Education

Ph.D. in Computer Science
Carnegie Mellon University, 2015
Tom Mitchell was my advisor.

M.Eng. in Computer Science
Massachusetts Institute of Technology 2009
Henry Lieberman was my thesis advisor and Saman Amarasinghe was my academic advisor.

S.B. in Computer Science, MIT (2008)

Teaching

I've been a teaching assistant for:
11-713 - Advanced NLP Seminar (CMU, Fall 2012)
15-213 - Introduction to Computer Systems (CMU, Spring 2012)
10-701 - Machine Learning (CMU, Fall 2010)
6.857 - Computer and Network Security (MIT, Spring 2009)
6.006 - Introduction to Algorithms (MIT, Fall 2008)

Miscellaneous

Binary Search Tees. Clothing for computer scientists. Funny T-shirts that only a grad student could love.

Publications

Structured Set Matching Networks for One-Shot Part Labeling Jonghyun Choi, Jayant Krishnamurthy, Aniruddha Kembhavi, Ali Farhadi. CVPR 2018. PDF / bib

Neural Semantic Parsing with Type Constraints for Semi-Structured Tables Jayant Krishnamurthy, Pradeep Dasigi, Matt Gardner. EMNLP 2017. PDF / bib

Learning a Neural Semantic Parser from User Feedback Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, Luke S. Zettlemoyer. ACL 2017. PDF / bib

Semantic Parsing to Probabilistic Programs for Situated Question Answering Jayant Krishnamurthy, Oyvind Tafjord and Aniruddha Kembhavi. EMNLP 2016. PDF / Code, Data and Online Appendix / bib

Probabilistic Models for Learning a Semantic Parser Lexicon Jayant Krishnamurthy. NAACL 2016. PDF / Data and Code / bib

Instructable Intelligent Personal Agent Amos Azaria, Jayant Krishnamurthy and Tom M. Mitchell. AAAI 2016. PDF / bib

Visually-Verifiable Textual Entailment: A Challenge Task for Combining Language and Vision Jayant Krishnamurthy Proceedings of the Fourth Workshop on Vision and Language, 2015. PDF / bib

Learning a Compositional Semantics for Freebase with an Open Predicate Vocabulary Jayant Krishnamurthy and Tom M. Mitchell. Transactions of the Association for Computational Linguistics, 2015. PDF / Data and Online Appendix / bib

Learning to Understand Natural Language with Less Human Effort Jayant Krishnamurthy. PhD Thesis, Computer Science Department, Carnegie Mellon University, 2015. PDF / bib

Never-Ending Learning Tom M. Mitchell, William Cohen, Estevam Hruschka, Partha Talukdar, Justin Betteridge, Andrew Carlson, Bhavana Dalvi, Matt Gardner, Bryan Kisiel, Jayant Krishnamurthy, Ni Lao, Kathryn Mazaitis, Thahir Mohamed, Ndapa Nakashole, Emmanouil Platanios, Alan Ritter, Mehdi Samadi, Burr Settles, Richard Wang, Derry Wijaya, Abhinav Gupta, Xinlei Chen, Abulhair Saparov, Malcom Greaves and Joel Welling. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), 2015. PDF / bib

Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases Matt Gardner, Partha Talukdar, Jayant Krishnamurthy and Tom M. Mitchell. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014. PDF / bib

Joint Syntactic and Semantic Parsing with Combinatory Categorial Grammar Jayant Krishnamurthy and Tom M. Mitchell. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014. PDF / Data and Online Appendix / bib

Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models. Jayant Krishnamurthy and Tom M. Mitchell. In Proceedings of the 2013 ACL Workshop on Continuous Vector Space Models and their Compositionality, 2013. PDF / bib

Toward Interactive Grounded Language Acquisition. Thomas Kollar, Jayant Krishnamurthy and Grant Strimel. In Robotics: Science and Systems, 2013. PDF / bib

Jointly Learning to Parse and Perceive: Connecting Natural Language to the Physical World. Jayant Krishnamurthy and Thomas Kollar. Transactions of the Association for Computational Linguistics, 2013. PDF / Data and Online Appendix / bib

Weakly Supervised Training of Semantic Parsers. Jayant Krishnamurthy and Tom M. Mitchell. In Proceedings of the 2012 Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), 2012. PDF / bib

Learning to Parse and Ground Natural Language Commands to Robots. Jayant Krishnamurthy and Thomas Kollar. In Proceedings of the AAAI 2012 Workshop on Grounding Language for Physical Systems, 2012. PDF

Which Noun Phrases Denote Which Concepts? Jayant Krishnamurthy and Tom M. Mitchell. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL), 2011. PDF / bib

CrossBridge: Finding Analogies using Dimensionality Reduction. Jayant Krishnamurthy and Henry Lieberman. In Proceedings of the AAAI Fall Symposium on Common Sense Knowledge, November 2010. PDF

Finding Analogies in Semantic Networks using the Singular Value Decomposition. Jayant Krishnamurthy. Master's thesis, Massachusetts Institute of Technology, 2009. PDF CrossBridge, the analogy algorithm from the paper, is now included in Divisi.

An Interface for Targeted Collection of Common Sense Knowledge using a Mixture Model. Robert Speer, Jayant Krishnamurthy, Catherine Havasi, Dustin Smith, Kenneth Arnold, and Henry Lieberman. In Proceedings of Intelligent User Interfaces, 2009. PDF

The MD6 Hash Function -- A Proposal to NIST for SHA-3. Ronald L. Rivest, with Benjamin Agre, Daniel V. Bailey, Christopher Crutchfield, Yevgeniy Dodis, Kermin Elliott Fleming, Asif Khan, Jayant Krishnamurthy, Yuncheng Lin, Leo Reyzin, Emily Shen, Jim Sukha, Drew Sutherland, Eran Tromer, and Yiqun Lisa Yin. Submitted to NIST on October 27, 2008. PDF The latest version of the MD6 report, along with other related material and code is available from the MD6 website.