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Vivek Kulkarni

Postdoctoral Scholar in Computer Science

Stanford University

I am a post-doctoral research scholar at Stanford advised by Prof. Dan Jurafsky and Prof. Daniel McFarland. My research interests are at the intersection of natural language processing and computational social science. In particular, I am focused on making NLP models human-centric, socially aware, robust amd fair. I am also interested in applying NLP methods to uncover social biases through the lens of natural language.

To know more about my research, please see my Research Statement, and CV.

Interests

  • Natural Language Processing
  • Computational Linguistics
  • Computational Social Science

Education

  • PhD in Computer Science, 2017

    Stony Brook University

  • MS in Computer Science, 2014

    Stony Brook University

Recent Publications

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(2020). DialectGram: Automatic Detection of Dialectal Variation at Multiple Geographic Resolutions. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing.

(2019). TWEETQA: A Social Media Focused Question Answering Dataset. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics.

(2018). Multi-view Models for Political Ideology Detection of News Articles. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing.

(2018). Simple neologism based domain independent models to predict year of authorship. Proceedings of the 27th International Conference on Computational Linguistics.

(2017). Don't Walk, Skip!: online learning of multi-scale network embeddings. Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017.

(2017). Human Centered NLP with User-Factor Adaptation. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing.

(2016). Freshman or fresher? quantifying the geographic variation of internet language. Tenth International AAAI Conference on Web and Social Media.

(2015). Polyglot-NER: Massive multilingual named entity recognition. Proceedings of the 2015 SIAM International Conference on Data Mining.