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Professor Eyad Elyan
|Biography||Eyad Elyan is an active researcher in the field of Machine Learning and Computer Vision, serving as a Professor at the School of Computing in RGU. He is the founder and head of the Interactive Machine Vision research group. His research focuses primarily on applied computer vision, deep learning, and machine learning. Prof Elyan also collaborates with various industries by providing training and consultancy to help them utilise the potential of machine learning to enhance their decision-making process and offer quicker, more secure, and precise services.
After earning his PhD for his research on 3D modeling and recognition of human faces at the University of Bradford, he became a lecturer at RGU School of Computing in 2009. In 2015, he was promoted to Senior Lecturer and subsequently to Reader in 2018. In 2020, he was promoted to the position of full Professor in Machine Learning and Computer Vision.
His expertise in ensemble-based learning and learning from unstructured and imbalanced datasets has been successfully implemented in various real-world applications across different domains. These applications include processing and analyzing engineering diagrams, remote inspection for oil and gas installations and platforms, intelligent and real-time condition monitoring of offshore assets, biometric applications, medical datasets analysis, and more. His research has been supported by various public funding bodies such as Innovate UK, the Data Lab Innovation Centre, Oil and Gas Innovation Centre (OGIC), NetZero Technology Centre (NTZ), Historic Environment Scotland, and others, which he has utilised to lead several multi-disciplinary projects with industrial partners.
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).
Professor Elyan's research is centered on utilising cutting-edge machine learning and deep learning techniques to convert complex and unstructured data into knowledge and actionable insights. His focus is primarily on learning from images, videos, and other forms of unstructured data. One notable example of his work is his pioneering contribution to the development of an end-to-end solution for processing and analysing Piping and Instrumentation Diagrams (P&ID) between 2017 and 2019. By leveraging advanced technologies for the automatic analysis and processing of complex documents and P&ID diagrams, the project successfully transformed intricate and unstructured diagrams into actionable insights. A demo of this work can be found here https://youtu.be/8e1n7mIvACw
|Teaching and Learning||Advanced Data Science Development, Data Science Development, Image Processing|
|Scopus Author ID||35226184300|