Hi, I am a PhD student in the Center for Language and Speech Processing (CLSP) at Johns Hopkins University. My primary research is in building computational models for user modeling, specifically in language learning. I apply techniques from Natural Language Processing (NLP), Machine Translation (MT), and Machine Learning (ML) towards this problem. In addition, I am working on building models for grammar correction for language learners. Finally, I am interested in studying speed vs. accuracy trade-offs in machine translation and interactive machine translation.

I am advised by Philipp Koehn and Jason Eisner. I also have worked with Adam Lopez on finite automata based systems for machine translation and translation using Abstract Meaning Representations (AMR).

Before joining CLSP, I worked on designing new modalities of user interaction at the Arts Media & Engineering program. I also worked at Rosetta Stone as a software developer and did a brief stint as an NLP engineer at MModal.

Publications

Knowledge Tracing in Sequential Learning of Inflected Vocabulary
Adithya Renduchintala, Philipp Koehn and Jason Eisner, Conference on Computational Natural Language Learning (CoNLL), 2017.

User Modeling in Language Learning with Macaronic Texts.
Adithya Renduchintala, Rebecca Knowles, Philipp Koehn and Jason Eisner, Annual Meeting of the Association for Computational Linguistics (ACL), 2016.

Creating Interactive Macaronic Interfaces for Language Learning.
Adithya Renduchintala, Rebecca Knowles, Philipp Koehn and Jason Eisner, System Description, Annual Meeting of the Association for Computational Linguistics (ACL), 2016.

Analyzing Learner Understanding of Novel L2 Vocabulary
Rebecca Knowles, Adithya Renduchintala, Philipp Koehn and Jason Eisner, Conference on Computational Natural Language Learning (CoNLL), 2016.

An Algerian Arabic-French Code-Switched Corpus.
Ryan Cotterell, Adithya Renduchintala, Naomi P. Saphra and Chris Callison-Burch. LREC Workshop on Free/Open-Source Arabic Corpora and Corpora Processing Tools. 2014.

Using Machine Learning and HL7 LOINC DO for Classification of Clinical Documents.
Adithya Renduchintala, Amy Zhang, Thomas Polzin, Gilan Saadawi.AMIA, 2013.

Designing for persistent Audio Conversations in the Enterprise.
Adithya Renduchintala, Ajita John, Shreeharsh Kelkar, and Doree Duncan-Seligmann. Design for User Experience. 2007.

Creating serendipitous encounters in a geographically distributed community
Adithya Renduchintala, Aisling Kelliher, Hari Sundaram, ACM international workshop on Human-centered multimedia. 2006

Contact

adi.r@jhu.edu
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