Dr. Foad Faraji is a Senior Lecturer in Engineering within the School of Computing, Engineering and Digital Technologies (SCEDT) at Teesside University. He is a Chartered Engineer (CEng), a member of the Institution of Mechanical Engineers (IMechE), and a Fellow of the Higher Education Academy (FHEA).

Foad holds a PhD in Energy Engineering from Teesside University, where he also earned a First-Class Honours MEng in Mechanical Engineering in 2016. Prior to his academic career, he contributed to industrial innovation as part of the quality control team at British Steel Special Profiles in Skinningrove, where he supported the descaling project.

His research spans the fields of mathematical modelling, artificial intelligence and machine learning in engineering, as well as the industrial application of the Finite Element Method (FEM) and Computational Fluid Dynamics (CFD). Foad has published extensively in peer-reviewed journals, contributing to the advancement of intelligent systems and computational techniques in engineering practice

Foad's primary research focuses on leveraging Artificial Intelligence (AI) and Machine Learning (ML) techniques to address complex engineering challenges across various domains.

His areas of expertise and research interests include:

• Engineering applications of Machine Learning and Artificial Intelligence

• Finite Element Methods (FEM)

• Fluid Mechanics and Computational Fluid Dynamics (CFD)

• Statistical Modelling

• Sustainable Materials and Technologies

Foad is currently leading two externally funded projects in collaboration with industry partners, PSI Global and Sylatech. These projects focus on the development of advanced digital models integrating Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and Machine Learning (ML).

In addition, he is actively contributing to other industry-focused initiatives, including a project with Fabrx that explores the application of 3D printing technologies in medical fields.

• Computer Aided Analysis 
• Finite Element Methods (FEM)
• Computational Fluid Dynamics (CFD)
• Applied Machine Learning in Engineering
• CAD/CAM and Product Developments
• Group Design and Build Projects

Fellow of the Higher Education Academy (FHEA)

• Teaching and project supervision in Engineering department 
• Research and enterprise activities 
• Personal tutoring 
• Link Tutor for the school's international partners in UAE and Singapour

• Charted Engineer and Member of IMechE 
• Institution of Mechanical Engineers (IMechE) Mentor 
• IMechE mentor to supervise MPDS placement students
• Reviewer of Scientific Journals (Scientific Reports- Nature, Gas Science and Engineering)
• Associate member of SPE