technique that generates summaries of redundant opinions and uses sentiment analysis to combine the statements. The summaries thus generated were abstraction based summaries and were well formed to convey the gist of the text.

Deep Paraphrase Detection in Indian Languages
This paper presents an approach to the problem of paraphrase identification in English and Indian languages using Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN). The lack of NLP resources for Indian languages has been a deterrent to the advancement of paraphrase detection task in Indian languages. Three approaches have been proposed, a simple CNN that uses word embeddings as input, a CNN that uses WordNet scores as input and RNN based approach with both LSTM and bi-directional LSTM.