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Generative models with diffusion

The powerful engines behind synthetic data generation in AI are diffusion models, aka, stochastic differential equations. A success story that draws a lot of public attention recently is the generation of high-resolution images from text prompts, e.g. stable diffusion and DALLE-2, which have achieved amazing results.

The objective of this project is twofold. First, we aim to explore the application of diffusion models to generation of other data types, e.g. network data. One use case of this extension is drug discovery. Second, we aim to analyse the mathematical properties of diffusion models for various data structures.

You should have a background in Probability and Statistics. It would be advantageous to have experience in Programming (language agnostic). You should be a highly motivated individual and possess a strong sense of curiosity. The ability to study independently, think critically and collaborate with others is essential.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

  1. Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
  2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
  3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)

Xiaochuan Yang - I am Lecturer in Mathematics/Statistics at Brunel. My research interest lies in Probability Theory and its connection with analysis, statistics, and other disciplines of science and technology such as physics, machine learning, geometric and topological data analysis. Before joining Brunel, I held the position of EPSRC postdoc at the University of Bath, the Luxembourg-Singapore bilateral postdoc position, and visiting assistant professor position at Michigan State University. 

Related Research Group(s)

Statistics and Data Science

Statistics and Data Science - Strategic growth area of statistical methods and models for data science.