Mukiibi Moses
AI & Data Science Researcher • Computer Scientist
AI & Data Science Researcher • Computer Scientist
Mukiibi Moses is a computer engineering student and AI researcher specializing in artificial intelligence, machine learning, and data science. He focuses on building intelligent systems, emotion-aware AI models, and scalable data-driven applications for real-world problem solving.
Mukiibi Moses specializes in key areas of artificial intelligence including natural language processing, generative AI, and data-driven systems. His work focuses on building intelligent applications that understand human emotion, optimize machine learning models, and improve decision-making using data. Core areas include:
Mukiibi Moses is a computer engineering student at Kyungdong University specializing in artificial intelligence, machine learning, and data science. His research focuses on emotion-aware AI systems, natural language processing, and optimization of generative models. He has built AI applications including sentiment analysis systems, text-to-image generation pipelines, and data analytics solutions using AWS. His goal is to develop intelligent systems that solve real-world problems efficiently and at scale.
Mukiibi Moses is actively publishing and sharing research through platforms such as Google Scholar, ResearchGate, and Academia, contributing to the global artificial intelligence research community.
CGPA: 4.27 / 4.5
Relevant Coursework: Algorithms, Machine Learning, Computer Security, Data Structures, Cryptography, Cybersecurity & Probability & Statistics
Majors: Physics, Economics, Mathematics & Computer Studies
Developed a multi-modal AI assistant with real-time web search, document analysis (PDF, DOCX, TXT, CSV, JSON), file comparison capabilities, conversation memory, and work evaluation features. Built with Streamlit and Groq's LLM API, featuring a fixed-position chat interface for seamless user experience.
Streamlit • Groq LLM • Sentence Transformers • BeautifulSoup • PyPDF2 • Real-time Search • Current-newsA web-based airport simulation system that models real-world airport operations, including flight handling, runway management, and aircraft movement. The project demonstrates how aviation systems can be represented digitally with interactive UI components.
Html• CSS • JavascriptDeveloped a digital wallet web application supporting deposits, withdrawals, and peer-to-peer transfers with persistent storage and transaction history using JavaScript and LocalStorage.
Html• CSS • Javascript • Local StorageThis project is an artificial intelligence system designed to generate empathetic responses using natural language processing and sentiment analysis. It uses transformer-based models to understand user emotions and provide context-aware replies. The system improves human-computer interaction by making AI responses more emotionally intelligent.
Python • NLP • Transformer ModelsEngineered an analytics pipeline with AWS tools to process 50,000+ social media posts, extract insights, visualize trends, and generate dashboards for social trend interpretation.
AWS • Data Pipelines • VisualizationDeveloped a Gradio-powered interface for prompt-driven image generation using Stable Diffusion models and documented findings in a full research thesis, including model optimization techniques.
Stable Diffusion • Gradio • Research Documentation
He specializes in artificial intelligence, machine learning, and data science.
He has developed AI systems including emotional support applications, sentiment analysis pipelines, and generative AI models.
He uses Python, AWS, NLP models, Stable Diffusion, and data engineering tools.
His research is available on Google Scholar, ResearchGate, and Academia.
Explore foundational concepts in artificial intelligence, machine learning, and data science. These guides provide clear explanations of key topics and real-world applications.
ORCID
ResearchGate
GoogleScholar
I’m open to research collaborations, internships, and AI projects. Feel free to reach out.
Last updated: April 2026