Dr. Paolo Missier, PhD (Computer Science)

School of Computing, Newcastle University
Urban Sciences Building, Firebrick Avenue
Newcastle upon Tyne, NE4 5TG, United Kingdom

paolo dot missier at newcastle dot ac dot uk
Official staff page @Newcastle
my Google Scholar profile
Scopus WOS page

Publications
[my self maintained list[Official University page]
[Google Scholar[DBLP] [ResearchGate]

http://twitter.com/pMissier http://uk.linkedin.com/pub/paolo-missier/0/254/b4a
https://www.turing.ac.uk/people/researchers/paolo-missier
 

Current and funded recent Projects

  • 2018-2020: PI, P4@NU: Addressing Data Science challenges associated with the development of new data-driven models to enable a vision of Preventive, Predictive, Personalised, and Participatory (P4) medicine.  See funding from the Alan Turing Institute in the UK. Read more
  • 2016-2019PIReComp: sustained value extraction from analytics by recurring, selective re-computation. (EPSRC funding, £585,000, 2016-2019).
  • 2017-2019: CO-I: Discovering activists online to help fight viral epidemics (Dengue, Zika) in Brasil, Newton Fund UK (£99K).
  • 2017-2021: CO-I, Flood-PREPARED: Predicting Rainfall Events by Physical Analytics of REaltime Data (NERC funding, £1.9M, 48 months)
  • 2017-2019: PI for Newcastle, CEM-DIT: Communication and Trust in Emergencies, with Heriot-Watt and Coventry Universities (Office of Naval Research Global, (£110,000, 3 years) 
  • 2017-present: Enabling a fair IoT data marketplace without central trust. PhD student: Shaimaa Bajoudah
    • follows 2016-2017Researcher in Residence programme, Digital Economy Catapult (EPSRC funding, £25,000, Nov. 2016-June 2017). 
  • 2013-2015: PI, The Cloud e-genome project. Funded by NIHR Biomedical Research Centre (£180,000/ 2 years), in collaboration with the Institute of Genetics Medicine at Newcastle University.
  • 2012-2013: PI, Trusted Dynamic Coalitions, joint EPSRC/DSTL funding (£100,000). Investigating abstraction in provenance. and provenance-based policies for information exchanges amongst partners with limited trust.

Selected publications

Please see "publications" tab for the whole list

My Twitter Timeline

Bio and research profile

New: my profile at the Alan Turing Institute for Data Science and Artificial Intelligence

I am a Reader (Associate Professor) in Large-Scale Information Management with the School of Computing at Newcastle University and a Fellow of the Alan Turing Institute, UK's National Institute for Data Science and Artificial Intelligence. I joined academia in 2011 after a career in industrial R&D (Bellcore, US) between 1994 and 2001, a spell as strategic consultant for the Italian Government on Data Quality, and a PhD in Computer Science from University of Manchester, UK (2007).
I serve as Sr. Associate Editor for the ACM Journal on Data and Information Quality (JDIQ). 

As of 2019, my research group at Newcastle consists of 4 postdocs (2 full time funded by the Turing Institute, 2 part-time) and 6 PhD students. 

My current research is focused on Data Science for Health. We study techniques to predict and prevent age-related diseases through Machine Learning, with a specific focus on extracting digital biomarkers from a variety of self-monitoring devices (wearables) that are predictive of personalised disease trajectories. Read more

My recent past research has focused on metadata analytics, namely understanding the role of metadata, most notably data provenance [7], in Big Data Analytics, to improve and optimise the expensive processes that produce and extract insights from the data. In this context I have been leading the ReComp project (2016-2019, EPSRC) focused on preserving value from large-scale data analytics over time through selective re-computation (http://recomp.org.uk ) [invited talk].

I am also interested in the role of provenance in making experimental science more reproducible, and in finding ways to incentivise experimental scientists to share their data assets in an Open Science setting.

I have also been involved in the specification of the W3C PROV data model for provenance (2011-2013) where I contributed to the main recommendation documents.

See the tabs above for my editorial roles and reviewing community service, invited talks and research visits, publications etc.

Additional research

My other research interests are centred around (large-scale) information management:
  • Social media analytics (Twitter) to help health authorities combat Zika and Dengue epidemics [5], 
  • Enabling trust-less and fair marketplaces for “personal” IoT data streams using blockchain technology [2], 
  • Real-time multi-source data analytics to predict rainfall events and mitigate their impact (funded project: Flood-PREPARED, 2017-2021, Co-I, NERC)
  • Implementing efficient and cost-effective genomics data processing pipelines using workflow technology on the Cloud (funded project:  Cloud-eGenome:, 2013-2015, PI, MRC/ NIHR) [6]
  • Online active learning for Human Activity Recognition [9]
  • Analysing the effect of cognitive load on car drivers [10]
  • Data and Information QualityDuring my PhD I proposed the notion of Quality Views [16,17], a semantics-based method for semi-automatically adding data quality control to scientific workflows. I am currently Sr. Associate Editor for the ACM Journal on Data and Information Quality (JDIQ) 

Teaching

I am responsible for the our School’s post-graduate academic teaching on Big Data Analytics.
Students interested in projects (UG/PGT/PGR) should look here.