Portfolio & CV
CV Overview
As a driven, bilingual Computer Science student with a pan-African perspective, I bring a unique blend of technical skill, cultural awareness, and global ambition to everything I do. Born in Benin and currently based in Ghana, I’ve had the privilege of experiencing life and learning across several West African countries (Nigeria, Togo, Benin, Niger) — an experience that has shaped both my mindset and my mission. I will graduate from West End University College in January 2026, equipped not just with academic knowledge, but with a deep understanding of how technology can address real-world challenges in education, infrastructure, business, and beyond.
This CV reflects my ongoing growth — from technical capabilities and project leadership to problem-solving and cross-cultural communication. Whether you’re a recruiter, mentor, collaborator, or investor, I invite you to explore my background and consider how we might work together to create impact. I’m ready to learn, grow, and contribute in meaningful ways — and I’m open to exciting opportunities around the world.
technical proficiencies — all shaped by my journey as a bilingual learner navigating diverse environments across West Africa. Set to graduate in January 2026 from West End University College in Ghana, I’m eager to contribute to innovative teams, grow through collaboration, and solve meaningful challenges. If my profile resonates with your vision, I’d be excited to connect
Portfolio
Power line monitoring with ACO
I designed a UAV path planning model using Ant Colony Optimization (ACO) to improve the efficiency of power line corridor inspections. Traditional inspection methods are often unreliable, costly, and unsafe. By mimicking the pheromone-based behavior of ants, the ACO algorithm helps drones determine the shortest and most efficient routes. The system was developed and tested using Ghana’s high-voltage transmission network dataset, ensuring realistic terrain and constraints. The project aimed to enhance inspection coverage, reduce energy consumption, and offer a smarter alternative to manual methods. Tools used: Python, MATLAB (optional), custom ACO implementation.
AI-Powered Spam Email Classifier
I built an AI-powered spam detection system that uses Multinomial Naive Bayes and TF-IDF vectorization to automatically classify emails as spam or legitimate. The model analyzes the frequency and importance of words within email content to make accurate predictions, offering a lightweight yet effective solution for filtering unwanted messages. The dataset used for training and evaluation was downloaded from the UCI Machine Learning Repository – Spam Base Dataset, a widely recognized source for benchmark datasets. This project strengthened my skills in Natural Language Processing (NLP) and machine learning workflows. Tools used include Python, Pandas, and Scikit-learn.
Car Dealership Website
I developed a fully responsive car dealership website using HTML, CSS, and JavaScript to provide users with an interactive and visually appealing experience. The site allows visitors to browse available vehicles, filter listings by brand and price, and view detailed information for each car. A functional contact form was also included to facilitate customer inquiries. The project focused on clean design, usability, and smooth user interaction across desktop and mobile devices. Tools used include HTML, CSS, and vanilla JavaScript.
Nigeria Macroeconomic Case Study
I conducted an in-depth Excel-based analysis of Nigeria’s macroeconomic trends from 1991 to 2022, focusing on key indicators such as GDP growth, inflation, unemployment, labor productivity, and exchange rates. The study involved cleaning and preprocessing real-world data, performing descriptive statistics, and applying regression analysis and hypothesis testing to evaluate economic claims and forecast future trends. Using tools like the Excel Data Analysis ToolPak, I built both simple and multiple linear regression models to uncover relationships between variables, such as the impact of unemployment and inflation on GDP growth. This project demonstrated my ability to work with complex datasets, draw actionable insights from economic data, and apply statistical techniques to support evidence-based conclusions.