A. Seza Doğruöz

Automatic processing of large-scale language data is widely used for diverse AI tasks and applications. However, most of these systems target high resource languages based on the data available on the Internet which is limited in terms of linguistic variety, genres and domains. There is an increasing need for high quality and linguistically diverse data sets across domains for training and evaluation of the AI systems across different tasks.

As a board member, I will participate in the ELRA board meetings and contribute to the discussions about the current, future goals and strategic plans (e.g., increasing the visibility of ELRA internationally, promoting language resources for Human Language Technologies and low resource languages, communication with external partners, plans around the LREC conference and LRE journal, potential improvements on the website, improving the communication with the ELRA members to understand their needs and preferences). I will also bring in interdisciplinary research expertise and international experience as a member of the board to stimulate the discussions around the issues mentioned above.

Short Bio: After obtaining my PhD (Netherlands), I obtained research grants and carried out research projects at the University of California Santa Barbara (USA) and Carnegie Mellon University/ Language Technologies Institute (USA). Afterwards, I was in industry for a while (e.g., Google Research). Besides my current role as a professor at Universiteit Gent (Belgium), I have served several times as the Area Chair (AC) and the Senior Area Chair (SAC) for ACL’23, EMNLP’23 (outstanding SAC award), LREC-COLING’24, Best Paper Award Committee Member (EMNLP’24), expert evaluator for European Research Area for computational linguistics and AI. Broadly, my research investigates the linguistic diversity in human-human and human-systems interactions focusing on multilingual communication and low resource languages around the world through curating (collection, transcription, annotation) and analyzing multilingual data sets for linguistic and NLP related tasks.

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