Interested in the technology behind AlphaGo, recommender systems, and modern robotics? Reinforcement learning is arguably the most complex, but most exciting branch of machine learning to gain traction in recent years. Any problem that can be cast as an agent interacting with its environment to maximise some reward function can be solved using reinforcement learning. Fancy learning the theory behind these ideas and how to apply some state of the art algorithms?
DPhil in Engineering - University of Oxford
In her PhD, she presented scalable multi-agent reinforcement learning algorithms for the distributed control of residential energy flexibility, including electric vehicles and smart heating. The novel optimisation-based learning approach drastically improved the scalability of prosumer cooperation in stochastic environments in a privacy-preserving way.
University of Oxford
GDSC Lead
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Events Lead
Kinsta
Sponsorship, Partnership, Careers
Events Lead
Sponsorship, Partnership, Careers
Events and Marketing
