Qizhen Zhang (Irene)

I am a first year machine learning PhD student at the University of Oxford , where I work on reinforcement learing and multi-agent systems. My advisor is Jakob Foerster.

Prior to my PhD, I built large language models with the wonderful people at Cohere, and wrote my Master's thesis on cooperative multi-agent RL at the University of Toronto and the Vector Institute.

I obtained my Bachelor's at McGill University, while spending time at Mila. In a previous life, I wanted to become a doctor (the useful ones) and studied biochemistry for my first two years at McGill.

Send me puppy videos at qizhen [dot] zhang 🐕 jesus [dot] ox [dot] ac [dot] uk

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Highlighted Work

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Centralized Model and Exploration Policy for Multi-Agent RL

Qizhen Zhang, Chris Lu, Animesh Garg, Jakob Foerster
International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Full paper, Oral Presentation, 2022
arxiv / talk /

We propose a model-based method for fully cooperative multi-agent settings (Dec-POMDPs). Our method learns a centralized model, and is up to 20x more sample efficient in three commuication tasks. We also show theoretical sample complexity bounds for model-based methods learning in tabular Dec-POMDPs.


I was a teaching assistant for the following courses.


CSC311: Introduction to Machine Learning

CSC413/2516: Neural Networks and Deep Learning

CSC384: Introduction to Artificial Intelligence

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