Biography

As of Fall 2025, Kimia is a first-year PhD student in Computer Science at the University of Toronto, working with Dr. Babak Taati. Her team focuses primarily on computer vision for healthcare, and Kimia is currently working on machine learning approaches to support Parkinson’s disease diagnosis and monitoring. She is also part of the AMBIENT project, which focuses on gait analysis and 3D pose estimation for robust clinical prediction.

Kimia completed her Master of Mathematics in Combinatorics & Optimization at the University of Waterloo. Her thesis, “Combinatorial Aspects of Feynman Integrals and Causal Set Theory,” examined Feynman integrals from both a discrete combinatorics perspective and explored how machine learning techniques can be used to predict Feynman periods. She also holds a Bachelor of Mathematics in Combinatorics & Optimization with a specialization in Computing from the University of Waterloo. She has received numerous awards, including the NSERC Canada Graduate Scholarship – Doctoral (CGS-D), the NSERC CGS-M, the Ontario Graduate Scholarship, and the Combinatorics & Optimization Department’s Outstanding TA Award. She is affiliated with both the Vector Institute and the University Health Network (UHN).

Outside of research, Kimia has extensive volunteer experience, including work supporting patients in clinical environments as both a hospital volunteer and a medical assistant. She is also passionate about outreach for women in computer science and has contributed to multiple workshops and programs aimed at helping young women explore and enter the field.