the tech perspective

About Me

My name is Stephanie Lawal and I am a graduate Computer Scientist! My main areas of interest are Software Development and Machine Learning. With an inclination towards creativity, I enjoy problem-solving and learning.

Recently, I have become certified AWS Solutions Architect (SAA-C03)! This certification has consolidated my systems designs knowledge and how companies are scaling and maintaining their applications in the cloud and on-premises. It feels good to be knowledgable in the cloud tools that are becoming a large foundation of the internet today.

I am interested in the ways that creative industries, particularly fashion, are influenced by technology and vice versa. Hence why I started this blog, ‘the tech perspective’, to do some interesting analysis within that intersection by relating concepts and topics in computer science to the fashion industry!

Outside of tech, I enjoy reading books, writing, film, music and playing instruments and of course, art and fashion.

Education

King’s College London ● 2021-2024

BSc Computer Science

Upper Second Class (Honours)

Key Modules

Software Engineering (Python, Django, HTML)
Database Systems
Practical Experiences in Programming (C++, Scala)
Machine Learning & Pattern Recognition – Master’s Module (Python, Tensorflow)
Software Measurement & Testing
Human Computer Interaction
Operating Systems
Robotics (ROS)

Projects

NoteTogether

An easy-to-use, note-taking app with auto-saving capabilities (collaborative note-taking coming soon). Read more on GitHub!

Merlin’s Apprentice – Terminal Game

A Java game played in the terminal. Loosely inspired by an obsession with the BBC TV Series, Merlin (2008).

Java

See Github

Minted – Money Management Site

A fun group project in which we were tasked with creating a personal spending tracker. I was responsible for front and backend development of features such as the login and sign-in features with Google integration and Rewards system.

Machine Learning Virtual Stylist

Demonstrates the potential for Machine Learning to be used for styling outfits, based on aesthetics collated from various collections and designers from across the decades. Uses a Machine Learning algorithm created from scratch to explore a ‘feature space’ of attributes, such as prominent colours and silhouettes, to output an outfit comprised of suitable clothing items. Recommendations are produced in response to user feedback.