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Professor Eyad Elyan
|Biography||Eyad Elyan is a Professor in Machine Learning and Computer Vision at the School of Computing at RGU. He is leading the Machine Learning and Vision Applications research theme at the School and his primary research is in machine learning, deep learning, and applied computer vision. He joined the School of Computing as a lecturer in 2009 after obtaining his PhD from the University of Bradford for his work in 3D modelling and recognition of human faces. In 2015 he was appointed as a Senior Lecturer, then in 2018 he was promoted to a Reader, and in 2020 he was promoted to full professor of Machine Learning and Computer Vision.
His work in the area of ensemble-based learning and learning from unstructured and imbalanced datasets have been successfully applied to various real-world applications across different domains, such as processing and analysing engineering diagrams, remote inspection for oil and gas installations and platforms, biometric applications, medical datasets analysis, and others. Over the past decade, he has attracted funds to support his research from different public funding bodies including Innovate UK, the Data Lab Innovation Centre, Oil and Gas Innovation Centre (OGIC), Historic Environment Scotland, and Others. He is leading several multi-disciplinary projects with industrial partners. The latest examples of his work include the development of an end-to-end platform for processing and analysing Piping and Instrumentation Diagrams (P&ID) between the years 2017 to 2019 (Case Study - Data Lab). The project resulted in developing and applying cutting edge technologies to automatically analyse and process complex documents and P&ID diagrams and transform legacies of unstructured and complex diagrams into knowledge (Demo).
Elyan is a Fellow member of the British Higher Education Academy and serves as the Scotland Data Lab Innovation Centre Ambassador. He plays a lead organising role in various national and prestigious international events, reviewing for many leading international journals in the area of artificial intelligence, computer vision, and machine learning, and a reviewer for research councils such as EPSRC. He has given numerous talks in the area of Machine Learning, AI, and Big Data Analytics, supervised seven PhD students to successful completion and examined more than fourteen PhD students at different UK universities.
|Research Interests||Lead of the Interactive Machine Vision Research Group
Machine Learning and Machine Vision (image classification, class-imbalance problem and video content analysis).
|Teaching and Learning||Advanced Data Science Development, Data Science Development, Image Processing|
|Scopus Author ID||35226184300|