MSc Advanced Aerospace Engineering graduate (Distinction; top student and best project) from the University of Liverpool.
I like applying AI and numerical methods to real engineering problems: time-series forecasting, orbital mechanics, modelling, control and simulation.
- Machine learning / AI: PyTorch, scikit-learn, XGBoost, Optuna
- Time-series pipelines: custom Datasets/DataLoaders, reproducible splits, baselines, residuals, regression tracking
- Modelling and control: MATLAB/Simulink, PX4/Pixhawk, Kalman filtering
- Aerospace & numerical methods: orbital propagation, ODE integration, 3D visualisation
- Engineering tools: SolidWorks, Teamcenter, FORAN, AutoCAD
- Workflow: Linux, Git, GPU/CPU management, LaTeX reporting
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solar-activity-forecasting
Time-series forecasting of solar activity using LSTM, Transformer, autoencoder and XGBoost models. Includes reproducible pipelines with fixed splits, baseline comparisons, seed control, experiment logging and error analysis. Based on my MSc dissertation (94%, Best Project). -
numerical-orbit-propagation
A clean, self-contained Python notebook demonstrating orbital mechanics:
converting orbital elements → Cartesian state, integrating the equations of motion using SciPysolve_ivp, and visualising trajectories in 2D, 3D, and interactive Plotly animation. Showcases practical aerospace simulation, ODE methods and scientific-Python workflow.
- MSc Advanced Aerospace Engineering, University of Liverpool – Distinction, Top Student, Best Project (2023–2024)
- BEng Mechanical Engineering, University of Lincoln – 2:1 (2019–2022)
- Email: alfie.mowle@outlook.com
- LinkedIn: linkedin.com/in/alfiemowle