The Sargent Centre is delighted to announce we are hosting another Summer School in 2026, on the topic of Data-driven optimisation: Bayesian optimisation.
The school will consist of preliminary tutorials on Gaussian processes and Bayesian optimisation. Attendees will gain a foundation in the underlying principles, and learn probabilistic modelling and sequential decision-making. With hands-on exercises, students will develop their understanding of how Gaussian processes serve as powerful tools for modelling uncertainty and guiding decision-making processes.
As the program develops, participants will explore Bayesian optimisation from different experts, going into diverse applications across high-dimensional spaces, molecular discovery, real-time optimisation, and safety-critical systems in science and engineering.
From navigating the complexities of multi-fidelity Bayesian optimisation to harnessing the potential of batch Bayesian optimisation for high-throughput experimentation, students will discover how Bayesian techniques can be used both in industry and academia.
