Hi ^_^


I’m currently a Machine Learning Researcher affiliated with the Princeton Robot Planning and Learning Group (PRPL) and the UBC Natural and Artificial Intelligence Lab (NAIL), working with Dr. Tom Silver and Dr. Kelsey Allen. I will begin my PhD in September 2026 under their supervision. Before this, I completed my Master’s in Computer Science at the University of Alberta under the supervision of Dr. Levi Lelis.

Currently, my research focuses on building agents that can learn physical strategies from only a few demonstrations. In particular, I study programmatic policies and learned abstractions that help agents generalize beyond the examples they observe. More broadly, I’m interested in how we can build systems that learn, reason, and understand the world more like humans, using ideas from symbolic reasoning, neurosymbolic AI, reinforcement learning, and imitation learning.

You can contact me at 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