Mouhssine Rifaki
I'm a reinforcement learning researcher and PhD student at Imperial College London. I hold a bachelor's in mathematics from Sorbonne and a master's from the MVA program at ENS Paris-Saclay.
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Research
My doctoral research aims to demonstrate that an agent can learn from nearly no data at all. Currently, millions of examples are needed by today's algorithms to recognize existing structures within a given problem. I am working toward identifying new methods for extracting this structure; doing so in the most difficult to identify (multi-agent) environments; as well as developing theoretical models to understand how the cost of learning decreases. These three goals all test the same hypothesis.
News
- September 2026Beginning PhD at Imperial College London, Department of Electrical and Electronic Engineering.
- April 2026Started working with the Arbabian Lab.
- March 2026Started working with the EMERGE Lab.
- March 2026Finished research visit at OIST.
- January 2026Started a research visit at OIST.
- September 2025Started the MVA master's at ENS Paris-Saclay.
- June 2025Finished M1 in applied mathematics at Sorbonne University.
- June 2023Finished BSc in mathematics at Sorbonne University.