Mohamad Ibrahim

I’m a motivated Aerospace Engineering graduate with strong analytical and problem-solving skills developed through complex modelling, optimisation, and project work. I’m used to turning technical inputs into evidence-based decisions, and I enjoy collaborating with others to deliver practical outcomes.

In my dissertation, I enhanced the manufacturing and optimisation of wind turbine blades using machine learning, improving production efficiency through Python. I performed data cleaning, feature engineering, and model evaluation with Scikit-learn and Pandas, and built ML models in Python (Naïve Bayes, Logistic Regression, KNN) to achieve 97% model accuracy.

I also contributed to an Airbus group design project focused on reducing aircraft weight by 15% through design optimisation and the adoption of lighter APU systems and engines, aiming to lower fuel consumption. I presented findings and recommendations to academic and industry stakeholders, with a consultative, solution-oriented mindset.

Alongside engineering projects, I completed an Operations Engineer Intern role where I prepared technical reports, drawings, and work packs, coordinated with vendors and contractors for timely materials, and reviewed HSE documentation to support compliance with safety standards. With certifications including Lean Six Sigma Yellow Belt, I’m eager to apply structured thinking and communication skills to drive impactful results.