What I do

I'm a senior PhD student in the Language Technologies Institute, in the School of Computer Science, at Carnegie Mellon University (though my advisor moved to the University of Washington, so I live in Seattle). I'm primarily interested in statistical machine learning and natural language processing, though many problems elswhere also catch my attention. I've worked on a wide variety of projects, including generating descriptions of images, semantic parsing, temporal grounding of events, question answering with neural networks, hyperparameter optimization, structured sparsity in neural networks, and reproducibility in machine learning. I've been very lucky to work with some fantastic people. I currently am advised by Noah Smith. As an undergrad at the University of Washington my honors thesis was advised by Luke Zettlemoyer.

During the summer of 2011, I was selected to participate in the John's Hopkins summer workshop as an undergrad, where I worked with a host of fantastic people (and got a great sweatshirt). I was on the vision and language team; you can see the website for our project here.

In the summer and fall of 2015 I interned at Facebook AI Research in NYC with Jason Weston and Antoine Bordes, where I built the Movie Dialog dataset and the MovieQA dataset. Slate.com wrote an article that covered some of my work!

In the summer of 2018 I interned at Google AI with Elad Eban, where I worked with the MorphNet team. I got a shoutout in their blog post.

As of the summer of 2019, I am currently interning at the Allen Institute for Artificial Intelligence with my advisor, Noah Smith, on the AllenNLP team.

See below for a list of my publications.



Publications

  • Green AI
     Roy Schwartz*, Jesse Dodge*, Noah A. Smith, Oren Etzioni
    Opinion Piece, 2019
    * denotes equal contribution

  • Show Your Work: Improved Reporting of Experimental Results
     Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith
    Empirical Methods on Natural Language Processing (EMNLP), 2019

  • RNN Architecture Learning with Sparse Regularization
     Jesse Dodge, Roy Schwartz, Hao Peng, Noah A. Smith
    Empirical Methods on Natural Language Processing (EMNLP), 2019

  • Open Loop Hyperparameter Optimization and Determinantal Point Processes
     Jesse Dodge, Kevin Jamieson, Noah A. Smith
    AutoML Workshop at International Conference on Machine Learning (ICML), 2017

  • Key-Value Memory Networks for Directly Reading Documents
     Alexander Miller, Adam Fisch, Jesse Dodge, Amir-Hossein Karimi, Antoine Bordes, Jason Weston
    Empirical Methods on Natural Language Processing (EMNLP), 2016

  • Evaluating Prerequisite Qualities for Learning End-to-end Dialog Systems [poster]
    Jesse Dodge*, Andreea Gane*, Xiang Zhang*, Antoine Bordes, Sumit Chopra, Alexander Miller, Arthur Szlam, Jason Weston
    International Conference on Learning Representations (ICLR), 2016
    * denotes equal contribution

  • Retrofitting Word Vectors to Semantic Lexicons
     Manaal Faruqui, Jesse Dodge, Sujay Jauhar, Chris Dyer, Eduard Hovy, Noah A. Smith
    North American Chapter of the Association for Computational Linguistics (NAACL), 2015
    Won best student paper award

  • Large scale retrieval and generation of image descriptions
    Vicente Ordonez, Xufeng Han, Polina Kuznetsova, Girish Kulkarni, Margaret Mitchell, Kota Yamaguchi, Karl Sratos, Amit Goyal, Jesse Dodge, Alysssa Mensch, Hal Daumé III Alexander C. Berg, Yejin Choi, Tamara L. Berg
    International Journal of Computer Vision, 2015.

  • CMU: Arc-Factored, Discriminative Semantic Dependency Parsing
    Sam Thomson, Brendan O'Connor, Jeffrey Flanigan, David Bamman, Jesse Dodge, Swabha Swayamdipta, Nathan Schneider, Chris Dyer, Noah A. Smith
    International Workshop on Semantic Evaluations (SemEval), 2014.

  • Context-dependent Semantic Parsing for Time Expressions [demo] [code] [tool]
    Kenton Lee, Yoav Artzi, Jesse Dodge, Luke Zettlemoyer
    Association for Computational Linguistic (ACL), 2014.

  • Midge: Generating Image Descriptions From Computer Vision Detections
    Margaret Mitchell, Jesse Dodge, Amit Goyal, Kota Yamaguchi, Karl Sratos, Xufeng Han, Alysssa Mensch, Alexander C. Berg, Tamara L. Berg, Hal Daumé III
    European Chapter of the Association for computational Linguistics (EACL), 2012.

  • Understanding and Predicting Importance in Images
    Alexander C. Berg, Tamara L Berg Hal Daumé III, Jesse Dodge, Amit Goyal, Xufeng Han, Alyssa Mensch, Margaret Mitchell, Aneesh Sood, Karl Stratos, Kota Yamaguchi
    Computer Vision and Pattern Recognition (CVPR), 2012.

  • Detecting Visual Text
    Jesse Dodge, Amit Goyal, Xufeng Han, Alyssa Mensch, Margaret Mitchell, Karl Stratos, Kota Yamaguchi, Yejin Choi, Hal Daumé III, Alexander C. Berg, Tamara L. Berg
    North American Chapter of the Association for Computational Linguistics (NAACL), 2012.



    Presentations, posters, and other work

  • Presentation: Context-dependent Semantic Parsing for Time Expressions
    Kenton Lee, Yoav Artzi, Jesse Dodge, Luke Zettlemoyer
    Cambridge NLP Seminar, Cambridge University, UK

  • Poster: Graph-based Algorithms for Semantic Parsing
    Jeffrey Flanigan, Sam Thomson, David Bamman, Jesse Dodge, Manaal Faruqui, Brendan O'Connor, Nathan Schneider, Swabha Swayamdipta, Chris Dyer, Noah A. Smith
    Workshop on Semantic Parsing at Association for Computational Linguistics (ACL), 2014

  • An Exploration of How to Learn from Visually Descriptive Text
    Alexander C. Berg, Tamara L. Berg, Hal Daumé III, Jesse Dodge, Amit Goyal, Xufeng Han, Alyssa Mensch, Margaret Mitchell, Karl Stratos, Kota Yamaguchi
    JHU-CLSP Summer Workshop Whitepaper, 2011.

  • Pikachu, Domosaur, and other Monolexical Languages
    Sarah Allen, Jesse Dodge, Domosaur
    Winner of the prestigious Award Award Award Award Award Award Award
    SIGBOVK 2014