Bio

Paul Watson is Professor of Computer Science and Director of the Digital Institute at Newcastle University. He is PI of the EPSRC Centre for Doctoral Training in Cloud Computing for Big Data as well as the £30M National Innovation Centre for Data. He previously directed the £12M RCUK-funded Digital Economy Hub on Social Inclusion through the Digital Economy which focussed on using advanced computing technologies to transform the lives of older people and those with disabilities. He graduated in 1983 with a BSc in Computer Engineering from Manchester University, followed by a PhD on parallel computing in 1986. In the 80s, as a Lecturer at Manchester University, he was a designer of the Alvey Flagship and Esprit EDS systems. From 1990-5 he worked for ICL as a system designer of the Goldrush MegaServer parallel database server, which was released as a product in 1994.

In August 1995 he moved to Newcastle University, where he has led a range of research projects. His research interest is in scalable information management with a current focus on Data Analytics and IoT. He sits on the board of Dynamo North East, an industry-led organisation created to grow the IT economy of the region. He is also a member of the Department for Transport Science Advisory Council. Professor Watson is a Fellow of the Royal Academy of Engineering, a Fellow of the British Computer Society, a Chartered Engineer and a member of the UK Computing Research Committee. He received the 2014 Jim Gray eScience Award.

Research interests

Paul's research focuses on designing, building and evaluating the next generation of scalable data analytics systems. He uses real-world applications – mainly drawn from healthcare - to inspire and evaluate our research.  Current work includes:

- the automatic partitioning, deployment and scaling of distributed IoT systems based on declarative descriptions of functional and non-functional properties. We apply these tools and techniques to systems that typically span wearables, mobile phones, and clouds, ensuring that they meet performance, security, bandwidth and energy requirements.

- the e-Science Central end-to-end data analytics platform that supports the ingestion, storage, sharing, discovery and analysis of data. This underpins a range of projects and labs, in both universities and industry