Projects per year
Personal profile
Biography
Dr. Eltabakh is a Principal Scientist at Qatar Computer Research Institute (QCRI). He received his Ph.D. degree in Computer Science from Purdue University in 2010. He was a faculty member at the Computer Science Department, Worcester Polytechnic institute (WPI), MA, USA between 2011 and 2022. He has extensive industry-related experience working at Google, Microsoft, IBM, and Teradata (in USA) for more than 8 years combined. Dr. Mohamed Eltabakh’s research expertise falls under the broad areas of big data management, scalable data analytics, AI and Large Language Models, and distributed systems. Dr. Eltabakh is leading the Fanar project, an Arabic-Centric GenAI platform developed in Qatar. Dr. Eltabakh’s research is funded by several entities including National Science Foundation (NSF), USA, Ministry of Transportation (MoT), Qatar, and Ministry of Interior (MoI), Qatar.
Education/Academic qualification
Computer Science, PhD, Purdue University
1 May 2005 → 31 May 2010
Award Date: 10 May 2010
External positions
Associate Professor in the Computer Science Department, Worcester Polytechnic Institute
1 Jul 2017 → 1 Oct 2022
Consultant and Technical Lead, Teradata Corporation
10 May 2017 → 31 Aug 2022
Assistant Professor in the Computer Science Department, Worcester Polytechnic Institute
1 Jul 2011 → 30 Jun 2017
Keywords
- Q Science (General)
- Computer Science
- AI
- database systems
- distributed systems
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Collaborations and top research areas from the last five years
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Projects
- 3 Active
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QCRI-CORE-000006: Fanar Arabic-Centric Large Language Model
Eltabakh, M. A. Y. (Lead Principal Investigator)
1/11/23 → 1/06/26
Project: Applied Research
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QCRI-CORE-000004: Data Management Systems
Eltabakh, M. A. Y. (Lead Principal Investigator)
1/01/24 → 1/06/26
Project: Applied Research
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EX-MOT-AI-1: Enterprise Q&A System using Large Language Models (LLMs)
Yang, D. (Principal Investigator) & Eltabakh, M. A. Y. (Lead Principal Investigator)
1/11/25 → 31/10/26
Project: Experimental Development/Translation Research
Research output
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Cross Modal Data Discovery over Structured and Unstructured Data Lakes
Eltabakh, M. Y., Elmagarmid, A. K., Kunjir, M. & Ahmad, M. S., 2023, In: Proceedings of the VLDB Endowment. 16, 11, p. 3377-3390 14 p.Research output: Contribution to journal › Conference article › peer-review
7 Citations (Scopus) -
RetClean: Retrieval-Based Data Cleaning Using LLMs and Data Lakes
Naeem, Z. A., Ahmad, M. S., Eltabakh, M., Ouzzani, M. & Tang, N., 1 Aug 2024, In: Proceedings of the VLDB Endowment. 17, 12, p. 4421-4424 4 p.Research output: Contribution to journal › Article › peer-review
6 Citations (Scopus) -
CLIMBER: Pivot-Based Approximate Similarity Search over Big Data Series
Zhang, L., Eltabakh, M. Y., Rundensteiner, E. A. & Alnuaim, K., 16 May 2024, Proceedings - 2024 IEEE 40th International Conference on Data Engineering, ICDE 2024. IEEE Computer Society, p. 3933-3946 14 p. (Proceedings - International Conference on Data Engineering).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
1 Citation (Scopus) -
PARROT: pattern-based correlation exploitation in big partitioned data series
Zhang, L., Alghamdi, N., Zhang, H., Eltabakh, M. Y. & Rundensteiner, E. A., May 2023, In: VLDB Journal. 32, 3, p. 665-688 24 p.Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Analytics at Scale: Evolution at Infrastructure and Algorithmic Levels
Al-Kateb, M., Eltabakh, M. Y., Al-Omari, A. & Brown, P. G., 2022, Proceedings - 2022 IEEE 38th International Conference on Data Engineering, ICDE 2022. IEEE Computer Society, p. 3217-3220 4 p. (Proceedings - International Conference on Data Engineering; vol. 2022-May).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review