Dr. Nadir Durrani


Scientist
Arabic Language Technologies

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QCRI gives me a flavor of industrial and academic research at the same time. It’s has quickly turned into a world class organization over the last few years and is growing faster than any other place.

Research Focus at QCRI

Dr. Nadir Durrani's research interests include:

- Neural and statistical machine translation (with a focus on reordering, domain adaptation, transliteration, dialectal translation, pivoting, closely related and morphologically rich languages), spoken language translation, eye-tracking for MT evaluation, word segmentation, spelling correction, writing scripts, font development, normalization and language collation;

- Localization of open source operating systems (desktop environment KDE/GNOME), word processing applications, chat tools, web browsers and web development tools, localization of domain names.

At QCRI, he is part of the machine translation group and is involved in all the MT related projects such as Speech and Medical Translation and international collaborations such as SUMMA and MIT. On the research side he has been involved in the Domain Adaptation and Eye-tracking for MT evaluation and Dialect Translation projects. He has also been involved in representing QCRI at Open NIST 2015 and IWSLT 2016 MT challenge.




Previous Experience

Prior to joining QCRI, Dr. Durrani was a research associate at the University of Edinburgh, where his work was focused on Markov based translation models and their integration into Phrase-based SMT.  He also worked on transliteration, and translation between closely related languages.  Much of his work is part of Moses Core and has directly contributed towards the success of the state-of-the-art systems in the previous translation campaigns such as WMT and IWSLT.

During a short stint at the IBM Watson Center, Dr. Durrani worked on improving the Egyptian-English machine translation in the BOLT project.

At CRULP, Pakistan, Dr. Durrani was involved in PAN Localization project and carried out research and development for local language technologies and its dissemination across masses.  He also worked onan OSS Localization project for Urdu, where he led a team that localized open source software such as Open Office, web browser and development tools, chatting software, and Linux desktop environment for Urdu. He also worked on the localization of domain names in Urdu.

Dr. Durrani also worked at STEA, Laos as a project consultant through PAN Localization project. There he was involved in developing localized open-source products (such as fonts, editor, spell checker, tokenization) for the Lao language.

Professional Experience

  • Dec 2012 – Sept 2014, Post-doctoral Research Associate at the School of Informatics,  University of Edinburgh, UK
  • Jan 2012 – April 2012, Research Intern at  the IBM Watson Center,  USA
  • Aug 2005 – Nov 2007, Research Officer at the Center for Research in Urdu Language Processing, NUCES, Pakistan
  • Jan 2005 – July 2005 Project Consultant at the Science and Technology Agency , Laos

Professional Associations and Awards

  • GSCL best doctoral thesis award in the field of language technologies and computational linguistics 2014
  • IMS best doctoral thesis award 2012
  • Silver Medal, MS (CS), National University of Computer and Emerging Science 2007
  •  Top Pre-Engineering Student Award (2nd position), awarded by Engineering Council of KSA 2000
  •  Member of Association for Computational Linguistic
Competitions
  • Best Arabic-English systems at IWSLT 2016
  • 2nd Best Egyptian-English system at Open NIST 2015
  • Our phrase-based systems beat Google's Online-B at WMT-13 and WMT-14 in several language pairs including Czech, French and Spanish
  • Our systems were ranked highest at IWSLT-13 and IWSLT-14 in many language pairs

Education

  • PhD., University of Stuttgart, 2012
  • BS(CS) and MS(CS), National University of Computer and Emerging Sciences, 2000-2007

Selected Research

Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, James Glass (2017). What do Neural Machine Translation Models Learn about Morphology? In Proceedings of the 55th Annual Conference of the Association for Computational Linguistics (ACL), Vancouver, Canada, July.

Hassan Sajjad, Fahim Dalvi, Nadir Durrani, Yonatan Belinkov, Ahmed Abdelali, Stephan Vogel (2017). Challenging Language-Dependent Segmentation for Arabic: An Application to Machine Translation and Part-of-Speech Tagging. In Proceedings of the 55th Annual Conference of the Association for Computational Linguistics (ACL), Vancouver, Canada, July

Shafiq Joty, Nadir Durrani, Hassan Sajjad and Ahmed Abdelali (2017) Domain Adaptation Using Neural Network Joint Model (2017), Computer Speech & Language, Special Issue on Deep Learning for Machine Translation

Nadir Durrani, Hassan Sajjad, Shafiq Joty, and Ahmed Abdelali (2016). A Deep Fusion Model for Domain Adaptation in Phrase-based MT.  In Proceedings of the 26th Annual Conference on Computational Linguistics (COLING). Osaka, Japan. December.

Hassan Sajjad, Francisco Guzmán, Nadir Durrani, Ahmed Abdelali, Houda Bouamor, Irina Temnikova and Stephan Vogel (2016). Eyes Don’t Lie: Predicting Machine Translation Quality Using Eye Movement.  In Proceedings of the 15th Annual Conference of the North American Chapter of the Association of Computational Linguistics: Human Language Technologies (NAACL), San Diego, US, June

Shafiq Joty, Hassan Sajjad, Nadir Durrani, Kamla Al-Mannai, Ahmed Abdelali, Stephan Vogel (2015). How to Avoid Unwanted Pregnancies: Domain Adaptation using Neural Network Models.  In Proceedings of the 12th Conference on Empirical Methods in Natural Language Processing (EMNLP), Lisbon, Portugal, September.

Nadir Durrani, Helmut Schmid, Alexander Fraser, Philipp Koehn, Hinrich Schütze (2015). The Operation Sequence Model - Combining N-Gram-based and Phrase-based Statistical Machine Translation. Computational Linguistics. Vol 41, No. 2 : 157–186.

Nadir Durrani, Philipp Koehn, Helmut Schmid, Alexander Fraser (2014). Investigating the Usefulness of Generalized Word Representations in SMT. In Proceedings of the 25th Annual Conference on Computational Linguistics (COLING). Dublin, Ireland. August

Nadir Durrani, Hassan Sajjad, Hieu Hoang, Philipp Koehn (2014). Integrating an Unsupervised Transliteration Model into Statistical Machine Translation. In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Gothenburg, Sweden, April
 
Nadir Durrani, Alexander Fraser, Helmut Schmid, Hieu Hoang, Philipp Koehn (2013). Can Markov Models Over Minimal Translation Units Help Phrase-Based SMT? In Proceedings of the 51st Annual Conference of the Association for Computational Linguistics (ACL). Sofia, Bulgaria, August

Nadir Durrani, Alexander Fraser, Helmut Schmid (2013). Model With Minimal Translation Units, But Decode With Phrases. In Proceedings of the 14th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), Atlanta, Georgia, USA, June

Nadir Durrani, Helmut Schmid, Alexander Fraser, (2011). A Joint Sequence Translation Model with Integrated Reordering. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (ACL-HLT), Portland, Oregon, USA, June

Nadir Durrani, Hassan Sajjad, Alexander Fraser, Helmut Schmid (2010). Hindi to Urdu Machine Translation Through Transliteration. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL),  Uppsala, Sweden, July

Nadir Durrani and Sarmad Hussain (2010). Urdu Word Segmentation. In Proceedings of the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), Los Angeles, California, USA, June

Please click here for a complete list of publications.

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