Hello! I'm Emre.
I'm a 2nd year Computer Science undergraduate, currently at the University of Exeter. I have a unique educational background which combines a foundation of low-level programming in C++, with a flexible software engineering skillset in Python and Java.
Beyond software, I enjoy playing tennis, piano, and being terrible at chess.
Education
University of Exeter | BSc Computer Science
Expected Graduation: 06/2027
- 1st year grade: 1:1 (First Class Honours)
- Relevant courseworks: multi-threaded game simulation in Java, web development in Python and the Flask framework, optimised lift routing algorithm in Python, functional programming in Haskell.
- Multiple projects completed in pair programming, well-versed in SDLC.
Imperial College London | BEng Electrical Engineering
Degree incomplete
- Programming in C++: Wrote custom versions of standard template library data structures such as vector.
- Computer Architecture: Design and simulation of a 16-bit computer, with full arithmetic and control flow operations.
- Group design project - remote controlled rover, with data transmission over LAN.
Lycée Francais Charles de Gaulle | French baccalaureate
2015 - 2022
- Specialty subjects: Mathematics, Physics, Chemistry
- Graduated with distinction (félicitations du jury) 18.21/20
- A-level equivalent: A* A* A*
Technical Skills
- Programming Languages: C++, Python, Java.
- Version control: Git and GitHub.
- Unit testing: JUnit framework.
- Containerization: Docker and Docker compose.
- Machine Learning & Data Science: See dedicated section below for skills in this area
Machine learning & data science skills
- Regression models: implemented linear and polynomial regression with feature selection and visualization
- Classification: built perceptron and logistic regression classifiers for MNIST and CIFAR10 datasets
- Clustering algorithms: applied k-means and DBSCAN with Silhouette and DB scoring metrics
- Dimensionality reduction: compared PCA, t-SNE, and UMAP for visualization and ML preprocessing
- Performance analysis: evaluated models using precision/recall metrics beyond simple accuracy
- Data preparation: performed feature engineering, normalization, and exploratory analysis