معرفی
Dr. Mohamed Amish serves as Professor and MSc Oil and Gas Engineering Programme Leader at Robert Gordon University's School of Computing, Engineering & Technology. With 22 years of academic experience complemented by 18 years of industry practice, he bridges petroleum engineering with educational innovation through strategic partnerships with Shell, Sonatrach, PDVSA and BP worth £14m. His leadership extends to establishing the school's digital world principles and postgraduate research frameworks.
Dr. Amish's research spans drilling optimization, formation damage, artificial lift systems, and sustainable energy transition, increasingly incorporating machine learning applications. His recent work addresses critical industry challenges including sustained casing pressure prediction, fluid loss management, and water optimization in upstream operations. The Sustainable Energy Research Group serves as his primary research affiliation, focusing on energy transition technologies and environmental impact reduction.
His publication trend shows increasing integration of artificial intelligence in petroleum engineering, with 14 of his 20 publications since 2022 exploring machine learning applications. Key research areas include SCP management, artificial lift optimization, and work-based learning models. His scientific contributions focus on practical industry solutions rather than theoretical exploration.
- Chaired steering groups managing 40+ internal/external contributors
- Developed £14m strategic partnership programs with major energy companies
- Pioneered virtual engineering labs using ADDIE instructional model
- Implemented Merrill's First Principles for work-based learning frameworks
- Secured significant cost savings through staff development initiatives
Dr. Amish actively supervises PhD candidates, with Mahdi M.A.A.'s 2023 thesis on artificial lift selection representing current student work. His Sustainable Energy Research Group focuses on practical applications of digital technologies in energy transition, maintaining strong industry connections that provide students with real-world projects and employment pathways. The group's work particularly addresses upstream operational challenges through machine learning solutions while developing next-generation engineering competencies.
