Aida Ramezani

Aida Ramezani

Ph.D. student at the Departmant of Computer Science, University of Toronto

I’m a final year Ph.D. student at the Department of Computer Science, University of Toronto. My research explores the interplay of language, morality, and AI. I take a multidisciplinary approach drawing on natural language processing, machine learning, moral psychology, cognitive science, and computational social science. My current focus is on developing computational methodologies for understanding temporal and cultural variation in moral values informed by how people use language and AI tools.

Awards

  • Schwartz Reisman Institute for Technology and Society Graduate Affiliate, 2022-2025.
  • Cognitive Science Society Disciplinary Diversity & Integration Award, 2024.
  • Schwartz Reisman Institute for Technology and Society Graduate Fellowship, 2021-2022.
  • Iran’s National Elites Foundation: Recognized as elite member, 2016-2020.

Publications

  • Ramezani, A., Stellar, J.E., Feinberg, M., and Xu, Y. Evolution of the moral lexicon. Open Mind (2024). pdf, code

  • Ramezani, A., Liu, E., Lee, S., Xu, Y. Quantifying the emergence of moral foundational lexicon in child language development. PNAS Nexus (2024). pdf, code.

  • Ramezani, A., and Xu, Y. Moral association graph: A cognitive model for moral inference. In Proceedings of the 46th Annual Meeting of the Cognitive Science Society. Disciplinary Diversity & Integration Award. pdf, code. To appear in topiCS, 2024.

  • Ramezani, A., and Xu, Y. Knowledge of cultural moral norms in large language models. In Proceedings of the 61th Annual Meeting the Association for Computational Linguistics: ACL 2023. pdf, code.

  • Ramezani, A., Stellar, J.E., Feinberg, M., and Xu, Y. Evolution of moral semantics through metaphorization. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society. pdf, code.

  • Ramezani, A., Liu, E., Ferreira Pinto Jr., R., Lee, S., Xu, Y. The emergence of moral foundations in child language development. In Proceedings of the 44th Annual Meeting of the Cognitive Science Society. pdf.

  • Ramezani, A., Zhu, Z., Rudzicz, F., and Xu, Y. An unsupervised framework for tracing textual sources of moral change. Findings of the Association for Computational Linguistics: EMNLP 2021. pdf, code.

Education

  • Ph.D. in Computer Science, University of Toronto, September 2020 – Present
  • B.S. in Computer Engineering, Sharif University of Technology, September 2016 - July 2020