Qizhen Zhang (Irene)

I am a first year machine learning PhD student at the University of Oxford, where I work on Large Language Models and reinforcement learning. My advisor is Jakob Foerster. I'm also spending half of my time doing research at Cohere, hosted by Phil Blunsom.

Prior to my PhD, I was a member of technical staff at Cohere building frameworks and training LLMs. I wrote my Master's thesis on cooperative multi-agent reinforcement learning at the University of Toronto and the Vector Institute.

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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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