I am a 5th-year Electronic and Computer Engineering student at Jomo Kenyatta University of Agriculture and Technology, passionate about data science, machine learning, and intelligent hardware systems. I specialize in building AI-powered applications, machine learning classifiers, and embedded IoT solutions using tools like Python, Scikit-learn, ESP32 microcontrollers, and modern web frameworks like Gradio and Streamlit. I enjoy bridging the gap between hardware and software, turning data-driven ideas into functional end-to-end applications, and continuously working on practical projects to sharpen my engineering skills. Outside of academics, I enjoy playing football and Hiking.
I'm currently building a Solar Microgrid with Intelligent Load Management, where I'm focused on optimizing power distribution and automated load prioritization for off-grid renewable energy systems. It's built using an ESP32 microcontroller, C++, and Python, and involves real-time sensor data monitoring, decision-making algorithms, and IoT dashboard integration.
Languages
Tools & Platforms
A full-stack web application designed to digitize and streamline health insurance operations for Kenya's Social Health Authority (SHA). It facilitates a secure transition from manual record-keeping to a digital environment by automating healthcare workflows and beneficiary data management.
Tech stack: Python, Flask, MySQL, HTML/CSS, JavaScript
A web-based security application that detects and classifies online phishing attempts to protect users from malicious link tactics. It utilizes trained text-classification machine learning models paired with a real-time web interface.
Tech stack: Python, Scikit-learn, Gradio, Pandas
A custom recommendation tool designed to analyze listener preferences and generate personalized song suggestions based on feature similarity. It processes normalized audio feature matrices and uses cosine similarity along with radar chart visual analytics.
Tech stack: Python, Scikit-learn, NumPy, Plotly Express, Streamlit
Smart Solar Microgrid Controller
An embedded IoT microgrid management system designed to optimize load distribution and prevent total power blackouts in standalone solar setups. It integrates real-time sensor feedback with intelligent load-prioritization logic on microcontrollers.
Tech stack: C++, Python, ESP32, Arduino IDE, MQTT
- School Work (JKUAT): Advanced Control Systems, Microprocessor Systems, Embedded Hardware Design, and Digital Signal Processing
- Python Ecosystem: Object-Oriented Programming (OOP), Data Structures & Algorithms, Clean Code Architecture, and Performance Optimization
- Data & AI in Python: Data Analysis (Pandas, NumPy), Machine Learning Pipelines (Scikit-learn), and Data Visualization (Plotly, Seaborn)
I'm open to internships and entry-level AI Engineering opportunities — feel free to reach out!