Sagar Indurkhya, PhD

About

I completed my doctorate in Computer Science, with a focus on Computational Linguistics, at MIT. In my doctoral thesis, supervised by Prof. Robert C. Berwick at the Laboratory for Information and Decision Systems, I developed a computational model of language acquisition within the framework of the Minimalist Program. Prior to this I completed an M. Eng in EECS in 2015 and a B.S. in Computer Science and Engineering in 2012, both from MIT. I graduated from the North Carolina School of Science and Mathematics in 2007.

Publications

  1. Indurkhya, S. (2023). A Procedure for Inferring a Minimalist Lexicon from an SMT Model of a Language Acquisition Device. Proceedings of 16th edition of the International Conference on Grammatical Inference (ICGI), in Proceedings of Machine Learning Research pp. 217:35-58. (abstract, pdf, & code)
  2. Indurkhya, S. (2022). Parsing as Deduction Revisited: Using an Automatic Theorem Prover to Solve an SMT Model of a Minimalist Parser. In Proceedings of the 26th Conference on Computational Natural Language Learning (CoNLL), pp. 157–175, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics (ACL). (abstract, pdf, & code)
  3. Indurkhya, S. (2022). Modeling the Ordering of English Adjectives using Collaborative Filtering. In Proceedings of the 5th International Conference on Natural Language and Speech Processing (ICNLSP 2022), pages 156–167, Trento, Italy. Association for Computational Linguistics (ACL). (DOI & pdf)
  4. Indurkhya, S. (2022). Incremental Acquisition of a Minimalist Grammar using an SMT-Solver. Proceedings of the Society for Computation in Linguistics, 5(1), 212-216. (abstract & pdf)
  5. Indurkhya, S. and Berwick R. C. (2021), Evaluating the Cognitively-Related Productivity of a Universal Dependency Parser, 2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC), 2021, pp. 7-15. (pdf & Best Paper Award)
  6. Indurkhya, S. (2021) Using Collaborative Filtering to Model Argument Selection. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021) (pp. 629–639). (abstract & pdf)
  7. Indurkhya, S., Yankama, B., & Berwick, R. C. (2021) Evaluating Universal Dependency Parser Recovery of Predicate Argument Structure via CompChain Analysis. Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics (pp. 116–128). Association for Computational Linguistics (ACL). (abstract, pdf & talk)
  8. Indurkhya, S. (2021). Solving for Syntax (Doctoral dissertation, Massachusetts Institute of Technology). (abstract & pdf)
  9. Indurkhya, S. (2020) Inferring Minimalist Grammars with an SMT-Solver, Proceedings of the Society for Computation in Linguistics: Vol. 3 , Article 56. (abstract & pdf)
  10. Indurkhya, S. Modeling minimalist grammars with SMT. Proceedings of the Seventh Annual Conference on Cognitive Systems. (2019) (poster)
  11. Indurkhya, S. (2019) Automatic inference of minimalist grammars using an SMT-solver. Learning and Automata (LearnAut) Workshop, Logic in Computer Science (LICS) 2019. (abstract & pdf)
  12. Sprouse, J., Yankama, B., Indurkhya, S., Fong, S., & Berwick, R. C. Colorless green ideas do sleep furiously: gradient acceptability and the nature of the grammar. The Linguistic Review. (2018) (DOI)
  13. Indurkhya, S. (2015) Acquiring Minimalist Grammars via Constraint Satisfaction. (M. Eng Thesis, Massachusetts Institute of Technology). (abstract & pdf)
  14. Sprouse, J., Indurkhya, S., Fong, S., & Berwick, R.C. (2015) Colorless green ideas do sleep furiously: the necessity of grammar. NELS-46, NELS 46, October 16-18, 2015. Concordia University.
  15. Berwick, R., & Indurkhya, S. (2013) Language evolution is not like genomic evolution: phonemic diversity fails to detect language evolution out of Africa. Proceedings of the 19th International Congress of Linguists, July, Geneva, Switzerland:International Congress of Linguists.
  16. Indurkhya, S., & Beal, J. (2010). Reaction factoring and bipartite update graphs accelerate the Gillespie algorithm for large-scale biochemical systems. PloS one, 5(1), e8125. (pdf)
  17. Reza, F., Chandran, K., Feltz, M., Heinz, A., Josephs, E., O'Brien, P., Van Dyke, B., Chung, H., Indurkhya, S., Lakhani, N. & Lee, J. (2007) Engineering novel synthetic biological systems. IET Synthetic Biology, 1(1), pp.48-52. (abstract & pdf)

Industry Talks and Articles

Teaching Assistantships (at MIT)

  • 6.863J - Natural Language Processing - Spring 2018 - taught by Prof. Robert. C. Berwick
  • 6.006 - Introduction to Algorithms - Fall 2017 - taught by Profs. Silvio Micali, Muriel Medard and Dr. Jason Ku.
  • 6.046 - Design and Analysis of Algorithms - Spring 2017 - taught by Profs. Debayan Gupta, Aleksander Madry, and Bruce Tidor.
  • 6.878 - Advanced Computational Biology - Fall 2016 - taught by Prof. Manolis Kellis.
  • 6.049 - Computational Evolutionary Biology - Spring 2016 - taught by Profs. David Bartel and Robert C. Berwick.
  • 6.s083 - Language and Computation - Fall 2015 - taught by Prof. Robert C. Berwick.

Resume/CV

If you would like a copy of my Resume or CV, please contact me.

Contact

You can reach me via LinkedIn or by emailing me at either indurks@mit.edu (checked frequently) or sagar.indurkhya@gmail.com.

Last updated on April 28th, 2024.