Paolo is Professor of Scalable Data Analytics with the School of Computing at Newcastle University and currently a Fellow (2018-2020) of the Alan Turing Institute, UK’s National Institute for Data Science and Artificial Intelligence.

With a background in traditional databases and data management, his research has touched on Data and Information Quality, web semantics, workflow-based infrastructure for e-science, and data provenance.

Paolo’s work has been funded over the years by EPSRC, NIHR-BRC, Newton Fund UK, Microsoft Azire for Research, and the Turing Institute. Funded projects include Cloud-e-Genome on scalable processing of genomics pipeline on the cloud (NIHR-BRC), ReComp on optimising analytics pipelines in response to changes in data (EPSRC), P4@NU (towards Personalised, Participatory, Preventive, Precision Medicine), and more.

His more recent research portfolio addresses the challenges and opportunities of Applied Data Science and Machine Learning for Health, with contributions on the search for “digital markers” from self-monitoring devices, and recent work on predicting respiratory crises  in acute covid patients.

Paolo’s interests are also expanding to the management and exploitation of data provenance in data science pipelines, and to the study of algorithmic fairness.