MBZUAI adjunct professor Iryna Gurevych was appointed to the German National Academy of Sciences Leopoldina and received the “Social Impact Award” at the 18th Conference of the European Chapter of the Association for Computational Linguistics. The Social Impact Award recognized her study on sociodemographic prompting, a technique that steers prompt-based models towards answers reflecting specific sociodemographic profiles. Gurevych was also named one of the 15 most important women in AI in Germany by Manager Magazin for her work building an AI assistant with Amazon. Why it matters: Recognizing experts at MBZUAI raises the visibility of the university and its contributions to cutting-edge NLP research, particularly in areas like ethical and responsible AI development.
MBZUAI Adjunct Professor Iryna Gurevych has won the 2025 Royal Society Milner Award for her contributions to NLP and AI. The Milner Award recognizes outstanding European computer scientists and includes a bronze medal and a £5,000 honorarium. Gurevych's work focuses on processing big data with NLP tools, argument mining, and detecting misleading content. Why it matters: The award highlights MBZUAI's growing prominence in the international AI research landscape and Gurevych's work in making language models safer.
Iryna Gurevych from TU Darmstadt discussed challenges in using NLP for misinformation detection, highlighting the gap between current fact-checking research and real-world scenarios. Her team is working on detecting emerging misinformation topics and has constructed two corpora for fact checking using larger evidence documents. They are also collaborating with cognitive scientists to detect and respond to vaccine hesitancy using effective communication strategies. Why it matters: Addressing misinformation is crucial in the Middle East, especially regarding public health and socio-political issues, making advancements in NLP-based fact-checking highly relevant.
Iryna Gurevych from TU Darmstadt presented research on using large language models for real-world fact-checking, focusing on dismantling misleading narratives from misinterpreted scientific publications and detecting misinformation via visual content. The research aims to explain why a false claim was believed, why it is false, and why the alternative is correct. Why it matters: Addressing misinformation, especially when supported by seemingly credible sources, is critical for public health, conflict resolution, and maintaining trust in institutions in the Middle East and globally.
The InterText project, funded by the European Research Council, aims to advance NLP by developing a framework for modeling fine-grained relationships between texts. This approach enables tracing the origin and evolution of texts and ideas. Iryna Gurevych from the Technical University of Darmstadt presented the intertextual approach to NLP, covering data modeling, representation learning, and practical applications. Why it matters: This research could enable a new generation of AI applications for text work and critical reading, with potential applications in collaborative knowledge construction and document revision assistance.
MBZUAI graduate Svetlana Maslenkova worked with Assistant Professor Mohammad Yaqub on a project focused on the earlier detection of kidney failure using tabular data. Maslenkova's master's thesis involved predicting Acute Kidney Injury (AKI) using Electronic Health Records (EHR), specifically the MIMIC-IV v2.0 database. She found that patient weight distribution was a factor in the severity of kidney failure. Why it matters: This research highlights the potential of AI and machine learning to improve healthcare outcomes through the analysis of often-overlooked tabular data in electronic health records.
DERC's Aysha Al Neyadi won the Young Scientists Competition at the 14th International Conference Interaction of Radiation with Solids in Minsk, Belarus. Aysha co-authored a paper with researchers from Belarus State University and TII on the structure and phase composition stability of amorphous zirconium irradiated with helium ions. The paper examined amorphous alloy samples based on zirconium irradiated with Helium ions at 40 keV. Why it matters: This award recognizes contributions to materials science and highlights international research collaborations involving UAE institutions.
Dr. Teresa Lynn from Dublin City University (DCU) discussed the challenges in developing NLP tools for Irish, a low-resource language facing digital extinction. She highlighted the lack of speech and language applications and fundamental language resources for Irish. Lynn also mentioned her work at DCU on the GaelTech project and her involvement in the European Language Equality project. Why it matters: The development of NLP tools for low-resource languages like Irish is crucial for preserving linguistic diversity and preventing digital marginalization in the AI era.