I am currently a Staff Research Scientist at Duolingo, working on the Duolingo English Test. In the past, I was a Distinguished AI Engineer at the ETS AI Labs. I obtained my Ph.D. from the Department of Computer Science at University of Maryland, College Park. I was also a graduate research assistant in the Computational Linguistics and Information Processing Laboratory at the Institute for Advanced Computer Studies, where I worked with my advisor, Bonnie Dorr.
In general, my research has been focused on building systems—with underlying computational models of language—that process written text so as to enhance our experience with those texts. As an example, in my dissertation, I demonstrated the existence of a concrete symbiotic semantic relationship between systems that translate text and those that paraphrase text; I then exploited this relationship to build better translation and paraphrasing systems. Besides machine translation and paraphrase generation, I have also worked on automatic summarization and information retrieval systems. I am also particularly interested in information and data visualization and over the last few years, I have worked on some interesting projects such as visualizing poetry for humanity scholars and interactive scoring for statistical machine translation systems.
My work has allowed to me to apply NLP techniques to build useful educational applications and technologies. Some examples include mining Wikipedia revision history to correct grammatical errors, using paraphrase generation to improve sentiment analysis of essay data, and automatically detecting organizational elements in argumentative discourse.
I also currently serve as the Chief Information Officer for the Association for Computational Linguistics (ACL) with the goal of transforming its current IT infrastructure into a more modern, efficient, robust, and collaborative version of itself.
I have also had a great time teaching computer science during my days as a graduate student and I am hoping to be involved with more of that in the future.
| 2023 |
|---|
| Local Similarity and Global Variability Characterize the Semantic Space of Human Languages. In Proceedings of the National Academy of Sciences, 120(51):e2300986120. Molly Lewis, Aoife Cahill, Nitin Madnani, and James Evans. [link] |
| Beyond the Repo: A Case Study on Open Source Integration with GECToR. In Proc. Workshop for Natural Language Processing Open Source Software (NLP-OSS). Sanjna Kashyap, Zhaoyang Xie, Kenneth Steimel, and Nitin Madnani. [pdf] [bib] |
| The Role of Robust Software in Automated Scoring. In Yaneva, V. and von Davier, M. (Eds) Advancing Natural Language Processing in Educational Assessment. NCME Educational Measurement and Assessment Book Series. Taylor & Francis. Nitin Madnani, Aoife Cahill, and Anastassia Loukina. [Volume] [Chapter] |
| 2021 |
| Automated Essay Scoring. In Synthesis Lectures on Human Language Technologies (Vol. 14, Issue 5, pp. 1–314). Springer Nature. Beata Beigman Klebanov and Nitin Madnani. [link] |
| 2020 |
| User-centered & Robust Open-source Software: Lessons Learned from Developing & Maintaining RSMTool. In Proc. Workshop for Natural Language Processing Open Source Software (NLP-OSS). Nitin Madnani and Anastassia Loukina. [pdf] [bib] |
| Using PRMSE to Evaluate Automated Scoring Systems in the Presence of Label Noise. In Proc. Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Anastassia Loukina, Nitin Madnani, Aoife Cahill, Lili Yao, Matthew S. Johnson, Brian Riordan, and Daniel F. McCaffrey. [pdf] [bib] |
| Automated Evaluation of Writing - 50 Years and Counting. In Proc. ACL. Beata Beigman Klebanov and Nitin Madnani. [pdf] [bib] |
| Detecting Learning in Noisy Data: The Case of Oral Reading Fluency. In Proc. 10th International Learning Analytics & Knowledge Conference (LAK). Beata Beigman Klebanov, Anastassia Loukina, John Lockwood, Van Liceralde, John Sabatini, Nitin Madnani, Binod Gyawali, Zuowei Wang and Jennifer Lentini. [pdf] [bib] |
| 2019 |
| My Turn To Read: An Interleaved E-book Reading Tool for Developing and Struggling Readers. In Proc. ACL (demos). Nitin Madnani, Beata Beigman Klebanov, Anastassia Loukina, Binod Gyawali, Patrick Lange, John Sabatini and Michael Flor. [pdf] [bib] |
| The Many Dimensions of Algorithmic Fairness in Educational Applications. In Proc. 14th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Anastassia Loukina, Nitin Madnani, and Klaus Zechner. [pdf] [bib] |
| Would you? Could you? On a tablet? Analytics of Children’s eBook Reading. In Proc. 9th International Learning Analytics & Knowledge Conference (LAK). Beata Beigman Klebanov, Anastassia Loukina, Nitin Madnani, John Sabatini, and Jennifer Lentini. [pdf] [bib] |
| 2018 |
| Evaluating On-device ASR on Field Recordings from an Interactive Reading Companion. In Proc. IEEE Workshop on Spoken Language Technology (SLT). Anastassia Loukina, Nitin Madnani, Beata Beigman Klebanov, Abhinav Misra, Georgi Angelov, and Ognjen Todic. [pdf] [bib] |
| Writing Mentor: Writing Progress Using Self-Regulated Writing Support. In Journal of Writing Analytics, 2:280-284. Jill Burstein, Norbert Elliot, Beata Beigman Klebanov, Nitin Madnani, Diane Napolitano, Maxwell Schwartz, Patrick Houghton, and Hillary Molloy. [pdf] [bib] |
| Writing Mentor: Self-Regulated Writing Feedback for Struggling Writers. In Proc. COLING (demos). Nitin Madnani, Jill Burstein, Norbert Elliot, Beata Beigman Klebanov, Diane Napolitano, Slava Andreyev, and Maxwell Schwartz. [pdf] [bib] |
| Automated Scoring: Beyond Natural Language Processing. In Proc. COLING. Nitin Madnani and Aoife Cahill. [pdf] [bib] |
| Atypical Inputs in Educational Applications. In Proc. NAACL (Industry Track). Su‐Youn Yoon, Aoife Cahill, Anastassia Loukina, Klaus Zechener, Brian Riordan, and Nitin Madnani. [pdf] [bib] |
| Second Language Acquisition Modeling. In Proc. 13th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Burr Settles, Chris Brust, Erin Gustafson, Masato Hagiwara and Nitin Madnani. [pdf] [bib] |
| The ACL Anthology: Current State and Future Directions. In Proc. ACL Workshop on NLP Open Source Software (NLPOSS). Dan Gildea, Min-Yen Kan, Nitin Madnani, Christoph Teichmann, and Martin Villalba. [pdf] [bib] |
| A Robust Microservice Architecture for Scaling Automated Scoring Applications. ETS Research Report Series, doi: 10.1002/ets2.12202. Nitin Madnani, Aoife Cahill, Daniel Blanchard, Slava Andreyev, Diane Napolitano, Binod Gyawali, Michael Heilman, Chong Min Lee, Chee Wee Leong, Matthew Mulholland, and Brian Riordan. [pdf] [bib] |
| Analyzing Item Generation with Natural Language Processing Tools for the TOEIC® Listening Test. ETS Research Report Series, doi:10.1002/ets2.12183. Su‐Youn Yoon, Chong Min Lee, Patrick Houghton, Melissa Lopez, Jennifer Sakano, Anastassia Loukina, Bob Krovetz, Chi Lu, and Nitin Madnani. [pdf] [bib] |
| 2017 |
| Building Better Open-source Tools to Support Fairness in Automated Scoring.In Proc. EACL Workshop on Ethics in Natural Language Processing. Nitin Madnani, Anastassia Loukina, Alina von Davier, Jill Burstein, and Aoife Cahill. [pdf] [bib] |
| Generating Language Activities in Real-Time for English Learners using Language Muse. In Proc. Fourth Annual ACM Conference on Learning at Scale (Short Papers). Jill Burstein, Nitin Madnani, John Sabatini, Dan McCaffrey, Kietha Biggers, and Kelsey Dreier. [pdf] [bib] |
| Examination of Paraphrasing Behavior in Source-Based Writing. Presented at the 27th Annual Meeting of the Society for Text and Discourse. Beata Beigman Klebanov and Nitin Madnani. |
| A Large Scale Quantitative Exploration of Modeling Strategies for Content Scoring. In Proc. 12th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Nitin Madnani, Anastassia Loukina, and Aoife Cahill. [pdf] [bib] |
| Speech- and Text-driven Features for Automated Scoring of English Speaking Tasks. In Proc. EMNLP Workshop on Speech-centric Natural Language Processing. Anastassia Loukina, Nitin Madnani, and Aoife Cahill. [pdf] [bib] |
| 2016 |
| Technology-Assisted Generation of Linguistically Relevant Instructional Activities to Support English Learners in Content and Language Learning. Presented at the Annual Meeting for the American Educational Research Association. John Sabatini, Jill Burstein, Nitin Madnani, and Kietha Biggers. |
| Prediction of Passage Acceptance/Rejection Using Linguistic Information. Presented at the the 78th Annual Meeting for the National Council on Measurement in Education. Swapna Somasundaran, Yoko Futagi, Nitin Madnani, Nancy Glazer, Matt Chametsky and Cathy Wendler. |
| Automatically Scoring Tests of Proficiency in Music Instruction. In Proc. 11th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Nitin Madnani, Aoife Cahill, and Brian Riordan. [pdf] [bib] |
| Model Combination for Correcting Preposition Selection Errors. In Proc. 11th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Nitin Madnani, Michael Heilman, and Aoife Cahill. [pdf] [bib] |
| The Effect of Multiple Grammatical Errors on Processing Non-native Writing. In Proc. 11th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Courtney Napoles, Aoife Cahill, and Nitin Madnani. [pdf] [bib] |
| Language Muse: Automated Linguistic Activity Generation for English Language Learners. In Proc. ACL (demos). Nitin Madnani, Jill Burstein, John Sabatini, Kietha Biggers, and Slava Andreyev. [pdf] [bib] |
| RSMTool: A Collection of Tools for Building and Evaluating Automated Scoring Models. In Journal of Open Source Software (JOSS), 1(3). Nitin Madnani and Anastassia Loukina. [html] [bib] |
| 2015 |
| Effective Feature Integration for Automated Short Answer Scoring. In Proc. NAACL (short papers). Keisuke Sakaguchi, Michael Heilman and Nitin Madnani. [pdf] [bib] |
| The Impact of Training Data on Automated Short Answer Scoring Performance. In Proc. 10th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Michael Heilman and Nitin Madnani. [pdf] [bib] |
| Preliminary Experiments on Crowdsourced Evaluation of Feedback Granularity. In Proc. 10th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Nitin Madnani, Martin Chodorow, Aoife Cahill, Melissa Lopez, Yoko Futagi and Yigal Attali. [pdf] [bib] |
| Using Automated Methods to Identify Overly Similar Discrete Items. Presented at the 77th Annual Meeting for the National Council on Measurement in Education. Nitin Madnani and Aoife Cahill. |
| 2014 |
| An Explicit Feedback System for Preposition Errors based on Wikipedia Revisions. In Proc. 9th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Nitin Madnani and Aoife Cahill. [pdf] [bib] |
| Content Importance Models for Scoring Writing From Sources. In Proc. ACL (short papers). Beata Beigman Klebanov, Nitin Madnani, Jill Burstein and Swapna Somasundaran. [pdf] [bib] |
| Predicting Grammaticality on an Ordinal Scale. In Proc. ACL (short papers). Michael Heilman, Aoife Cahill, Nitin Madnani, Melissa Lopez, Matthew Mulholland and Joel Tetreault. [pdf] [bib] |
| Bucking the Trend: Improved Evaluation and Anotation Practices for ESL Error Detection Systems. In Language Resources & Evaluation: Special Issue on Resources and Tools for Language Learners, 48(1). Joel Tetreault, Martin Chodorow and Nitin Madnani. [html] |
| 2013 |
| ParaQuery: Making Sense of Paraphrase Collections. In Proc. ACL (demos). Lili Kotlerman, Nitin Madnani and Aoife Cahill. [pdf] [bib] |
| Detecting Missing Hyphens in Learner Text. In Proc. 8th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Aoife Cahill, Martin Chodorow, Susanne Wolff and Nitin Madnani. [pdf] [bib] |
| Automated Scoring of a Summary-Writing Task Designed to Measure Reading Comprehension. In Proc. 8th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Nitin Madnani, Jill Burstein, John Sabatini and Tenaha O'Reilly. [pdf] [bib] |
| Robust Systems for Preposition Error Correction Using Wikipedia Revisions. In Proc. NAACL. Aoife Cahill, Nitin Madnani, Joel Tetreault and Diane Napolitano. [pdf] [bib] |
| HENRY-CORE: Domain Adaptation and Stacking for Text Similarity. In Proc. of the Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity. Michael Heilman and Nitin Madnani. [pdf] [bib] |
| ETS: Domain Adaptation and Stacking for Short Answer Scoring. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval). [Note: This version fixes some errors in the official ACL Anthology version.] Michael Heilman and Nitin Madnani. [pdf] [bib] |
| Using Pivot-based Paraphrasing and Sentiment Profiles to Improve a Subjectivity Lexicon for Essay Data. Transactions of the Association for Computational Linguistics, 1(2013):99−110. Beata Beigman Klebanov, Nitin Madnani and Jill Burstein. [pdf] [bib] |
| Sentiment Profiles of Multi-Word Expressions in Test-Taker Essays: The Case of Noun-Noun Compounds. ACM Transactions on Speech and Language Processing, 10(3):12. Beata Beigman Klebanov, Jill Burstein and Nitin Madnani. [html] |
| Sentiment Analysis and Detection for Essay Evaluation. Jill Burstein, Beata Beigman Klebanov, Nitin Madnani and Adam Faulkner. Handbook for Automated Essay Evaluation, Mark D. Shermis and Jill Burstein (eds.), Taylor and Francis. [link] |
| The E-rater Automated Essay Scoring System. Jill Burstein, Joel Tetreault and Nitin Madnani. Handbook for Automated Essay Scoring, Mark D. Shermis and Jill Burstein (eds.), Taylor and Francis. [link] |
| Generating Targeted Paraphrases for Improved Translation. ACM Transactions on Intelligent Systems and Technology, 4(3). Nitin Madnani and Bonnie Dorr. [pdf] [bib] |
| 2012 |
| Topical Trends in a Corpus of Persuasive Writing. ETS Research Report Series, RR-12-19. Michael Heilman and Nitin Madnani. [pdf] [bib] |
| Discriminative Edit Models for Paraphrase Scoring. In Proc. of the 6th International Workshop on Semantic Evaluation (SemEval). Michael Heilman and Nitin Madnani. [pdf] [bib] |
| Exploring Grammatical Error Correction with Not-So-Crummy Machine Translation. In Proc. 7th Workshop on Innovative Use of Natural Language Processing for Building Educational Applications (BEA). Nitin Madnani, Joel Tetreault and Martin Chodorow. [pdf] [bib] |
| Re-examining Machine Translation Metrics for Paraphrase Identification. In Proc. NAACL. Nitin Madnani, Joel Tetreault and Martin Chodorow. [pdf] [bib] [zip] |
| Identifying High Level Organizational Elements in Argumentative Discourse. In Proc. NAACL. Nitin Madnani, Michael Heilman, Joel Tetreault and Martin Chodorow. [pdf] [bib] |
| Building Subjectivity Lexicon(s) from Scratch for Essay Data. In Proc. CICLing. Beata Beigman Klebanov, Jill Burstein, Nitin Madnani and Adam Faulkner. [pdf] [bib] |
| 2011 |
| iBLEU: Interactively Scoring and Debugging Statistical Machine Translation Systems. In Proc. Fifth IEEE International Conference on Semantic Computing (Demos). Nitin Madnani. [pdf] [bib] [website] |
| E-rating Machine Translation. In Proc. WMT. Kristen Parton, Joel Tetreault, Nitin Madnani, Martin Chodorow. [pdf] [bib] |
| They Can Help: Using Crowdsourcing to Improve the Evaluation of Grammatical Error Detection Systems. In Proc. ACL (Short Papers). Nitin Madnani, Joel Tetreault, Martin Chodorow and Alla Rozovskaya. [pdf] [bib] [tgz] |
| The Web is not a PERSON, Berners-Lee is not an ORGANIZATION, and African-Americans are not LOCATIONS: An Analysis of the Performance of Named-Entity Recognition. In Proc. Workshop on Multiword Expressions. Bob Krovetz, Paul Deane and Nitin Madnani. [pdf] [bib] |
| 2010 |
| Machine Translation Evaluation and Optimization. Handbook of Natural Language Processing and Machine Translation. Joseph Olive, John McCary, and Caitlin Christianson (eds.) Yaser Al-Onaisan, Bonnie Dorr, Doug Jones, Jeremy Kahn, Seth Kulick, Alon Lavie, Gregor Leusch, Nitin Madnani, Chris Manning, Arne Mauser, Alok Parlikar, Mark Przybocki, Rich Schwartz, Matthew Snover, Stephan Vogel and Clare Voss. [html] |
| Putting the User in the Loop: Interactive Maximal Marginal Relevance for Query-Focused Summarization. In Proc. NAACL (Short Papers). Jimmy Lin, Nitin Madnani and Bonnie J. Dorr. [pdf] [bib] |
| Measuring Transitivity using Untrained Annotators. In Proc. Workshop on Creating Speech and Language Data With Amazon’s Mechanical Turk. Nitin Madnani, Jordan Boyd-Graber and Philip Resnik. [pdf] [bib] |
| Generating Phrasal & Sentential Paraphrases: A Survey of Data-Driven Methods. Computational Linguistics, 36(3):341-387. Nitin Madnani and Bonnie Dorr. [pdf] [bib] |
| The Circle of Meaning: From Translation to Paraphrasing and Back. Doctoral Dissertation. Department of Computer Science. University of Maryland College Park. [pdf] [bib] |
| The Python and The Elephant: Large Scale Natural Language Processing with NLTK and Dumbo. In Proc. of the Eighth Annual Python Conference. Nitin Madnani and Jimmy Lin. [video] [bib] [zip] |
| TER-Plus: Paraphrase, Semantic, and Alignment Enhancements to Translation Edit Rate. Machine Translation, 23(2-3):117-127. Matthew Snover, Nitin Madnani, Bonnie Dorr and Richard Schwartz. [html] [bib] |
| 2009 |
| Fluency, Adequacy, or HTER? Exploring Different Human Judgments with a Tunable MT Metric. In Proc. WMT. Matthew Snover, Nitin Madnani, Bonnie Dorr and Richard Schwartz. [pdf] [bib] |
| Querying and Serving N-gram Language Models with Python. The Python Papers. Volume 4, Issue 2. Nitin Madnani. [pdf] [bib] |
| Source Code: Querying and Serving N-gram Language Models with Python. The Python Papers Source Codes. Volume 1. Nitin Madnani. [pdf] [bib] |
| 2008 |
| Applying Automatically Generated Semantic Knowledge: A Case Study in Machine Translation. In Proc. of the Symposium on Semantic Knowledge Discovery, Organization and Use. Nitin Madnani, Philip Resnik, Bonnie Dorr and Richard Schwartz. [pdf] [bib] [poster] |
| Are Multiple Reference Translations Necessary? Investigating the Value of Paraphrased Reference Translations in Parameter Optimization. In Proc. AMTA. Nitin Madnani, Philip Resnik, Bonnie Dorr and Richard Schwartz. [pdf] [bib] |
| Combining Open-Source with Research to Re-engineer a Hands-on Introductory NLP Course. In Proc. of the Third ACL Workshop on Issues in Teaching Computational Linguistics (TeachCL-08). Nitin Madnani and Bonnie Dorr. [pdf] [bib] |
| Multiple Alternative Sentence Compressions and Word-Pair Antonymy for Automatic Text Summarization and Recognizing Textual Entailment. In Proc. of the Text Analysis Conference (TAC). Saif Mohammad, Bonnie J. Dorr, Melissa Egan, Nitin Madnani, David Zajic, and Jimmy Lin. [pdf] [bib] |
| TERp: A System Description. In Proc. of the First NIST Metrics for Machine Translation Challenge (MetricsMATR). Matthew Snover, Nitin Madnani, Bonnie Dorr and Richard Schwartz. [pdf] [bib] |
| 2007 |
| Using Paraphrases for Parameter Tuning in Statistical Machine Translation. In Proc. WMT. Nitin Madnani, Necip Fazil Ayan, Philip Resnik, Bonnie Dorr. [pdf] [bib] |
| Measuring Variability in Sentence Ordering for News Summarization. In Proc. ENLG. Nitin Madnani, Rebecca Passonneau, John Conroy, Necip Fazil Ayan, Bonnie Dorr, Judith Klavans, Dianne O'Leary and Judith Schlesinger. [pdf] [bib] |
| Getting Started on Natural Language Processing with Python. ACM Crossroads, 13(4). Nitin Madnani. [Note: This PDF version is now out of date and is here only for historical reasons. The GitHub repository contains a nice interactive iPython notebook version of the article and is kept up to date.] [github repo] [pdf] [html] [bib] |
| TREC 2007 ciQA Task: University of Maryland. In Proc. TREC. Nitin Madnani, Jimmy Lin, and Bonnie Dorr. [pdf] [bib] |
| Multiple Alternative Sentence Compressions for Automatic Text Summarization. In Proc. of the Document Understanding Conference (DUC) at HLT/NAACL. Nitin Madnani, David Zajic, Bonnie Dorr, Necip Fazil Ayan and Jimmy Lin. [pdf] [bib] |
| 2005 and earlier |
| The Hiero Machine Translation System: Extensions, Evaluation, and Analysis. 2005. In Proc. HLT/EMNLP. David Chiang, Adam Lopez, Nitin Madnani, Christof Monz, Philip Resnik and Michael Subotin. [pdf] [bib] |
| Rapid Porting of DUSTer to Hindi. 2003. ACM Transactions on Asian Language Information Processing, 2(2). Bonnie J. Dorr, Necip Fazil Ayan, Nizar Habash, Nitin Madnani, and Rebecca Hwa. [pdf] [bib] |
| Rater Scoring Modeling Tool (RSMTool): RSMTool is a python package for facilitating research on building and evaluating scoring models (SMs) for automated scoring engines. It allows the integration of educational measurement practices with the automated scoring and model building process. Work done in collaboration with Anastassia Loukina. [link] |
| SciKit-Learn Laboratory (SKLL): SKLL (pronounced "skull") provides a number of utilities to make it simpler to run common scikit-learn experiments with pre-generated features. Work done in collaboration with Daniel Blanchard and Michael Heilman. [link] |
| Python & Perl wrappers for SRILM: Wrappers that will allow you to read and query an SRI language model directly in your Python and Perl code. [link] (Note: I also have working Python and Perl wrappers for the IRSTLM toolkit but I am too lazy to put them up here. Drop me a note if you are interested and I will send them to you.) |
| Interactive BLEU Scoring Tool: A visual and interactive environment for scoring output of automatic machine translation systems. It's written to run entirely in the browser and utilizes the latest web technologies to allow interactive qualitative examination of MT output. [link] |
| python-zpar: A python wrapper around the ZPar English parser. [link] |
| node-zpar: A module that allows using the ZPar English parser with node.js [link] |
| NAACL 2019 Website/App/Schedule: Repositories for the NAACL 2019 conference for the website, the app, and for target-indepdent schedule parsing [website] [app] [schedule] |
| EMNLP 2018 Website: A website for the EMNLP 2018 conference with custom JavaScript code to allow printing of customized schedules [link] |
| ACL 2017 Website: A website for the ACL 2017 conference with custom JavaScript code to allow printing of customized schedules [link] |
| ParaQuery: An interactive querying tool for pivot-based paraphrase databases. Written entirely in Python. Work done in collaboration with Lili Kotlerman (my summer intern in 2012) and Aoife Cahill. [link] [pdf] |
| WebSocket Stanford Tagger Server: This project provides a WebSocket server that wraps the Stanford Part-of-Speech tagger. This makes it easier to get part-of-speech tags from JavaScript for arbitrary text. Includes a jQuery demo. [link] |
| clusterinfo: A Python script that displays current usage of a PBS-based cluster in a more condensed and easier-to-read format. [tgz] |
| LM Server: A Python-based XML-RPC server for an SRILM language model. Allows multiple clients to query the same language model that's loaded in memory in server mode. [tgz] |
| UMIACS Word Alignment Interface: A Java-based tool for creating and viewing word alignments between language pairs. It has been widely used across the community to create aligments for many language pairs including Welsh-English, Swahili-English, Czech-English and Chinese-English. [link] |
| TER-plus (TERp): An automated evaluation metric for Machine Translation, comparing system outputs to reference translations. TERp utilizes automatically generated paraphrases, stemming, synonyms, relaxed shifting constraints and other improvements. [link] (Note: collaboration with Matthew Snover, the main developer of TERp.) |
| The Evolution of Automated Writing Evaluation. 2021. Invited talk at the NLP in Assessment Conference organized by NBME. [slides] |
| Unite.AI interview about RSMTool. 2020. [link] |
| Using NLP for Automated Evaluation of Language Production. 2016. 5-day course taught at NASSLLI 2016 with Beata Beigman Klebanov. |
| Mining Wikipedia Revisions for Automatic Grammar Error Correction & Feedback. 2016. Invited talk at IISc Bangalore. |
| Machine Learning and Educational Assessment: A Pythonic Love Story. 2015. NYC PyData 2015. [slides] |
| Ouroboros and the Alchemy of Statistical Machine Translation. 2015. Invited talk at Princeton University. |
| An explanation of and thoughts about the Facebook PNAS paper on emotion contagion. 2014. [link] |
| Using Wikipedia Revisions for Automated Grammatical Error Correction. 2013. Invited CLUNCH talk at the University of Pennsylvania. |
| What Test Takers Say: Analyzing Argument Organization and Topical Trends in Essays. 2013. Invited talk for the Linguistics brown bag at Montclair State University. |
| A Story in Pictures. 2012. Entry for the Automated Student Assessment Prize Essay Visualization Contest organized by the William and Flora Hewlett Foundation. [pdf]
[Note: This entry won the first prize in the contest by popular vote. ]
|
| Using Statistical Machine Translation to Improve Statistical Machine Translation. 2011. Invited talk for the Yahoo! Data Sciences Seminar at Rutgers University. [pdf] |
| The Circle of Meaning: From Translation to Paraphrasing and Back. 2010. Invited talk for the NLP Seminar at CUNY Graduate Center, New York. |
| A timeline of inter-annotator agreement measures in Computational Linguistics based on Inter-Coder Agreement for Computational Linguistics by Ron Artstein and Massimo Poesio. Linguistics seminar on Corpus-based Social Science, University of Maryland. [pdf] |
| Decoding in Statistical Machine Translation. 2006. StatMT Reading Group, University of Maryland. [slides] |
| Expectation Maximization. 2004. Advanced NLP Seminar, University of Maryland. [slides] |
| Chief Information Officer, Association for Computational Linguistics (2019-Present). |
| Action Editor, Transactions of the Association for Computational Linguistics (TACL) (2020-Present). |
| Senior Area Chair (NLP Applications), EMNLP 2023. Recognized as an Outstanding Senior Area Chair by the Conference Organizers. |
| Area Chair (Resources & Evaluation), *SEM 2021. |
| Senior Area Chair (NLP Applications), NAACL 2021. |
| Judge for Computer Science Category, The Global Undergraduate Awards, 2020. |
| Executive Board Member, ACL Special Interest Group on Building Educational Applications (2018-2021). |
| Standing Reviewer, Transactions of the Association for Computational Linguistics (TACL), 2014-2020. |
| Website & Conference App Chair, NAACL 2019. |
| Website & Conference App Chair, EMNLP 2018. |
| Area Chair, Text Mining and NLP Applications, EMNLP 2017. |
| Website & Conference App Chair, ACL 2017. |
| Program Committee Member, NAACL, ACL, EMNLP (since 2010). |
| Volunteer, ACL Anthology. |
| Co-PI, Project Learning with Automated, Networked Supports (PLANS), National Science Foundation, 2015-2019. |
| Co-investigator, Technology-Assisted Generation of Linguistically-Relevant Instructional Activities to Support ELLs in Content and Language Learning in the Content Areas, Institute for Education Sciences, 2014-2018. |