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Computer Science

D-Index
52
Citations
12333
World Ranking
5035
National Ranking
44

Research.com Recognitions

  • Fellow of the Indian National Academy of Engineering (INAE)
  • Fellow of the Indian National Academy of Engineering (INAE)
  • Fellow of the Indian National Academy of Engineering (INAE)

Overview

Pushpak Bhattacharyya is affiliated with the Indian Institute of Technology Patna in India, contributing extensively to computer science research, particularly in artificial intelligence and related subfields.

Their research spans several fields of study, including:

  • Computer Science

With a focus on subfields such as:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Social Psychology
  • Experimental and Cognitive Psychology
  • Information Systems

The main topics covered in their work involve:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Sentiment Analysis and Opinion Mining
  • Multimodal Machine Learning Applications
  • Speech and Dialogue Systems
  • Hate Speech and Cyberbullying Detection
  • Advanced Text Analysis Techniques

Pushpak Bhattacharyya has published in a variety of venues, with the most frequent being:

  • arXiv (Cornell University)
  • IEEE Transactions on Computational Social Systems
  • ACM Transactions on Asian and Low-Resource Language Information Processing
  • Cognitive Computation
  • Knowledge-Based Systems

Recent papers authored or co-authored by them include:

  • "A Multitask Framework to Detect Depression, Sentiment and Multi-label Emotion from Suicide Notes" (2021), Cognitive Computation
  • "A Multitask Framework for Sentiment, Emotion and Sarcasm aware Cyberbullying Detection from Multi-modal Code-Mixed Memes" (2022), Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • "A Deep Multi-task Model for Dialogue Act Classification, Intent Detection and Slot Filling" (2020), Cognitive Computation
  • "EmoSen: Generating Sentiment and Emotion Controlled Responses in a Multimodal Dialogue System" (2020), IEEE Transactions on Affective Computing
  • "BERT-Caps: A Transformer-Based Capsule Network for Tweet Act Classification" (2020), IEEE Transactions on Computational Social Systems

Frequent co-authors include:

  • Asif Ekbal
  • Sriparna Saha
  • Diptesh Kanojia
  • Soumitra Ghosh

Pushpak Bhattacharyya has also contributed to book publications, including a title published by Springer Nature:

  • "Investigations in Entity Relationship Extraction" (2022)

The scientist has received recognition as a Fellow of the Indian National Academy of Engineering (INAE).

Best Publications

  • Automatic Sarcasm Detection: A Survey

    Aditya Joshi;Pushpak Bhattacharyya;Mark J. Carman

  • Harnessing Context Incongruity for Sarcasm Detection

    Aditya Joshi;Vinita Sharma;Pushpak Bhattacharyya

  • Interlingua-based English–Hindi Machine Translation and Language Divergence

    Shachi Dave;Jignashu Parikh;Pushpak Bhattacharyya

  • Multi-task Learning for Multi-modal Emotion Recognition and Sentiment Analysis

    Shad Akhtar;Dushyant Singh Chauhan;Deepanway Ghosal;Soujanya Poria

  • Feature selection and ensemble construction

    Shad Akhtar;Deepak Gupta;Asif Ekbal;Pushpak Bhattacharyya

  • A Fall-back Strategy for Sentiment Analysis in Hindi: a Case Study

    Aditya Joshi;Pushpak Bhattacharyya

  • Contextual Inter-modal Attention for Multi-modal Sentiment Analysis

    Deepanway Ghosal;Shad Akhtar;Dushyant Chauhan;Soujanya Poria

  • Are Word Embedding-based Features Useful for Sarcasm Detection?

    Aditya Joshi;Vaibhav Tripathi;Kevin Patel;Pushpak Bhattacharyya

  • Feature specific sentiment analysis for product reviews

    Subhabrata Mukherjee;Pushpak Bhattacharyya

  • The IIT Bombay English-Hindi Parallel Corpus.

    Anoop Kunchukuttan;Pratik Mehta;Pushpak Bhattacharyya

  • Sentiment Analysis in Twitter with Lightweight Discourse Analysis

    Subhabrata Mukherjee;Pushpak Bhattacharyya

  • Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis

    Dushyant Singh Chauhan;Dhanush S R;Asif Ekbal;Pushpak Bhattacharyya

  • Simple Syntactic and Morphological Processing Can Help English-Hindi Statistical Machine Translation.

    Ananthakrishnan Ramanathan;Jayprasad Hegde;Ritesh M. Shah;Pushpak Bhattacharyya

  • Is question answering an acquired skill

    Ganesh Ramakrishnan;Soumen Chakrabarti;Deepa Paranjpe;Pushpak Bhattacharya

  • Your Sentiment Precedes You: Using an author’s historical tweets to predict sarcasm

    Anupam Khattri;Aditya Joshi;Pushpak Bhattacharyya;Mark Carman

  • All-in-One: Emotion, Sentiment and Intensity Prediction using a Multi-task Ensemble Framework

    Shad Akhtar;Deepanway Ghosal;Asif Ekbal;Pushpak Bhattacharyya

  • A Hybrid Deep Learning Architecture for Sentiment Analysis

    Shad Akhtar;Ayush Kumar;Asif Ekbal;Pushpak Bhattacharyya

  • Relation Extraction : A Survey.

    Sachin Pawar;Girish K. Palshikar;Pushpak Bhattacharyya

  • Morphological Richness Offsets Resource Demand -- Experiences in Constructing a POS Tagger for Hindi

    Smriti Singh;Kuhoo Gupta;Manish Shrivastava;Pushpak Bhattacharyya

  • Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network

    Abhijit Mishra;Kuntal Dey;Pushpak Bhattacharyya

  • Cross-Lingual Sentiment Analysis for Indian Languages using Linked WordNets

    Balamurali A.R.;Aditya Joshi;Pushpak Bhattacharyya

  • A Multilayer Perceptron based Ensemble Technique for Fine-grained Financial Sentiment Analysis

    Shad Akhtar;Abhishek Kumar;Deepanway Ghosal;Asif Ekbal

Frequent Co-Authors

Asif Ekbal
Asif Ekbal Indian Institute of Technology Patna
Gholamreza Haffari
Gholamreza Haffari Monash University
Andy Way
Andy Way Dublin City University
Soujanya Poria
Soujanya Poria Nanyang Technological University
Chris Biemann
Chris Biemann Universität Hamburg
Sadao Kurohashi
Sadao Kurohashi Kyoto University
George Tsatsaronis
George Tsatsaronis Technical University of Berlin

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