Kimia Shaban
PhD Student, Computer Science, University of Toronto.
Advised by Dr. Babak Taati. Faculty Affiliate, Vector Institute. Research Appointee, KITE UHN.
I am a PhD student in Computer Science at the University of Toronto, working on AI for healthcare and computer vision.
Before my PhD, I completed an MMath in Combinatorics & Optimization at the University of Waterloo, supervised by Dr. Karen Yeats. I also worked with Dr. Paul-Hermann Balduf on machine learning for Feynman period estimation; our joint work is published in the Journal of High Energy Physics. My master’s thesis is available here.
I grew up in Waterloo, Ontario. Outside of research, I enjoy playing piano, hiking with my dog, and playing Tetris.
Mar 02, 2026 | New preprint: When Does RL Help Medical VLMs? — disentangling vision, SFT, and RL gains. Project page here. |
Sep 01, 2025 | Started my PhD in Computer Science at the University of Toronto, advised by Dr. Babak Taati. Also joined the Vector Institute as a Faculty Affiliate Researcher and KITE UHN as a Research Appointee. |
May 01, 2025 | Awarded the NSERC Canada Graduate Scholarship — Doctoral (CGS-D), $40,000/year for 2025–2028. |
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Preprint
When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains
Ahmadreza Jeddi, Kimia Shaban, Negin Baghbanzadeh, and 4 more authors
arXiv preprint, 2026
We study when reinforcement learning provides meaningful gains over supervised fine-tuning for medical vision-language models, disentangling the contributions of vision encoders, SFT, and RL to model performance.
@article{shaban2026medbridgerl,
title = {When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains},
author = {Jeddi, Ahmadreza and Shaban, Kimia and Baghbanzadeh, Negin and Sharan, Natasha and Moturu, Abhishek and Dolatabadi, Elham and Taati, Babak},
year = {2026},
journal = {arXiv preprint},
}
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JHEP
Predicting Feynman periods in φ^4-theory
Paul-Hermann Balduf and Kimia Shaban
Journal of High Energy Physics, Nov 2024
We apply machine learning to predict Feynman periods in φ⁴-theory, providing new computational tools for estimating the perturbative expansion of quantum field theories.
@article{balduf2024feynman,
title = {Predicting {F}eynman periods in $\phi^4$-theory},
author = {Balduf, Paul-Hermann and Shaban, Kimia},
journal = {Journal of High Energy Physics},
year = {2024},
month = nov,
publisher = {Springer},
doi = {10.1007/JHEP11(2024)038},
}