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Supervision areas include: Anomaly Detection, Condition Based Monitoring, Predictive Monitoring

Personal profile


I am a Reader with over 15 years’ experience in the fields of data analysis and machine learning as well as a strong track record in industry-academia collaboration.

I am an effective collaborator, having won, or been a part of externally funded projects with staff from all 5 of the University's faculties.

I have been PI/Co-I on more than 20 Innovate UK, STFC and DASA bids worth nearly £6.8 million in total (worth over £3.4 million for the University). These grants have been in collaboration with academic partners (Southampton, Nottingham, UCLAN and Brunel) and industrial partners within the maritime, railway, aerospace, high performance computing and manufacturing sectors.

I was entered into REF 2014 (UoA 19) as an Early Career Researcher and I also undertook a large part of the research that formed one of the impact case studies. This case study was featured on the Universities Alliance website. I was also entered into REF 2021 (UoA12) and submitted 2 out of the 4 impact case studies for this UoA.

Researcher development and support is a key interest. I sit on two working groups supporting the implementation of the Researcher Concordat within the University, as well as having previously served as Convenor of the Researchers' Network.

I received my PhD from Portsmouth in 2011 and the MMath degree from the University of Reading in 2005. I previously worked at Clearswift Ltd where I used machine learning techniques to automatically identify certain types of images in email attachments. 

Research Interests

My research interests focus on learning algorithms to detect rare or abnormal events from industrial data in situations where faulty data is sparse or non-existent. I am keen to apply such methods across several industry sectors as there are clear benefits to industry by improving maintenance methods through modern data analysis. Currently these methods are being applied in the manufacturing, computing and transport sectors of industry.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 2 - Zero Hunger
  • SDG 3 - Good Health and Well-being
  • SDG 7 - Affordable and Clean Energy
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 12 - Responsible Consumption and Production
  • SDG 14 - Life Below Water
  • SDG 16 - Peace, Justice and Strong Institutions


Dive into the research topics where Edward Smart is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years

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