Ruiyang Zhang
PhD studentResearch Overview
I am broadly interested in computational statistics and machine learning methodologies, and their applications in scientific and engineering disciplines. In particular, I aim to develop methodologies with strong relevance to applications.
Currently, I am investigating sequential Bayesian experiment designs (such as active learning and Bayesian optimization) and their application in oceanographic sensor deployment. I am also actively thinking about other tasks that could be improved using experiment design, or could be cast as a design problem.
Research Interests
- Sequential Bayesian Experiment Design, Bayesian Optimization, Active Learning
- Probabilistic Numerics
- Gaussian Process Modelling
- MCMC, SMC, Simulation-Based Inference
Supervised By
David Leslie, Henry Moss, Edward Cripps, Lachlan Astfalck
Web Links
Personal Website: https://shusheng3927.github.io/
- STOR-i Centre for Doctoral Training