Mohamed Eldesouki is a research associate and a software engineer with senior Researching and Developing skills and a wide technical and academic background in the fields of Arabic Language Technologies (ALT) and Machine Learning (ML) with a broad experience covering a diverse set of software development tools, languages and methodologies, gathered throughout almost 11 years of experience.
Mohamed has participated in designing, implementing and maintaining of NLP-related project such as Search Engines, Content-based Recommendation Systems, Auto-complete and correction for mobile devices, and Intelligent Tutoring Systems (ITS) for both Arabic and English content .
With a strong academic foundation in Information Retrieval (IR) and Information Extraction (IE) gained through the conducted research activities and studies of the MASTER’S DEGREE and deep linguistic analysis, Natural language Understanding NLU and Machine comprehension of text currently through his work at Qatar Computing Research Institute (QCRI).
Qatar Computing Research Institute (QCRI), Doha, QatarDEc 2015 - Present
OMS Company, Cairo, EgyptJan 2015 - Dec 2015
Taya IT Company, Cairo, EgyptAug 2013 - Dec 2014
MGD Company, Cairo, EgyptJul 2012 - Aug 2013
Institute of Statistical Studies and Research (ISSR), Cairo University, Cairo, EgyptJul 2009 - Jun 2012
Cairo University; Giza, Egypt2012
Cairo University; Giza, Egypt2003
Language Processing and Learning Models for Community Question Answering in Arabic, Information Processing & Management, Volume 56, Issue 2, March2019, Pages 274-290. [ARTICLE]2019
QCRI-MITLive Arabic Dialect Identification System, QCRI - MIT CSAIL Annual Meeting Qatar National Convention Centre March 27-28, 2018. [POSTER]2018
QCRI-MIT Live Arabic Dialect Identification System, ICASSP, Calgary, Canada. [DEMO]2018
Multi-Dialect Arabic POS Tagging: A CRF Approach, In 11th edition of the Language Resources and Evaluation Conference (LREC), 7-12 May 2018, Miyazaki (Japan).2018
Learning from Relatives: Unified Dialectal Arabic Segmentation. In Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), Vancouver, Canada, 432-441.2017
ClassStrength: A Multilingual Tool for Tweets Classification, Proc. of the 2017 IEEE/ACM International Conference on Advances in social networks analysis and mining (ASONAM), Sydney, Australia, 593-596.2017
Arabic Multi-Dialect Segmen-tation: bi-LSTM-CRF vs. SVM,http://arxiv.org/abs/1708.05891.2017
A Neural Architecture for Dialectal Arabic Segmentation. In Proc. of The 3rd Arabic Natural Language Processing Workshop (WANLP-2017) co-located with EACL 2017, Valencia, Spain, pages 46-54.2017
Arabic POS Tagging: Don’t Abandon Feature Engineering Just Yet, In Proc. of The 3rdArabic NLP Workshop (WANLP-2017) co-located with EACL 2017, Valencia, Spain, P.130.2017
QCRI@ DSL 2016: Spoken Arabic Dialect Identification Using Textual Features, Proc. of the3rd Workshop on NLP for Similar Languages, Varieties and Dialects, (VarDial 3), Osaka,Japan, P. 221.2016
Master’s Thesis, Cairo University.2012
Rep-resenting Arabic Documents Using Controlled Vocabulary Extracted from Wikipedia, InProc. of The 11th Conference on Language Engineering (ESOLEC’11), Cairo, Egypt.2011
UsingWikipedia for Retrieving Arabic Documents. In Proceedings of Arabic Language Tech-nology International Conference (ALTIC 2011), Alexandria, Egypt.2011
Stemming tech-niques of Arabic Language: Comparative Study from the Information Retrieval Perspec-tive, The Egyptian Computer Journal. 36(1):30-49.2009