Dr. Shafiq Joty

Scientist
Arabic Language Technologies
+974 44546005
QCRI offers me the right balance between ‘pure’ research and ‘applied’ research.

Research Focus at QCRI

Shafiq's research goal is twofold: a) to build computational models of different discourse processing tasks in asynchronous conversations (e.g., blogs, emails, Twitter); b) to effectively exploit the extracted discourse structures in end-user NLP applications like conversation summarization, visualization, information extraction and sentiment analysis. In particular, in his PhD, he developed state-of-the-art models for topic segmentation and labeling, dialog act recognition and rhetorical parsing in asynchronous conversations. Now, he is interested in investigating how the topic structure, the dialog structure and the rhetorical structure can be effectively exploited in the above mentioned applications.
 
At QCRI, Shafiq is also involved with many other projects on Arabic language including machine translation, meeting summarization, named entity recognition. 
 
As a methodology, he develops algorithms that are grounded in statistical machine learning and can leverage both rare labeled and abundant unlabeled data. Therefore, he is interested in unsupervised, semi-supervised and fully supervised statistical models.

Previous Experience

In his Ph.D., Shafiq worked with Dr. Giuseppe Carenini and Dr. Raymond Ng on discourse analysis of asynchronous conversations. In his M.Sc., he worked with Dr. Yllias Chali on text summarization and question answering systems.

Professional Experience

  • Microsoft Research, Research intern, Sep 2010 – Dec 2010.
  • Islamic University of Technology, Lecturer, Jan 2005 – Aug 2006.

Professional Associations and Awards

  • NSERC CGS-D (Canada)
  • Microsoft Excellent Intern (Research)
  • Four Year Fellowship (UBC, Canada)
  • ACL
  • SIGDAT
  • AAAI
  • ACM

Education

  • Ph.D., University of British Columbia, 2013
  • M.Sc., University of Lethbridge, 2008

Selected Research

  • Shafiq Joty, Giuseppe Carenini and Raymond Ng. Topic Segmentation and Labeling in Asynchronous Conversations. Journal of AI Research (JAIR), 2013.
  • Shafiq Joty, Giuseppe Carenini, Raymond Ng and Yashar Mehdad. Combining Intra- and Multisentential Rhetorical Parsing for Document-level Discourse Analysis. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL) 2013, Sofia, Bulgaria.
  • Shafiq Joty, Giuseppe Carenini and Raymond Ng. A Novel Discriminative Framework for SentenceLevel Discourse Analysis. In Proceedings of the Conference on Empirical Methods in Natural Language Processing and the Conference on Natural Language Learning (EMNLP-CoNLL) 2012, Jeju, Korea.
  • Shafiq Joty, Giuseppe Carenini, and Chin-Yew Lin. Unsupervised Modeling of Dialog Acts in Asynchronous Conversations. In Proceedings of the twenty second International Joint Conference on Artificial Intelligence (IJCAI) 2011. Barcelona, Spain.
  • Shafiq Joty, Giuseppe Carenini, Gabriel Murray and Raymond Ng. Supervised Topic Segmentation of Email Conversations. In Fifth International AAAI Conference on Weblogs and Social Media (ICWSM) 2011. Barcelona, Spain. (Short paper).
  • Shafiq Joty, Giuseppe Carenini, Gabriel Murray and Raymond Ng. Exploiting Conversation Structure in Unsupervised Topic Segmentation for Emails. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) 2010. Cambridge, Massachusetts, USA.
  • Yllias Chali, Shafiq Joty and Sadid Hasan. Complex Question Answering: Unsupervised Learning Approaches and Experiments. Journal of AI Research (JAIR) 2009. Vol. 35, Page 1-47.

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2017

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(MLDAS 2017) Machine Learning and Data Analytics Symposium

Download ICS File 13/03/2017  - 14/03/2017 , Qatar National Convention Centre

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Past Events

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Download ICS File 03/02/2017 ,

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2016

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QCRI - IBM Data Science Connect 2016

Download ICS File 16/11/2016 ,

QCRI–IBM Data Science Connect 2016  Doha, Qatar 12.30pm –5:30pm, Wednesday, November 16 HBKU Research Complex, Ground Level Multi-Purpose Room Google Map link to location https://goo.gl/maps/...

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News Releases

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