AI & Graduate Researcher - SEOUL, KR

Kwangwoon University
BCML lab

Graduate researcher at Kwangwoon University working on spike neural networks, emotion-aware AI, natural language processing, and the optimization of generative models — building systems that turn noisy human signal into something a machine can act on.

Keywords — NLP · Generative AI · Spike Neural Networks · Model Optimization · Data Engineering · Emotion-Aware Systems
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Mukiibi Moses
FIG. 01 — PROFILEKWANGWOON U.
Masters and PhD student
Computer Engineer
Researcher
01About

Mukiibi Moses is a graduate researcher at Kwangwoon University specializing in artificial intelligence, machine learning, and data science, with research focused on emotion-aware AI systems, natural language processing, and the optimization of generative models.

He holds a bachelor's degree in computer engineering from Kyungdong University, and is currently pursuing a combined master's and PhD in computer engineering at Kwangwoon University, Seoul, South Korea.

His applied work spans sentiment analysis systems, text-to-image generation pipelines, and data analytics solutions built on AWS — aimed at intelligent systems that solve real problems at scale. He publishes and shares research through Google Scholar, ResearchGate, and Academia.

CORE EXPERTISE
Natural Language ProcessingNLP
Generative AIGENAI
Stable DiffusionSD
ML Model OptimizationOPT
Data EngineeringDE
Emotion-Aware AIEAI
Conversational SystemsDIALOG
AWS PipelinesAWS
Deep LearningDL
02Education
2024 — PRESENT
Integrated Master's & PhD, Computer Engineering — Kwangwoon University
Algorithms · Spike neural networks · Natural language processing · Emotion-aware AI systems · Deep learning & transformers · Generative AI & Stable Diffusion optimization · Data engineering & cloud pipelines.
2020 — 2024
BSc Computer Engineering — Kyungdong University Global Campus
Algorithms · Machine learning · Computer security · Data structures · Cryptography · Cybersecurity · Probability & statistics.
CGPA 4.30 / 4.50
2018 — 2020
Uganda Advanced Certificate of Education — Mengo Senior School
Majors: physics, economics, mathematics, computer studies.
03Technical toolkit
PROGRAMMINGPython, C / C++, Java, R, MATLAB
AI & MLDeep learning (CNNs, RNNs, transformers), NLP — sentiment, embeddings, intent, geometric deep learning, probabilistic models, model optimization & evaluation
DATA SCIENCEPandas, NumPy, scikit-learn, data wrangling & feature engineering, SQL & database design, Tableau, Excel analytics, AWS data pipelines
TOOLSGit & GitHub, Jupyter Notebook, VS Code, Linux / Bash, Gradio, Stable Diffusion
SECURITYCryptographic algorithms, penetration testing basics, network security, cybersecurity principles
04Featured projects
01
MozeAI — Intelligent Autonomous Agent
Multi-modal AI assistant with real-time web search, document analysis, conversation memory, and work evaluation, built with Streamlit and Groq's LLM API.
StreamlitGroq LLMSentence Transformers
View demo
02
Fly Moses — Airport Simulation
Web-based airport simulation modeling flight handling, runway management, and aircraft movement with an interactive UI.
HTMLCSSJavaScript
View demo
03
Digital Wallet Pro
Digital wallet web app supporting deposits, withdrawals, and peer-to-peer transfers, with persistent storage and full transaction history.
HTMLCSSJavaScriptLocalStorage
View demo
04
AI-Based Emotional Support App
Generates empathetic responses using NLP and sentiment analysis; transformer-based models read user emotion and produce context-aware replies.
PythonNLPTransformers
Research write-up
05
Social Media Sentiment Analysis
AWS-based analytics pipeline processing 50,000+ social media posts — extracting insight, visualizing trends, and generating dashboards.
AWSData PipelinesVisualization
Private repo
06
Text-to-Image Generation Pipeline
Gradio interface for prompt-driven image generation using Stable Diffusion, documented in a full research thesis including model optimization techniques.
Stable DiffusionGradioResearch
Research write-up
05Leadership & community
2022 — 2024
President, Programming Club — Kyungdong University
Organized AI workshops, led student teams, and designed coding curricula.
ONGOING
Tech & Innovation Team Lead
Directs technical projects and leads mentoring sessions across technical and non-technical teams.
ONGOING
Community Tech Volunteer
Teaches AI and Python fundamentals to non-technical learners through community outreach programs.
06Certifications
01Cisco Data Analytics Essentials2026
02Cisco Introduction to Modern AI2026
03Cisco & OpenEDG Python Essentials 22026
04Introduction to Cyber Security: Stay Safe Online2026
05Dremio-Powered AI Agents2026
06Inclusive Open Source Community Orientation2026
07ISO/IEC 42001:2023 — AI Management System (AIMS), Alison2026
Data Analytics Essentials
Python Essentials 2
Modern AI
Cyber Security
Badge
07Common questions
What does Mukiibi Moses specialize in?
Artificial intelligence, machine learning, and data science, with a focus on emotion-aware systems and NLP.
What projects has he worked on?
Emotional support AI, sentiment analysis pipelines, generative AI models, an airport simulation, and a digital wallet system.
What technologies does he use?
Python, AWS, NLP models, Stable Diffusion, Streamlit, the Groq LLM API, and various data engineering tools.
Where can I find his research work?
Published on Google Scholar, ResearchGate, and Academia.edu.
08Learn AI

Foundational concepts in artificial intelligence, machine learning, and data science — plain explanations with real-world applications.

What are AI emotional response systems?
What is artificial intelligence?
What is natural language processing?
Machine learning basics
Generative AI optimization — research
Generative AI explained
Deep learning explained
Let's build something worth measuring.
Open to research collaborations, internships, and AI projects. Reach out through any channel below.
LinkedIn
GitHub
Credly
ORCIDORCID
RGResearchGate
GSGoogle Scholar
WoSWeb of Science
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