Zahra Khalid

Zahra holds a B.S. in Data Science from LUMS and an M.S. in Machine Learning from the University of Toronto. She started in healthcare analytics, favoring interpretable models that clinicians could trust over black-box gains. That philosophy guides her writing on bias audits, dataset documentation, and ML monitoring that watches for drift without drowning teams in alerts. Zahra translates math into metaphors people keep quoting, and she’s happiest when a product manager says, “I finally get it.” She mentors through women-in-data programs, co-runs a community book club on AI ethics, and publishes lightweight templates for model cards. Evenings are for calligraphy, long walks after rain, and quiet photo essays about city life that she develops at home.