Paokinator
December 2025 Project Completed

Paokinator

An AI-powered guessing game API server inspired by Akinator, where users think of an item and the system asks yes/no questions to identify it through machine learning. You can play the game at https://paokinator.olisemeka.dev/.

PragBase: AI-Powered Chatbot for your business
July 2025 Project Completed

PragBase: AI-Powered Chatbot for your business

PragBase is an embeddable widget that analyzes your knowledge base, and provides intelligent, structured answers. Built for businesses to create AI chatbots from their own knowledge bases.

Semantic Search Engine
July 2025 Project Completed

Semantic Search Engine

An intelligent search engine that helps users find relevant information using natural language queries, making content easily discoverable.

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June 2025 Project Completed

Sequential Fine-tuning Project: Medical AI Specialization

Developed a sophisticated sequential fine-tuning pipeline to create a specialized medical AI model focused on dialysis care. This project demonstrates advanced machine learning techniques, domain adaptation, and responsible AI development practices using Google's Gemma 2B model.

INFERNO: AI-Powered Fire & Smoke Detection and security System on edge device
May 2025 Project Completed

INFERNO: AI-Powered Fire & Smoke Detection and security System on edge device

INFERNO is a real-time fire, smoke, and motion detection system designed for edge devices. Trained on 160,000 labeled images and optimized for Raspberry Pi, it offers robust performance and rapid alerts without the need for expensive hardware or cloud subscriptions.

Meal Craft: Smart Meal Recommendation App
April 2025 Project Completed

Meal Craft: Smart Meal Recommendation App

Find, save, and organize recipes with Meal Craft. Get meal recommendations from tags and an AI-powered Chef Steve, plus manage your own recipe collections.

EEG Feature Engineering and Clustering: A Data Mining Approach for Neural Signal Analysis
December 2024 Project Completed

EEG Feature Engineering and Clustering: A Data Mining Approach for Neural Signal Analysis

End-to-end EEG data analysis pipeline: from preprocessing and statistical feature extraction to unsupervised clustering, metric-driven evaluation, and comprehensive visualization. Demonstrates robust data mining and ML engineering techniques using real neural signal datasets.

EEG Neural Network and ML Model Comparison
June 2024 Project Completed

EEG Neural Network and ML Model Comparison

A comprehensive analysis of EEG classification using artificial neural networks compared to classical machine learning models, showcasing advanced model engineering, automated preprocessing, and robust evaluation pipelines.