Hasan Hachem

Personal Profile

A proactive Mechanical Engineering student with hands-on experience in data analysis, data visualisation, and predictive modelling. Skilled in Python, Excel, and Power BI with a strong foundation in statistical analysis and machine learning. Keen to apply my data-driven problem-solving skills in a collaborative and commercial environment.

Education

MEng Mechanical Engineering, UCL, University of London (2021 - 2025)

Relevant modules: Machine Learning for Robotics, Data Mining and Analysis, Data Driven Methods for Engineers, Introduction to Robotics, Mathematical Modelling and Analysis, Robotics in Medicine and Industry.

Central Foundation Boys' School (2014 - 2021)

A-Levels: Mathematics (A*) Physics (A*) Arabic (A*) Further Mathematics (A)

Data Projects

Data Mining Project – Predicting Hospital Readmission Rates for Diabetic Patients (2024)

Developed and optimized a machine learning model to predict hospital readmission rates, addressing class imbalance using ADASYN resampling and Recursive Feature Elimination (RFE) for feature selection.
Utilised libraries such as scikit-learn, XGBoost, LightGBM, and imbalanced-learn for model development, resampling techniques, and evaluation metrics.
Contributed to data preprocessing, handling missing values, standardizing numerical features with StandardScaler, and encoding categorical variables to ensure model compatibility.
Assisted in implementing multiple machine learning models (Random Forest and Gradient Boosting) and ensemble methods (VotingClassifier, StackingClassifier), comparing performance using cross-validation and F1-scores.
Applied Monte Carlo Cross-Validation (MCCV) for model validation and optimized hyperparameters using RandomizedSearchCV and GridSearchCV.
Utilised Pandas, NumPy, Matplotlib, and Seaborn for data manipulation, analysis, and visualization to support model development and results interpretation.

Backpropagation in MLP & Transfer Learning in CNNs (2024)

Developed and implemented MLP and CNNs for regression and classification tasks.
Designed and trained 1-3-1 neural network with SGD, SGDM, and ADAM.
Built 4-5-3-3 network for iris dataset classification with optimized hyperparameters.
Applied transfer learning using AlexNet and GoogleLeNet, achieving 95% and 90% accuracy.
Analysed performance via hyperparameter tuning and dataset size variations.

Data-Driven Motion Analysis of Spring Pendulum (2025)

Processed multi-camera video data to track object motion using OpenCV and Python.
Implemented image binarisation, contour detection, and centroid tracking to extract pendulum mass trajectory.
Applied Principal Component Analysis (PCA) to reduce 6D motion data to 2 key components, capturing 84% of system variance.
Validated the system's 2 degrees of freedom and discussed insights through scree plots and time series visualisation.
Used Python (OpenCV, NumPy, Pandas, Matplotlib) for data cleaning, modelling and visualisation.

Technical Skills

Programming & Analysis: Python (Pandas, NumPy, Scikit-Learn, XGBoost, LightGBM), MATLAB, SQL

Data Visualisation: Matplotlib, Power BI, Seaborn

Tools: Jupyter Notebook, Anaconda, Git, OpenCV, scikit-learn, AWS (beginner)

Languages: English (Native), Arabic (Native)

Other Experience

UCL Ahlul-Bayt Islamic Society VP/President/Advisor (2022 - 2025)

Collaborated and led teams to host events, workshops, and campaigns.
Delegated responsibilities and supported committee members.
Built networks with students and alumni across universities.
Efficiently balanced society work with academic commitments.