My research brings together expertise in language, data science, and educational measurement to develop and evaluate artificial intelligence applications in dentistry, medicine, and education. I specialize in natural language processing (NLP), combining an understanding of language and assessment with computational methods for analysing clinical and educational text.
My expertise is grounded in two complementary PhDs. I completed my first PhD in Applied Linguistics, specializing in language testing and assessment, at Shahid Chamran University of Ahvaz in 2019. To extend this foundation with advanced training in computational and measurement methods, I pursued a second PhD in Measurement, Evaluation, and Data Science at the University of Alberta, completed in 2023 under the supervision of Dr. Mark Gierl. My research on automated essay scoring brought these fields together through the application of transformer-based language models. This integration of linguistic knowledge, data science, and measurement provides the foundation for my approach to NLP: understanding not only how language can be modelled computationally, but also how the resulting analyses and scores should be interpreted and evaluated.
I extended this interdisciplinary expertise into health sciences through an Alberta Innovates Postdoctoral Fellowship at the University of Alberta’s School of Dentistry (2023–2025), working with Dr. Hollis Lai. My postdoctoral research applied computational methods to clinical information, including the analysis of clinicians’ notes for dental research. I am a member of the Oral Health Analytics and Informatics (OHAI) Unit at the Mike Petryk School of Dentistry, contributing to a research environment that connects clinical practice with technological innovation in oral health.
My current research focuses on transformer-based language models and graph-based retrieval-augmented generation to structure unstructured clinical information and advance dental analytics. In education and health professions assessment, my work encompasses multilingual automated essay scoring, automatic item generation, and AI-supported feedback. These research directions connect the development of language technologies with questions about how they can support assessment, learning, and clinical reasoning.
I lead funded research on AI-supported assessment and learning, including a SSHRC Insight Development Grant examining university instructors’ perceptions of AI-assisted improvements to multiple-choice questions. My scholarship includes publications in the Journal of Educational Measurement and the Journal of Graduate Medical Education, as well as an invited chapter on multilingual automated essay scoring in The Routledge International Handbook of Automated Essay Evaluation. Alongside my research, I develop and teach graduate courses that equip students to apply NLP methods to the extraction, analysis, and interpretation of textual healthcare data.