Arabic NLP and ontologies researcher; builds shared tasks and benchmarks for Arabic language technology
3
papers here
2
reviewed by Evolve
0
first-author
0
corresponding
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works · OpenAlex
24
h-index · OpenAlex
Bibliometric figures come from OpenAlex (2026-10-17) and cover the author's entire public record, not just the papers listed here. Reproducibility signal comes from Evolve's own reviews.
Research profile
Output—
Not yet scored. This axis would measure publication volume and productivity trends over the career; per-year counts appear in the raw record, but bibliographic coverage behind the axis is still incomplete, so no output score is computed here.
Impact—
Not yet scored. This axis would measure citation-based influence such as citations per paper and field-normalized impact; citation coverage is incomplete here, though the raw record lists an h-index of 24 and an i10-index of 43 without a derived score.
Focus0/100
The radar scores focus at 0. The underlying fieldDist splits evenly (0.5/0.5) between computational linguistics/Arabic NLP and NLP/machine translation — adjacent areas — while the topic list spans five clusters led by Semantic Web and Ontologies (85) and NLP Techniques (77), with Topic Modeling (55), Biomedical Text Mining (42) and Sentiment Analysis (37) behind, indicating breadth rather than one narrow line.
Collaboration66/100
Collaboration scores 66. The raw record lists 27 distinct coauthors, and the frequent-coauthor list includes Mo El-Haj, Saad Ezzini, Samir Abdaljalil, Nadir Durrani, Fahim Dalvi and Erchin Serpedin. On all three 2026 catalog papers this researcher holds a middle author position with no corresponding role, consistent with consortium-style shared-task papers aggregating many contributors.
Activity100/100
Activity scores a full 100. Counts by year show a pronounced recent acceleration: 17 works in 2023, 23 in 2024, 14 in 2025 and 22 already in 2026, against 1-5 per year through 2019-2022; recent3yWorks totals 59. All three catalog papers date from 2026, confirming that current output is concentrated in shared tasks and evaluation resources.
Reproducibility55/100
Reproducibility scores 55, a mean computed over 2 assessed papers. Both 2026 shared-task papers (AraGenre 2026 and AlexandriaX 2026) carry a medium reproducibility-readiness rating; Evolve's reviews find the task designs sound and results honestly reported, while flagging thin gold-label validation and ranking caveats such as a transductive winner and single-reference spBLEU.
Research summary
Mustafa Jarrar is a researcher at Hamad bin Khalifa University working across Arabic natural language processing, machine translation, and semantic web technologies. The bibliometric record, resolved from OpenAlex, lists an h-index of 24, an i10-index of 43, and 27 distinct coauthors. Output is heavily back-loaded: 59 works in the last three years, with per-year counts rising from 1-5 across 2019-2022 to 17 in 2023, 23 in 2024, 14 in 2025 and 22 already in 2026 — the basis for a maximal activity score of 100. The topic distribution is led by Semantic Web and Ontologies (85) and Natural Language Processing Techniques (77), followed by Topic Modeling (55), Biomedical Text Mining and Ontologies (42), and Sentiment Analysis and Opinion Mining (37), while the field distribution splits evenly (0.5/0.5) between Arabic NLP and machine translation. Recent catalog papers show a pivot toward community evaluation infrastructure: AraGenre 2026 on definition-guided zero-shot Arabic genre classification and AlexandriaX 2026, the first shared task on dialectal Arabic machine translation, both judged methodologically sound with noted evaluation caveats, plus ImageEval 2026 on culturally grounded Arabic multimodal evaluation. Reproducibility readiness is rated medium for both reviewed shared tasks, with a mean reproducibility score of 55.
Collaboration pattern
The collaboration score of 66 rests on 27 distinct coauthors. Recent work is consortium-style: on all three 2026 catalog papers this researcher sits in a middle author position without a corresponding role. Recurring partners include Mo El-Haj, Saad Ezzini, Samir Abdaljalil, Nadir Durrani, Fahim Dalvi and Erchin Serpedin, alongside Basel Mousi, Ahlam Bashiti, Hunzalah Hassan Bhatti, Farina Amir, Md Arid Hasan and Zien Sheikh Ali.
Research keywords
Highlights
AraGenre 2026: definition-guided Arabic genre classification
AlexandriaX 2026: first shared task on dialectal Arabic MT
A 2026 evaluation program for Arabic language technology
Alongside the two shared tasks, ImageEval 2026 targets culturally grounded Arabic multimodal evaluation. Together, the three 2026 catalog papers mark a turn toward community benchmarks and evaluation infrastructure for Arabic, consistent with the maximal activity score and 59 works in the last three years.
Timeline
- 2026AraGenre 2026 is released: a hierarchical, definition-guided shared task for zero-shot Arabic genre classification.
- 2026AlexandriaX 2026, the first shared task on dialectal Arabic machine translation, spans three subtasks: cross-dialect translation, MT error detection and quality estimation.
- 2026ImageEval 2026 extends the program to culturally grounded Arabic multimodal evaluation, completing a three-paper year in which 22 works are recorded.
Papers in the Evolve catalog
Frequent co-authors
About this profile
This profile is AI-structured by Evolve.Pub from public bibliographic data (OpenAlex) and Evolve's own paper reviews. It is not written or endorsed by the researcher unless the profile is claimed. Radar dimensions are computed from real bibliometrics with fixed formulas — raw figures are shown alongside; missing dimensions mean insufficient data, never zero. Errors? Claim the profile to correct or hide it.
- Bibliometric figures come from OpenAlex identity resolution; citation and venue coverage may lag or undercount.
- Output and impact radar axes are unscored; the h-index of 24 and i10-index of 43 are raw record values, not verified against full citation graphs.
- Only three catalog papers are covered, two with full Evolve verdicts; the reproducibility score of 55 averages just those two papers.
- All timeline entries derive from the three 2026 catalog papers; earlier career milestones fall outside the provided data scope.