I am an Electrical & Electronics Engineering student focused on integrating Artificial Intelligence with real-world hardware systems.
My work combines software intelligence with electrical systems — building predictive, adaptive, and data-driven engineering solutions.
- Machine Learning for engineering systems
- Deep Learning (Intermediate Level)
- Embedded AI & TinyML
- Signal Processing & Control Systems
- Intelligent energy and predictive modeling
I approach AI as a system-level tool — something that enhances sensors, circuits, controllers, and power systems rather than existing in isolation.
- Studying Machine Learning and Deep Learning
- Building neural network architectures using TensorFlow
- Working with CNNs and optimization strategies
- Experimenting with TinyML deployment on ESP32
- Designing predictive models for energy and control systems
Completed:
- CS50’s Introduction to Programming with Python
- CS50’s Introduction to Artificial Intelligence with Python
Certificates:
- https://cs50.harvard.edu/certificates/6e9f7b4a-73ff-4893-9591-f32554c938d1
- https://cs50.harvard.edu/certificates/61c34e61-1a6c-41b9-80e5-d931ac878d42
Currently Studying:
- Machine Learning (Andrew Ng – Coursera)
- Advanced Deep Learning Architectures
- Electrical & Electronics Engineering (University Program)
Repo: Smart-Personal-Assistant
A modular Python CLI assistant designed for productivity and engineering workflows.
Focused on architecture, scalability, and future NLP integration.
Repo: Maze-Solver-AI
Implementation and visualization of BFS, DFS, and A* search algorithms with performance comparison.
Repo: https://github.com/me50/wayne540
Includes:
- Degrees of Separation (Graph BFS)
- Nim AI (Minimax)
- PageRank (Iterative Probability)
- Traffic Sign Classifier (CNN using TensorFlow)
Repo: EEE204-Circuit-Theory-II
MATLAB and Python simulations for RLC systems, AC bridges, and power modeling.
- AI for Smart Grids
- Embedded Neural Networks
- Predictive Maintenance Systems
- Reinforcement Learning for Control
- Energy Consumption Forecasting
Email: omanyowayne@gmail.com
LinkedIn: Omanyo Wayne
GitHub: https://github.com/wayne540