Satanu Ghosh

(pronounced as: Shaw-toh-nuh)

PhD Student | Computer Science | UNH

Profile Picture

About Me

I am a 3rd year PhD student of Computer Science in the University of New Hampshire, specializing in harnessing the transformative potential of Large Language Models. My research revolves around utilizing these cutting-edge models to tackle complex problems across diverse domains such as material science, healthcare, and education.

I am also motivated to explore the implications of Large Language Models in the space of diversity, equity, and inclusivity. By delving into these areas, I strive to contribute to creating a more inclusive and equitable technological landscape.

Presently, I am working with my wonderful advisor Dr. Sam Carton ( for my PhD. Previously, I did one year of my Ph.D. in the iSchool of the University of Oklahoma under the supervision of Dr. Kun Lu (

Research Interests

  • Natural Language Processing
  • Large Language Models
  • Computational Linguistics
  • Information Extraction
  • Explainability


  • Brodnik, N., Carton, S., Muir, C., Ghosh, S., Downey, D., Echlin, M. P., Pollock, T. M., & Daly, S. H. (2023). Perspective: Large Language Models in Applied Mechanics. Journal of Applied Mechanics, 1–12.
  • Ghosh, S., Ghosh, S., & Shah, C. (2023, June). Toward Connecting Speech Acts and Search Actions in Conversational Search Tasks. In 2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL) (pp. 119-131). IEEE.
  • Ghosh, S., & Lu, K. (2022). Band gap information extraction from materials science literature–a pilot study. Aslib Journal of Information Management, 75(3), 438–454.
  • Ghosh, S., & Ghosh, S. (2021a). “ Do Users Need Human-like Conversational Agents?”-Exploring Conversational System Design Using Framework of Human Needs. DESIRES, 117–127.
  • Ghosh, S., & Ghosh, S. (2021b). Classifying Speech Acts using Multi-channel Deep Attention Network for Task-oriented Conversational Search Agents. Proceedings of the 2021 Conference on Human Information Interaction and Retrieval, 267–272.
  • Ghosh, S., & Ghosh, S. (2019). Exploring the Ideal Depth of Neural Network when Predicting Question Deletion on Community Question Answering. Proceedings of the 11th Forum for Information Retrieval Evaluation, 52–55.
  • Ghosh, S., Ghosh, S., & Das, D. (2017a). Complexity metric for code-mixed social media text. Computación y Sistemas, 21(4), 693–701.
  • Ghosh, S., Ghosh, S., & Das, D. (2017b). Sentiment identification in code-mixed social media text. ArXiv Preprint ArXiv:1707.01184.
  • Ghosh, S., Ghosh, S., & Das, D. (2016a). Labeling of query words using conditional random field. ArXiv Preprint ArXiv:1607.08883.
  • Ghosh, S., Ghosh, S., & Das, D. (2016b). Part-of-speech tagging of code-mixed social media text. Proceedings of the Second Workshop on Computational Approaches to Code Switching, 90–97.
  • Ghosh, S., & Liu, J. (n.d.). OUHCIR at the NTCIR-16 Data Search 2 Task.


  • Panel member of ACM-CHIIR 2024 - SCAI workshop
  • Invited to become a PC member of ECIR 2023.
  • Paper titled "Toward Connecting Speech Acts and Search Actions in Conversational Search Tasks" nominated for best paper award at ACM/IEEE JCDL, June 2023.
  • Research internship with National Board of Medical Examiners (NBME), June 2023.
  • Received Teaching Assistantship from UNH Computer Science, August 2022 - present.
  • Admission to University of New Hampshire, August 2022.
  • Research collaboration with Stephenson Cancer Research Center, June 2022 - August 2022.
  • Received Graduate Assistantship from OU SLIS, August 2021 - May 2022.
  • Admission to the University of Oklahoma, August 2021.


Please do not hesitate to reach out to me if you have any research projects and want to collaborate with me and my advisor.
Indian Flag