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Shreya Agarwal

Teaching Assistant , Computer Science and Engineering · INDIAN INSTITUTE OF INFORMATION TECHNOLOGY

https://researchid.co/shreya_agarwal_123
@iiitsurat.ac.in
7Scopus Publications
21Google Scholar Citations
2Google Scholar h-index
1Google Scholar i10-index

Research Interests

Natural Language Processing in Indian languages

Biography

Shreya Agarwal is a Teaching Assistant in the Computer Science Department at IIIT-Surat. She has a strong academic background, with a B.Tech and a Master's in Science, in Computer Science, from Dr. APJ Abdul Kalam Technical University and JK Institute of Applied Physics and Technology, respectively. Her research interests lie in Natural Language Processing (NLP), and her recently submitted P.hD. thesis focuses on developing anaphora resolution systems for Indian languages. Shreya is an active member of the academic community, having participated in generative AI workshops with IIT-Ghandhinagar (organised by the ACM and sponsored by Microsoft) and advanced NLP courses at IIIT-Hyderabad. In addition to her core research, she has also studied and presented on the topic of bias in automated systems against people with disabilities. Her work was featured at a two-day national seminar, "The Past, Present and Future of Disability-Inclusive India: Celebrating 75 Years of India’s Indepe

Education

B.Tech CSE, M.Sc CSE, PhD in NLP

Recent Scopus Publications

  1. Harnessing AI for Health and Knowledge: An Investigation into Machine and Deep Learning Models for Medical and Textual Data
    SN Computer Science, 2025
  2. A Hybrid Stacked Ensemble Model for Resolving Pronominal Anaphoric Ambiguity in Hindi Discourse
    SN Computer Science, 2025
  3. Unsupervised hindi word sense disambiguation using graph-based centrality measures
    Iaes International Journal of Artificial Intelligence, 2024
  4. A Hybrid Framework for Implementing Modified K-Means Clustering Algorithm for Hindi Word Sense Disambiguation
    Communications in Computer and Information Science, 2024
  5. Information Extraction for Design of a Multi-feature Hybrid Approach for Pronominal Anaphora Resolution in a Low Resource Language
    Communications in Computer and Information Science, 2024

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