I am a Professor of Computer Science, in the Web and Internet Science Group (WAIS), in Electronics and Computer Science at the University of Southampton. My research is in the area of database systems, focusing on using data appropriately and effectively. This involves solving problems that span the areas of databases, information discovery and retrieval, provenance, and algorithmic accountability. I work closely with clinical practitioners and other health-deliverers in order to understand their needs, refine my research and apply it. I have worked closely with the US Federal government, and influenced the Office of the National Coordinators (ONC) report on the usage of provenance within electronic health systems. I have advised the US Food and Drug Agency (FDA) , the National Geospatial-Intelligence Agency (NGA), and the Department of Homeland Security (DHS) on data management problems.
I chair the steering committee of the Theory and Practice of Provenance (TaPP) and ProvenanceWeek. I am the recipient of the 2016 ACM SIGMOD Test of Time Award for my work on provenance. I run a Science Fair for the local primary schools to encourage the joy of research in budding scientists.
To apply for a PhD with me, please provide a research proposal that aligns with my interests and follow the ECS PhD application process.
Artificial Intelligence and Data Science are making huge strides in improving the human condition, helping us to make decisions and utilize resources better. We are creating a new economy - the data economy. In support of this, my research revolves around how to ensure that data required for artificial intelligence and data science can be found and used appropriately. This includes:
- Dataset retrieval: How can we discover datasets and rapidly assess which is suitable for a given task?
- Data improvement: Can we provide additional information that allows data to be better understood, such as provenance and annotations?
- Appropriate data usage: How can we ensure that the data chosen is used responsibly? To support algorithmic accountability, can we provide mechanisms that allow end users to understand the algorithmic impact of their data choices (e.g. to support the machine learning algorithms in the criminal justice system). Can we ensure that users's consent on their personal data is honored?
External roles and responsibilities
- SIGMOD Test of Time Award (2016)
- Program Recognition Award (2013)