Hamdy Mubarak

 
Senior Software Engineer
Arabic Language Technologies

Connect with me

QCRI is a world-class organization that has a very strong team in the NLP field. QCRI offers a wonderful environment for research and development. Colleagues are highly talented with great background, certificates and experience from all the world continents.

Research Focus at QCRI

Hamdy Mubarak is a senior software engineer with extensive experience in building tools and engines for Arabic Natural Language Processing (NLP). He previously managed a team that built the first Arabic diacritizer and Arabic grammar checker in the 1990s. Hamdy also helped to build the first rule-based parser for Arabic, the best Arabic-to-English Machine Translation (NIST2009), and reading machine for blind people (OCR+TTS) among other applications.

Hamdy has a B.Sc. in Computer Sciences with honors from the Faculty of Engineering, Alexandria University, Egypt (1994).

He has participated in building Farasa Arabic NLP tools (word segmentation, spell checker, POS tagging, diacritization, etc.) using machine learning techniques that are very competitive to state-of-the-art systems.

His research interests include:
  • Arabic NLP for Modern Standard Arabic
  • Arabic NLP for dialectal Arabic
  • Enriching Lexical and Semantic resources for Arabic.

Previous Experience

 Projects:
  • Modern Arabic Lexicon
  • Lexical and Semantic Database for Arabic
  • Multi-Mode Morphological Analyzer for Arabic
  • Spell and Grammar Checker for Arabic
  • Diacritization of Modern Standard Arabic
  • Diacritization of Classical Arabic
  • Bilingual (Arabic and English) Keyword and Named-Entity Extraction
  • Bilingual Theme Prediction
  • Bilingual Summarizer
  • Computerized Arabic Corpus
  • Sub-categorization Automatic System (Semantic Restrictions)
  • Arabic Morphological, Syntactic, and Semantic Disambiguation System
  • Rule-Based Arabic Parser
  • Bilingual Search Engine (IDRISI)
  • Multi-Lingual Dictionary
  • Bilingual Name Transliteration and Search

 Support for Projects:

  • MT, TTS, OCR

Professional Experience

  • Arabic NLP R&D Manager, Sakhr Software, Egypt, 1994-2001, 2004-2013
  • Software Manager, Ellipsis Digital Systems (Digital Communications, Head Branch in California, USA), Egypt, 2001-2003

Professional Associations and Awards

  • NIST09 Open Machine Translation A2E Human Assessment (1st Rank), 2009, Ottawa, Canada.
  • E-Content 2ndRank, 2009, Kuwait Electronic Awards for Text Mining.
  • E-Content 3rd Rank, 2009, Kuwait Electronic Awards for News Gathering and Classification Tool.
  • Certificate of Appreciation from Abu Dhabi International Center for Organizational Excellence “ADICOE” for “Transliteration Standards”, 2009, UAE.
  • Best of Gitex, UAE, 1999, Best Arabic Spell and Grammar Checker.
  • Best of Gitex, UAE, 1996, Best Arabic Diacritizer.

Education

BSc. Computer Science and Automatic Control, Faculty of Engineering,
Alexandria University, Egypt, 1992
(Distinct with degree of honor)

Selected Research

QCRI: Answer selection for community question answering-experiments for Arabic and English; Proceedings of the 9th International Workshop on Semantic Evaluation, SemEval
Massimo Nicosia, Simone Filice, Alberto Barrón-Cedeno, Iman Saleh, Hamdy Mubarak et. al.

SemEval-2016 task 3: Community question answering; Proceedings of SemEval
Preslav Nakov, Lluıs Màrquez, Alessandro Moschitti, Walid Magdy, Hamdy Mubarak, Abed Alhakim Freihat, Jim Glass, Bilal Randeree


Methods for integrating rule-based and statistical systems for Arabic to English machine translation

R Zbib, M Kayser, S Matsoukas, J Makhoul, H Nader, H Soliman, R Safadi
Machine Translation 26 (1-2), 67-83

Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging
K Darwish, A Abdelali, H Mubarak
International Conference on Language Resources and Evaluation (LREC-2014)

Using Twitter to collect a multi-dialectal corpus of Arabic
H Mubarak, K Darwish
ANLP 2014, 1

Automatic Correction of Arabic Text: a Cascaded Approach
H Mubarak, K Darwish
ANLP 2014, 132

Verifiably Effective Arabic Dialect Identification
K Darwish, H Sajjad, H Mubarak
EMNLP-2014

Arabic WordNet Enrichment Using Semantic Features and Lexical Database
Hamdy Mubarak, Mostafa Ramadan, Ahmed Metwally
The Arab League Educational, Cultural and Scientific Organization (ALECSO), Tunisia, 2011

Modern Arabic Lexicon, 2013, “The 2nd International Conference for Arabic”
Doha, Qatar.

Lexical and Morphological Statistics of an Arabic POS-Tagged Corpus, 2009,
The 9th Conference on Language Engineering
Ain Shams University, Cairo, Egypt.

Diacritization and Transliteration of Proper Nouns from Arabic to English,  2009
MEDAR, Cairo, Egypt.

Analyzing Arabic Diacritization Errors of MADA and Sakhr Diacritizer, 2011, The 11th Conference on Language Engineering
Ain Shams University, Cairo, Egypt.

Towards Arabic to English Transliteration Standards, 2009, The International Symposium  on Arabic Transliteration Standard: Challenges and Solutions
Abu Dhabi, UAE.

Named Entity Detection in Arabic, 2007, The Seventh Conference on Language Engineering
Ain Shams University, Cairo, Egypt.

Automatic Summarization of Arabic Texts, 2006, The Sixth Conference on Language Engineering, December 2006
Ain Shams University, Cairo, Egypt.


Connect with me

Follow Us

  • YouTube
  • Twitter
  • Facebook
  • RSS Feed
  • Linkedin
  • github-web.png
Back to Top

In the Media

roadtracer.png

MIT/QCRI system uses machine learning to build road maps

22/04/2018

Map apps may have changed our world, but they still haven’t mapped all of it yet. Specifically, mapping roads can be difficult and tedious: even after taking aerial images, companies still have to ...

Read More

Economist story pic.JPG

Improving disaster response efforts through data

08/02/2018

Extreme weather events put the most vulnerable communities at high risk. How can data analytics strengthen early warning systems and and support relief efforts for communities in need? The size and ...

Read More

Yazan Wired story pic.jpg

Your sloppy bitcoin drug deals will haunt you for years

28/01/2018

Perhaps you bought some illegal narcotics on the Silk Road half a decade ago, back when that digital black market for every contraband imaginable was still online and bustling. You might already ...

Read More

Upcoming Events

2018

Eman interns pic 2017.jpg

QCRI Summer Internship Program

Download ICS File 06/05/2018  - 05/07/2018 , Hamad Bin Khalifa Research Complex

Each year, Qatar Computing Research Institute organizes a summer internship program for undergraduate students studying computer science, computer engineering and other disciplines. The internship is unpaid, and QCRI does not provide any visa support.

Read More

Past Events

Regina

Public Talk by Prof. Regina Barzilay "Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text"

Download ICS File 27/03/2018 ,

Artificial Intelligence for Oncology: Learning to Cure Cancer from Images and Text A talk by Professor Regina Barzilay, MIT CSAIL Winner of 2017 MacArthur ‘genius grant’ At Education City Student ...

Read More

Slide1.JPG

QCRI & MIT-CSAIL Annual Project Review 2018

Download ICS File 27/03/2018 ,

Executive Overview Sessions Open to public Date:    Tuesday, March 27, 2018 Time:    9:00AM – 3:00PM Venue:  HBKU Research Complex Multipurpose Room To view full agenda, please click here . To RSVP, ...

Read More

News Releases

Issa Khalil cyber.jpg

QCRI and Turkish scientists to build pre-emptive cyber security platform

10/04/2018

Project to build defensive platform to detect emerging cyberattacks awarded $1.65m grant.

Read More

Daniela Rus CSAIL (2).JPG

MIT-CSAIL researchers visit Doha for annual QCRI research meeting

25/03/2018

Meeting updates joint research projects between the two institutions and will feature 'genius grant' recipient Prof. Regina Barzilay, who uses AI to detect cancer, as keynote speaker.

Read More

Arcpic1.jpg

QCRI’s Advanced Transcription System snares ARC’18 Best Innovation Award

19/03/2018

Her Highness Sheikha Moza bint Nasser presents accolade for system that automatically converts speech to text using state-of-the-art speech recognition techniques.

Read More