World's Best Scientists 2026 revealed!

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Computer Science

D-Index
54
Citations
16569
World Ranking
4464
National Ranking
39

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

Sunita Sarawagi is affiliated with the Indian Institute of Technology Bombay, India. Their research primarily lies within the field of Computer Science, focusing on Artificial Intelligence with additional work in Signal Processing, Computer Vision and Pattern Recognition, Computer Networks and Communications, and Management Science and Operations Research.

Their contributions span several topics that include Natural Language Processing Techniques, Topic Modeling, Machine Learning and Algorithms, Gaussian Processes and Bayesian Inference, Machine Learning and Data Classification, Semantic Web and Ontologies, and Advanced Database Systems and Queries.

They have published extensively, with a significant number of works appearing in notable venues such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Proceedings of the VLDB Endowment, and the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), as well as ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing.

  • Efficient Domain Generalization via Common-Specific Low-Rank Decomposition (2020, arXiv (Cornell University))
  • Deep indexed active learning for matching heterogeneous entity representations (2021, Proceedings of the VLDB Endowment)
  • Learning from Rules Generalizing Labeled Exemplars (2020, arXiv (Cornell University))
  • Overlap-based Vocabulary Generation Improves Cross-lingual Transfer Among Related Languages (2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers))
  • Robust Data Programming with Precision-guided Labeling Functions (2020, Proceedings of the AAAI Conference on Artificial Intelligence)

Frequent collaborators include Abhijeet Awasthi, Vihari Piratla, Preethi Jyothi, Lokesh Nagalapatti, and Partha Talukdar.

Sunita Sarawagi has been recognized as a Fellow of the Indian National Academy of Engineering (INAE).

Best Publications

  • Information Extraction

    Sunita Sarawagi

  • Discriminative Methods for Multi-labeled Classification

    Shantanu Godbole;Sunita Sarawagi

  • On the Computation of Multidimensional Aggregates

    Sameet Agarwal;Rakesh Agrawal;Prasad Deshpande;Ashish Gupta

  • Interactive deduplication using active learning

    Sunita Sarawagi;Anuradha Bhamidipaty

  • Modeling multidimensional databases

    R. Agrawal;A. Gupta;S. Sarawagi

  • Semi-Markov Conditional Random Fields for Information Extraction

    Sunita Sarawagi;William W. Cohen

  • Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications

    Sunita Sarawagi;Shiby Thomas;Rakesh Agrawal

  • Discovery-driven exploration of OLAP data cubes

    S. Sarawagi;R. Agrawal;N. Megiddo

  • Automatically Extracting Structure from Free Text Addresses.

    Vinayak R. Borkar;Kaustubh Deshmukh;Sunita Sarawagi

  • Annotating and searching web tables using entities, types and relationships

    Girija Limaye;Sunita Sarawagi;Soumen Chakrabarti

  • Efficient set joins on similarity predicates

    Sunita Sarawagi;Alok Kirpal

  • Efficient organization of large multidimensional arrays

    S. Sarawagi;M. Stonebraker

  • Record linkage: similarity measures and algorithms

    Nick Koudas;Sunita Sarawagi;Divesh Srivastava

  • Automatic segmentation of text into structured records

    Vinayak Borkar;Kaustubh Deshmukh;Sunita Sarawagi

  • Generalizing Across Domains via Cross-Gradient Training

    Shiv Shankar;Vihari Piratla;Soumen Chakrabarti;Siddhartha Chaudhuri

  • Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods

    William W. Cohen;Sunita Sarawagi

  • The Claremont report on database research

    Rakesh Agrawal;Anastasia Ailamaki;Philip A. Bernstein;Eric A. Brewer

  • The Claremont report on database research

    Rakesh Agrawal;Anastasia Ailamaki;Philip A. Bernstein;Eric A. Brewer

  • Mining Surprising Patterns Using Temporal Description Length

    Soumen Chakrabarti;Sunita Sarawagi;Byron Dom

  • Trainable Calibration Measures for Neural Networks from Kernel Mean Embeddings

    Aviral Kumar;Sunita Sarawagi;Ujjwal Jain

  • Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining

    Ying Li;Bing Liu;Sunita Sarawagi

Frequent Co-Authors

Soumen Chakrabarti
Soumen Chakrabarti Indian Institute of Technology Bombay
Rakesh Agrawal
Rakesh Agrawal Purdue University West Lafayette
Surajit Chaudhuri
Surajit Chaudhuri Microsoft (United States)
Alon Halevy
Alon Halevy Facebook (United States)
Raghu Ramakrishnan
Raghu Ramakrishnan Microsoft (United States)
Gerhard Weikum
Gerhard Weikum Max Planck Institute for Informatics
Yannis E. Ioannidis
Yannis E. Ioannidis National and Kapodistrian University of Athens
Hector Garcia-Molina
Hector Garcia-Molina Stanford University
Alexander S. Szalay
Alexander S. Szalay Johns Hopkins University

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