Foad Faraji

Foad Faraji is a Senior Lecturer in Engineering at the School of Computing, Engineering and Digital Technologies (SCEDT), Teesside University. He holds a PhD in Energy Engineering (2021) and a First-Class Honours MEng in Mechanical Engineering (2016), both from Teesside University. His research focuses on applying Artificial Intelligence, Machine Learning, Finite Element Analysis (FEA), and Computational Fluid Dynamics (CFD) to solve complex engineering problems. He is a Chartered Engineer (IMechE) and Fellow of the Higher Education Academy (FHEA).

Research Interests:

• Machine Learning in Engineering Applications
• CFD and FEA for Industrial Systems
• Sustainable Materials Development
• Fluid Mechanics and Multiphase Flow Modeling
• Energy Engineering and Reservoir Performance

Current Projects (2023–2026):

• AI-Driven Digital Twin for Pharmaceutical 3D Printing
• Distortion Rate Modeling in Aluminium Brazing
• Optimization of Porous Filters via Machine Learning
• Hydrogen Pipeline Leak Detection Tools

Awards and Activities:

• FHEA (2022)
• IMechE Mentor for Placement Students
• Reviewer for Nature Scientific Reports and Gas Science and Engineering

Teaching Responsibilities:

• Computer-Aided Engineering Analysis
• Finite Element Methods and CFD
• Applied Machine Learning for Engineers
• International Program Coordination (UAE/Singapore)