
Assistant Professor @mbzuai-nlp
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MBZUAI
Data Scientist
June 25, 2026 – Present
text-editing
October 15, 2024 – Present
Code, models, and data for "Enhancing Text Editing for Grammatical Error Correction: Arabic as a Case Study", ACL 2025
View Projectsamer-arabic-readability
May 13, 2024 – July 25, 2024
Code, models, and data for "Strategies for Arabic Readability Modelling". ArabicNLP 2024, ACL.
View Projectpersonalized-gen
January 28, 2024 – February 8, 2024
Code, models, and data for "Personalized Text Generation with Fine-Grained Linguistic Control". EACL 2024, Personalization of Generative AI.
View Projectarabic-gec
November 3, 2022 – August 29, 2024
Code, models, and data for "Advancements in Arabic Grammatical Error Detection and Correction: An Empirical Investigation". EMNLP 2023.
View ProjectCrisisTimelines
August 23, 2022 – June 24, 2023
Code and models for "CrisisLTLSum: A Benchmark for Local Crisis Event Timeline Extraction and Summarization". Findings of EMNLP 2022.
View Projectarabic_error_type_annotation
June 23, 2021 – October 28, 2022
The Arabic Error Type Annotation tool aims to annotate Arabic error types following the ALC tagset annotation.
View Projectarafix_ocr
May 24, 2021 – September 22, 2021
A tool for improving the output of generic Arabic OCR systems using an n-gram based post-correction approach.
View ProjectCAMeLBERT
February 20, 2021 – June 21, 2024
Code and models for "The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models". EACL 2021, WANLP.
View Projectcamel_tools
October 5, 2017 – Present
A suite of Arabic natural language processing tools developed by the CAMeL Lab at New York University Abu Dhabi.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily concentrated on academic research in Arabic NLP, which aligns well with roles requiring deep specialization in this domain. The diversity of projects within NLP (readability, error correction, text generation, crisis timelines) shows breadth within their niche. The current role as 'Data Scientist' at MBZUAI aligns with the target role. However, the lack of projects outside of academic NLP research might indicate a narrower scope of experience for broader data science roles, potentially impacting cultural fit for teams requiring diverse data science applications.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong focus on research and development, suggesting a detail-oriented and problem-solving approach. The nature of the projects implies an ability to work independently and contribute to complex technical challenges. However, without specific assessment data on communication, logical reasoning, or teamwork, it is difficult to fully assess soft skills and operational fit beyond technical contributions.