Find Academic Supervisors

• Machine Learning
• Computer Vision
• Deep Learning
• +7 more

Professor Eyad Elyan is a leading academic and researcher at Robert Gordon University's School of Computing, Engineering and Technology, where he serves as a Professor in Machine Learning and Computer Vision. He is the founder and head of the Machine Vision Research Group, driving innovative research in applied computer vision and deep learning with significant industry impact. Professor Elyan's research focuses on converting complex and unstructured data into knowledge and actionable insights, with particular emphasis on learning from images, videos, and other forms of unstructured data. His work spans engineering diagrams processing, remote inspection for oil and gas installations, intelligent condition monitoring of offshore assets, predictive maintenance, biometric applications, and medical datasets analysis. His expertise in ensemble-based learning and learning from unstructured and imbalanced datasets has been successfully implemented in various real-world applications. Professor Elyan was awarded the UK Knowledge Transfer Partnership Academic of the Year Award in 2023 for his transformative work in developing pioneering AI solutions for the oil and gas sector, and was a finalist for the Scottish Knowledge Exchange Award in 2024. These recognitions highlight his exceptional ability to bridge academic research with practical industry applications. His research has been supported by various public funding bodies including Innovate UK, the Data Lab Innovation Centre, Oil and Gas Innovation Centre (OGIC), NetZero Technology Centre (NTZ), and Historic Environment Scotland. Professor Elyan has supervised twelve PhD students to completion and examined more than fifteen others. He plays an active role in the academic community as a Fellow of the British Higher Education Academy and The International Neural Network Society, and serves as the Scotland Data Lab Innovation Centre Ambassador. Under Professor Elyan's leadership, the Machine Vision Research Group has developed innovative solutions including an end-to-end system for processing Piping and Instrumentation Diagrams (P&ID), AI-driven inspection systems for oil and gas assets, and defect recognition technologies. His work demonstrates a consistent commitment to translating cutting-edge research into practical tools that address real-world challenges, particularly in the energy sector.

Wolfgang KratschView profile

Research Professor

• Process Mining
• Artificial Intelligence in Business Processes
• Data-Driven Process Management
• +3 more

Prof. Dr. Wolfgang Kratsch serves as Research Professor for Applied AI at Augsburg University of Applied Sciences, Director of the FIM Research Institute for Information Management, and holds a leading position in Fraunhofer FIT's Business Information Systems division. He co-founded and manages the Center for Process Intelligence, driving industry-academia collaboration in digital transformation. His educational background includes B.Sc. and M.Sc. in Business Informatics from the University of Augsburg (2017), followed by a summa cum laude doctorate in data-driven management of process networks from the University of Bayreuth (2020). University of Augsburg: B.Sc./M.Sc. Business Informatics (2017) University of Bayreuth: PhD in Data-Driven Process Network Management (2020) Dr. Kratsch's research centers on data-driven process management , focusing on data extraction, quality assurance, and AI-driven context-sensitive process optimization. His methodology emphasizes design science research yielding prototype implementations for immediate practical use. Key domains include process mining, robotic process automation, and generative AI integration in business workflows, with strong industry applicability. Core Methodology: Design Science Research Technical Focus: Event Log Generation, Object-Centric Process Mining Application Areas: Manufacturing, Healthcare, Transportation His publication trajectory (2021–2025) reveals accelerating integration of generative AI with process mining , particularly in unstructured data extraction (text/video) and automated process improvement. Recent works emphasize practical industry solutions in manufacturing error analysis, airport operations, and medical monitoring, demonstrating consistent collaboration with industrial partners like Munich Airport. No scientific awards were explicitly mentioned in the source material. Dr. Kratsch actively contributes to academia through teaching at Augsburg and Bayreuth Universities, industry project leadership, and startup mentorship. His spin-off credium GmbH (founded 2020) built a 15-person AI/data science team, reflecting his entrepreneurial approach to translating research into market solutions. Current projects prioritize practical AI deployment in serial production and process intelligence systems. Teaching: Lectures/seminars at Augsburg & Bayreuth Universities Startup Experience: credium GmbH (Data Science/AI focus) Industry Projects: Manufacturing optimization, airport operations He leads the FIM Research Institute and Center for Process Intelligence, directing multidisciplinary teams in developing process mining prototypes. His labs focus on bridging academic research with industrial deployment, particularly in video-based process monitoring and generative AI for business process design.