Drew Springham

I research the mathematics and computational theory behind voting. Specifically, I look at voting systems in which there can be multiple winners, and so ideally we would like voting systems which produce outcomes where voters are proportionally represented in the outcome. The goal is to create a voting system which almost always gives us an approximately proportionally representative outcome in the scenario where we don’t have full information about the preferences of the voters.

I chose to study with the STAI CDT because of the broad range of training activities on offer. A good understanding of the philosophy and ethics of AI is crucial to exploring what exactly makes AI trusted and safe with respect to human values and behaviour. I believe that engaging with training in this area is absolutely necessary in order to become a responsible researcher in this field. Furthermore, the STAI CDT fosters an environment where I collaborate with a diverse and driven group of researchers with a variety of perspectives and ideas about safe AI, thereby amplifying the quality of my own research. 

Masters Qualification: Advanced Computer Science MSc, University of Oxford

Undergraduate Qualification: Mathematics and Computer Science BSc, University of Bristol

Work Experience:

  • Software Engineer, Darktrace
  • Data Scientist, Bank of England

LinkedIn: www.linkedin.com/in/drew-springham/