SALWA ALAHMARI

Dynamic educator with over a decade of experience in higher education, dedicated to advancing the fields of linguistics and technology. Passion for researching Natural Language Processing (NLP) specifically tailored to Arabic dialects, striving to merge traditional linguistic studies with modern computational methods. Proven ability to engage in rigorous research, focusing on the unique characteristics of Saudi Arabic dialects. Committed to fostering collaborations that enhance understanding and application of language technologies, with aspirations to contribute to impactful advancements in AI and linguistic studies. Eager to continue exploring innovative solutions that bridge language and technology for broader societal benefits.

During my PhD Study at the University of Leeds, I have published number of scientific papers with my supervisors:

• Alahmari, S., Atwell, E., Alsalka, M.A. (2024). Saudi Arabic Multi-dialects Identification in Social Media Texts. In: Arai, K. (eds) Intelligent Computing.SAI 2024. Lecture Notes in Networks and Systems, vol 1016. Springer, Cham.

• Alahmari S. 2025. SADSLyC: A Corpus for Saudi Arabian Multi-dialect Identification through Song Lyrics. The 31st International Conference on Computational Linguistics (COLING2025).

• Salwa Saad Alahmari. 2025. Saudi Arabian Multi-Dialects Identification Using Ensemble Transformer-based Model. ACCEPTED @ 13th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA-2025) June 06 - 07, 2025.

• Salwa Saad Alahmari. 2024. SiriusTranslators at OSACT6 2024 Shared Task: Fin-tuning Ara−T5 Models for Translating Arabic Dialectal Text to Modern Standard Arabic. In Proceedings of the 6th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT) with Shared Tasks on Arabic LLMs Hallucination and Dialect to MSA Machine Translation @ LREC-COLING 2024, pages 117–123, Torino, Italia. ELRA and ICCL.

• Salwa Alahmari, Eric Atwell, Mohammad Alsalka, and Hadeel Saadany. 2024. Evaluating the Performance of LLMs When Translating Saudi Arabic as Low Resource Language. In Artificial Intelligence XLI: 44th SGAI International Conference on Artificial Intelligence, AI 2024, Cambridge, UK, December 17–19, 2024, Proceedings, Part II. Springer-Verlag, Berlin, Heidelberg, 264–269.

• Alahmari, S. , Atwell, E. and Alsalka, M. A. (2024) ChatGPT for Identifying Saudi Arabic Dialects. International Journal on Islamic Applications in Computer Science And Technology, 12 (1). pp. 12-18. ISSN 2289-4012.

• Alahmari, S. , Atwell, E. and Alsalka, M. A. (2025).Arabic-Centric Large Language Models for Dialectal Arabic Sentiment Analysis Task. (ACCEPTED) @Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing (RANLP).September. Bulgaria.