Hi, I'm Chidubem
AI Engineer & Full-Stack Developer passionate about building intelligent systems that solve real-world problems using cutting-edge machine learning, deep learning, and cloud technologies.
About Me
AI Engineer with a passion for building intelligent systems that solve real-world problems
Education & Academic Leadership
First-class graduate from Covenant University with a degree in Computer Science. Currently pursuing graduate studies in AI with a focus on machine learning optimization and computer vision. Served as Technical Lead of the Data Science Club, where I mentored over 50 students and organized workshops on machine learning, data analytics, and cloud computing. Completed advanced AWS training in SageMaker, EKS, ECS, and cloud infrastructure management.
Learn MoreMy Approach
I believe in leveraging cutting-edge AI and machine learning to create meaningful impact. Every solution I build is driven by the goal to solve real-world problems, improve efficiency, and deliver measurable value. I combine technical excellence with practical business outcomes.
Current Focus
Researching Large Language Model optimization techniques and developing advanced computer vision applications. Actively exploring MLOps practices, model deployment at scale, and the intersection of AI with real-world business applications.
Tech Stack
Technologies I work with
Work Experience
My professional journey
Software Engineering Intern
Developed and deployed a Visitor Management System that generated secure access codes for guests, reducing entry processing time by 40% and eliminating delays caused by manual approval calls. Designed and implemented a Requisition and Expenses Tracking Dashboard, providing real-time visualization of company spending and contributing to a 3% reduction in operational costs within 6 months. Maintained and enhanced the company's WordPress website, improving site loading speed by 25%, reducing downtime incidents by 15%, and enhancing overall user engagement.
Data Science Intern
Optimized Large Language Models through fine-tuning techniques, achieving 30% performance improvement. Developed and deployed a predictive child malnutrition model with 85% accuracy using PyTorch and Streamlit. Leveraged AWS SageMaker for scalable machine learning model training and deployment.
Generative AI & Data Science Intern
Utilized CNNs for complex computer vision tasks. Implemented NLP and LSTM networks for sentiment analysis and text summarization. Mastered model fine-tuning using Hugging Face Transformers. Deployed models using AWS ECS for containerized application orchestration.
Featured Projects
Showcasing my best work
Smart Waste Management System
AI-powered waste classification system using CNN for object recognition and GPT API for generating specific recycling instructions.
Interactive Quiz Platform
Dynamic quiz platform enabling lecturers to create tests and students to take them with real-time feedback and grading.
Achievements
Notable accomplishments and recognitions
PulseGuard @ HackATL 2025
Developed the first Predictive Risk Interception System using adapted NASA VOC sensor technology to protect against drink tampering. Built real-time safety dashboard with heart rate monitoring, chemical detection simulation, and automated emergency alert system. Delivered end-to-end prototype in 36 hours with $1.37B addressable market and $775K projected first-year revenue.
Certifications
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Machine Learning
Issued by Udemy Academy
Completed comprehensive ML course covering supervised and unsupervised learning
Full Stack Web Development
Issued by Udemy Academy
Frontend and backend development with modern frameworks
Fundamentals of AI
Issued by MinnaLearn
Core AI concepts and practical applications
Networking Essentials
Issued by Cisco Network Academy
Network fundamentals and configuration
Cybersecurity Essentials
Issued by Cisco Network Academy
Security principles and best practices
Robotic Process Automation
Issued by Blue Prism
RPA development and implementation