I am a Ph.D. student in Computer Science at Columbia University, advised by Elias Bareinboim.

I research causal inference and its pivotal role in establishing generalizable machine learning. In particular, I utilize the formal language of causality to understand the fundamental challenges of prediction in the out-of-distribution (OOD) generalization problem. My primary focus is on the theoretical aspects of the topic, such as the asymptotic properties of learning algorithms and their performance guarantees.

Before joining Columbia, I completed my undergraduate degree in Computer Science and Economics at Sharif University of Technology, Tehran, Iran.

Email: kasra at cs dot columbia dot edu