Laleh Seyyed-Kalantari
Appointment
Solution Network Co-Director
Canadian AI Safety Institute Research Program
Mitigating Dialect Bias
About
Laleh Seyyed-Kalantari’s research focuses on fairness, bias mitigation, and digital inclusion across cultural, social, and healthcare domains. Her research works to ensure equitable representation of marginalized groups, languages, and cultural expressions in AI systems, such that AI models benefit all. By utilizing generative AI and foundation models, along with design adaptation strategies, her work enhances performance for underrepresented groups and promotes equitable access to emerging AI technologies. While some of her work extends into health and societal applications, the broader intellectual agenda is developing AI systems that serve society by embedding cultural and ethical context.
Awards
- 2025 York University Research Award, York University (2025)
- Google Research Scholar Award, Google Co. (2024)
- Vector Institute Faculty Affiliate (2023)
- Banting Postdoctoral Fellowship (declined-2022)
- NSERC Postdoctoral Fellowship, NSERC, 2018
Relevant Publications
- L. S. Kalantari, H. Zhang, M. McDermott, I. Y. Chen, and M. Ghassemi, ‘Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations’, Nature Medicine, Vol. 27, 2176–2182, 2021.
- J. W Gichoya, I. Banerjee, A. R. Bhimireddy, J. L Burns, L. A. Celi, L. Chen, R. Correa, N. Dullerud, M. Ghassemi, S. Huang, P. Kuo, M. Lungren, L. Palmer, B. Price, S. Purkayastha, A. Pyrros, L. Oakden-Rayner, C. Okechukwu, L. S. Kalantari, H. Trivedi, R. Wang, Z. Zaiman, H. Zhang, ‘AI recognition of patient race in medical imaging: a modelling study’, The Lancet Digital Health, Vol. 4, Issue 6, e406 – e414, 2022., May 11, 2022.
- A. M. Zadeh Khaki, A. Choi, L. S. Kalantari, Simulating social behavior of LLM-based autonomous negotiator agents in a game-theoretical framework using multi-agent system, International Journal of Human Computer Interaction, accepted Apr. 2025.
- N. Gohari Sadr, K. Megerdoomian, L. S. Kalantari, A. Emami, We Politely Insist: Your LLM Must Learn the Persian Art of Taarof, Empirical Methods in Natural Language Processing (EMNLP), main track, Suzhou, China, 2025.
- Esmaeilzehi, H. Zaredar, Y. Tian, L. S. Kalantari, ZFusion: Efficient Deep Compositional Zero-shot Learning for Blind Image Super-Resolution with Generative Diffusion Prior, International Conference on Computer Vision (ICCV), Honolulu, Hawaii, US, 2025.