Shweta Yadav

Computer Science , University of Illinois Chicago (UIC), IL, USA.

I am an Assistant Professor of Computer Science at the University of Illinois Chicago (UIC). Previously, I served as a Bridge to the Faculty (B2F) fellow in the Computer Science (CS) Department at UIC. I have also worked as a postdoctoral research fellow at the U.S. National Library of Medicine, National Institutes of Health (NIH). I earned my Ph.D. degree in computer science from the Indian Institute of Technology Patna, India.

My research interests lie at the intersection of Natural Language Processing, Healthcare-informatics, Biomedical Text Mining, and Computational Social Science. I aim to develop effective and efficient machine learning algorithms to accelerate the development of artificial intelligence in the healthcare and medical domains. I have a strong commitment to interdisciplinary collaboration and have experience working on emerging real-world problems in healthcare and social sciences.

My current research works focus on developing computational methods for medical document summarization, disease progression, and prediction of health outcomes from electronic health records and social media.


Jun, 2023 Excited to announce that I will be starting as an Assistant Professor of Computer Science at University of Illinois Chicago in Fall 2023!!
Jun, 2023 Research Assistantships Available: I am seeking highly motivated students, RAs, and interns. Please send me an email if you are interested in working with me at the intersection of NLP and ML, with a specific focus on biomedical and healthcare domain.
May, 2023 Our paper “Towards Identifying Fine-Grained Depression Symptoms from Memes” has been accepted at ACL 2023.
Jan, 2023 Please see our paper on consumer health question summarization accepted at The Web Conference 2023 (formerly WWW).
Sep, 2022 Two long papers accepted in the COLING 2022.

selected publications

  1. ACL
    Towards Identifying Fine-Grained Depression Symptoms from Memes
    Shweta Yadav, Cornelia Caragea, Chenye Zhao, Naincy Kumari, Marvin Solberg, and Tanmay Sharma
    In the Proceedings of the Association for Computational Linguistics (ACL) 2023
  2. WWW
    Towards Understanding Consumer Healthcare Questions on the Web with Semantically Enhanced Contrastive Learning
    Shweta Yadav, Stefan Cobeli, and Cornelia Caragea
    In the Proceedings of the ACM Web Conference (WWW) 2023
    Towards Summarizing Healthcare Questions in Low-Resource Setting
    Shweta Yadav, and Cornelia Caragea
    In the Proceedings of the 29th International Conference on Computational Linguistics (COLING) 2022
  4. ACL
    Reinforcement Learning for Abstractive Question Summarization with Question-aware Semantic Rewards
    Shweta Yadav, Deepak Gupta, Asma Ben Abacha, and Dina Demner-Fushman
    In ACL 2021
  5. ACL
    Multimodal Graph-based Transformer Framework for Biomedical Relation Extraction
    Sriram Pingali, Shweta Yadav, Pratik Dutta, and Sriparna Saha
    In ACL Findings 2021
  6. JBI
    Question-aware transformer models for consumer health question summarization
    Shweta Yadav, Deepak Gupta, Asma Ben Abacha, and Dina Demner-Fushman
    Journal of Biomedical Informatics 2022
    “When they say weed causes depression, but it’s your fav antidepressant”: Knowledge-aware Attention Framework for Relationship Extraction
    Shweta Yadav, Usha Lokala, Raminta Daniulaityte, Krishnaprasad Thirunarayan, Francois Lamy, and Amit Sheth
    PLoS one 2021
  8. ACL
    A Unified Multi-task Adversarial Learning Framework for Pharmacovigilance Mining
    Shweta Yadav, Asif Ekbal, Sriparna Saha, and Pushpak Bhattacharyya
    In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) 2019
  9. The Web (WWW)
    EDarkFind: Unsupervised Multi-View Learning for Sybil Account Detection
    Ramnath Kumar, Shweta Yadav, Raminta Daniulaityte, Francois Lamy, Krishnaprasad Thirunarayan, Usha Lokala, and Amit Sheth
    In Proceedings of The Web Conference 2020 (WWW 2020) 2020
    Relation extraction from biomedical and clinical text: Unified multitask learning framework
    Shweta Yadav, Srivastsa Ramesh, Sriparna Saha, and Asif Ekbal
    IEEE/ACM Transactions on Computational Biology and Bioinformatics 2020