Anoop Kunchukuttan
Principal Applied Researcher at Microsoft
Hyderabad, Telangana, India
Summary
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Senior🎓
Top SchoolAnoop Kunchukuttan is a vice president of research and multilingual NLP specialist with 13+ years building machine translation, transliteration and Indian-language AI systems across industry and academia. He co-leads AI4Bharat at IIT Madras and previously advanced Azure’s multilingual and multimodal efforts at Microsoft, adding support for 17+ Indic languages and extensive transliteration models. His PhD work leverages linguistic relatedness to create more accurate, low-resource translation systems, and he couples that theoretical lens with hands-on engineering—contributing to widely used open-source projects such as Moses and the Indic NLP Library. At Bodhan AI he now leads research to deliver the Bharat EduAI Stack, applying multilingual and multimodal models to educational needs across India. Notably, his background spans large-scale productionizing of translation and bespoke information-extraction systems for medical text, reflecting a rare blend of deep research and production engineering.
12 years of coding experience
8 years of employment as a software developer
Indian Institute of Technology BombayBE, Computer Science, BE, Computer Science at Savitribai Phule Pune University
English, Hindi, Marathi, Malayalam
Github Skills (12)
transliteration10
machine-translation10
c-language10
cprogramming-language10
python10
natural-language-processing10
normalization10
tokenizer9
nlp9
tokenize9
boost8
xml-parsing7
Programming languages (5)
Github contributions (5)
anoopkunchukuttan/indic_nlp_library
Sep 2013 - May 2021
Resources and tools for Indian language Natural Language Processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 5 reviews, 180 commits in 7 years 9 months
Contributions summary:Anoop primarily contributed to the Indic NLP Library, focusing on improvements and additions to the normalization and transliteration functionalities, specifically for various Indian languages. They added support for new features such as the handling of Malayalam chillus characters, support for script shared between languages, the creation of a trivial tokenizer, and also implemented improvements in the sentence splitting functionality. Furthermore, the user fixed several bugs within the library.
pythonword-embeddingslanguage-processingtext-processingphonetics
moses-smt/mosesdecoder
Sep 2020 - Oct 2020
Moses, the machine translation system
Role in this project:Back-end Developer
Back-end DeveloperContributions:12 commits in 5 days
Contributions summary:Anoop primarily contributed to the `mosesdecoder` project by implementing new features and modifying existing code related to the handling of different input types for machine translation. The commits show changes to the `TypeDef.h` and `SentenceWithCandidates.cpp` files, adding support for a new input type and associated classes. These changes indicate the user was involved in extending the core functionality of the translation system, focusing on input parsing and processing.
i18nmachine-translationtranslationlocalizationmoses
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