Rajkumar Pujari - Department of Computer Science - Purdue University Skip to main content
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Rajkumar Pujari

Graduate Student

Graduate Research Assistant


Joined department: Fall 2017

Education

Bachelors in Technology (Hons.), Indian Institute of Technology, Kharagpur, Computer Science and Engineering (2014)
Ph.D., Purdue University, Computer Science (2025)

I am a Ph.D. candidate in the Department of Computer Science at Purdue University. Currently, I am actively looking for full-time NLP research positions in the industry. I work under the guidance of Prof. Dan Goldwasser. My Ph.D. thesis is about conceptualizing and building systems for contextualized pragmatic language understanding.

Specifically, I worked on frameworks for wholistic political text contextualization and cultural context grounding for conversations. I have also worked on building and benchmarking challenging evaluation datasets for contextualized political text understanding. From a technical standpoint, I worked extensively with transformer-based models, fine-tuning LLMs, large graphs, and neural architecture design. I have also spent significant time designing, collecting, and curating interesting CSS datasets for pragmatic language understanding. I am currently working on DARPA CCU program.

I interned at Microsoft Research Redmond in 2021 and Amazon Alexa Seattle in 2019. At MSR, I worked with Elnaz Nouri, Erik Oveson and Priyanka Kulkarni on building a Reinforcement Learning Guided Multi-Task Framework for Low-Resource Stereotype Detection. Our work was published as a long paper at ACL 2022. At Amazon, I worked under Kevin Small. We worked on a sports conversational multi-turn question-answering dataset.

Selected Publications

Rajkumar Pujari and Dan Goldwasser. LLM-Human Pipeline for Cultural Context Grounding of Conversations. arXiv preprint arXiv:2410.13727 (2024).
Rajkumar Pujari, Chengfei Wu, and Dan Goldwasser. “We Demand Justice!”: Towards Social Context Grounding of Political Texts. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. 2024.
Rajkumar Pujari and Dan Goldwasser. 2021. Understanding Politics via Contextualized Discourse Processing. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1353–1367, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Rajkumar Pujari, Erik Oveson, Priyanka Kulkarni, and Elnaz Nouri. 2022. Reinforcement Guided Multi-Task Learning Framework for Low-Resource Stereotype Detection. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 6703–6712, Dublin, Ireland. Association for Computational Linguistics.
Rajkumar Pujari and Dan Goldwasser. 2019. Using Natural Language Relations between Answer Choices for Machine Comprehension. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 4010–4015, Minneapolis, Minnesota. Association for Computational Linguistics.
Last Updated: Dec 4, 2020 2:04 PM

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