About

I am Amirali Shateri, a Ph.D. student in the field of Mechanical Engineering at the renowned University of Derby. My research interests lie in the fascinating domains of heat transfer, non-Newtonian fluids, natural convection, combustion processes, and the integration of artificial intelligence and machine learning (AI-ML) techniques.  Within my research, I am dedicated to developing innovative computational models and conducting numerical simulations that leverage AI-ML methodologies. By applying these advanced techniques, I aspire to gain a deeper understanding of the intricate mechanisms underlying heat transfer, fluid dynamics, and combustion processes. Moreover, I aim to explore the immense potential of AI-ML in optimizing and enhancing various engineering applications related to these fields.  Through my work, I strive to contribute to the scientific community by uncovering novel insights and advancing the knowledge frontier in the realm of Mechanical Engineering. The fusion of combustion processes, heat transfer, and AI-ML holds tremendous promise for driving advancements in energy efficiency, sustainability, and the overall optimization of engineering.

Title of thesis 

Enhancing Engine Efficiency and Reducing Emissions: Multi Scale Modelling of Diesel Fuel Droplet Heating and Evaporation in Combustion Engine 

Supervisors 

• Dr. Jianfei Xie 
• Prof. Zhiyin Yang 

Expected finish date 

7th September 2026 

Teaching responsibilities

Teaching Assistant for the courses of CFD (Computational Fluid Dynamics) and Dynamics and Vibrations.

Qualifications

I hold a Bachelor's degree in Mechanical Engineering with a specialisation in Fluid Mechanics. Building upon my Bachelor's degree, I pursued a Master's degree in Mechanical Engineering with a focus on Energy Conversion. Now, as a Ph.D. student in Mechanical Engineering AI-ML CFD.