Hi ^_^


I’m a PhD student in Computer Science at the University of British Columbia, co-advised by Dr. Kelsey Allen at UBC and Dr. Tom Silver at Princeton University. I’m also affiliated with Princeton Robot Planning and Learning Group (PRPL). Before this, I completed my Master’s in Computer Science at the University of Alberta under the supervision of Dr. Levi Lelis.

I’m interested in understanding how to learn physical strategies from only a few demonstrations and generalize beyond what was observed. Currently, I study how learned abstractions and structured policies can support generalization from limited experience. More broadly, I’m interested in reinforcement learning, world models, and cognitively inspired approaches to learning and reasoning.

You can contact me at zbashir1@student.ubc.ca OR zb2882@princeton.edu.

Publications

What to Represent, How to Act: Programmatic Feature Induction for Few-Shot Bayesian Imitation

Zahra Bashir, Kelsey Allen, Tom Silver RLC — RL in Big Worlds

SEGClobber — A Linear Clobber Solver

Taylor Folkerson, Zahra Bashir, Fatemeh Tavakoli, Martin Müller International Computer Games Association

Plastic Programming Languages: Learning Neuro-Augmented Domain-Specific Languages

Zahra Bashir, David Aleixo, Kevin Ellis, Levi Lelis In preparation

LINT: Assessing the Interpretability of Programmatic Policies with Large Language Models

Zahra Bashir, Michael Bowling, Levi Lelis RLC 2024 InterpPol Workshop