The Centre for Robust Inference in a Digital Economy (RIDE) was approved by Royal Holloway in October 2016. Its main area of research is robust inference as the basis for robust decision making in finance, economics, and other social sciences.

The emphasis is on the opportunities and challenges resulting from the digitalisation of society, e.g. big data availability, flash crashes and abuse in financial markets caused by algorithms,data integrity/fabrication of electronic surveys, etc.

We are interested in methods to conduct inference and making decisions which are nearly optimal in the face of considerable uncertainty and in ways to make various social networks of decision makers (such as financial markets) less fragile and prone to users' abuse.

Developing robust methods of prediction is also covered,as prediction can be fruitfully considered as a special case of both inference and decision making.

The basis of inference is data, and therefore we are also interested in data collection data processing, including data analysis and big-data technologies (such as MapReduce)and data distribution.

Here are some of our goals:

• Developing robust methods of inference
• Developing robust methods of decision making
• Developing methods of making various social networks (including financial markets) less fragile
• Defining and testing various regulations and policy mechanisms to make society immune from treats  that arise implicitly or explicitly in the digital economy using data and economic experiments.