I am a Digital Business & Innovation student. I am learning advanced technologies to digitalize business operations and solve real business problems.
My current focus is Data Analytics and Explanable- Practical AI systems for Enterprise Digital Transformation.
My applied area is customer analytics, where I use data to understand customer behavior and support better business decisions.
My developing pathway is Positive Computing and Cogitive Computing ===> build human-centered AI systems
[Alert!] I love diagram-- mindmap, therefore, most of the documents are filled with diagrams. Thank you!!!
Technical Skills
My Learning Journey
From Existing business Problem -> DIgital( AI) solutions -> Overall Business Digital transformation and achieve business goals
| Year 1 Technical Foundation |
Python · R · Computer Networking · Business Principles Built my foundation in programming, statistical thinking, and basic system/network understanding. |
| Year 2 Data & Business Foundation |
Statistics · Mathematics · Database_Big Data Developed core data analysis skills and learned how technology connects with business operations. |
| Career Practicum Enterprise Experience |
IHI & Aster internship-based project Worked as a data analyst on bridge risk analysis and business proposal development. Result: List of Maintainance-needed bridge Proposal and Team received 95/100. This experience helped me understand enterprise business problems, infrastructure risk, and data-driven proposal design. |
| Turning Point AI Ethics & XAI |
AI & Intelligent Product Development Became interested in AI ethics, Explainable AI, and human-centered AI systems. |
| Year 3 Early Graduation / Research |
Bayesian Network + Genetic Algorithm for interpretable machine learning Started thesis research on interpretable ML and probabilistic reasoning. Status: CIDM 2026 paper submitted; result pending. |
| Current Focus Applied AI/Data |
Mining Unstructured Data · Business Analytics & AI · Customer Analytics & AI · Generative AI and application Developing toward Applied AI for business digitalization, positive computing, ethical AI, and explainable AI/Data solutions. |
Featured Projects
flowchart TD
A[Applied AI / Data Portfolio]
A --> B[ElderCare Agent]
A --> C[Bridge Monitoring Intelligence]
A --> D[Interpretable ML Research]
A --> E[AI Portfolio Website]
B --> B1[Multi-agent workflow]
B --> B2[RAG + lightweight GraphRAG]
B --> B3[Guardrails + human approval]
C --> C1[Bridge risk analysis]
C --> C2[Enterprise business proposal]
C --> C3[IHI & Aster practicum<br/>3rd place · 95/100]
D --> D1[Bayesian Network]
D --> D2[Genetic Algorithm]
D --> D3[Explainable prediction pathways]
Role: Individual project
Focus: Hybrid routing( ML-based + rule-based), RAG, lightweight GraphRAG, memory, guardrails and caregiver escalation
Value: Supports elderly users with safer, explainable next-step guidance. Link: View project repository
Role: thesis direction/ Collaborated research project
Focus: Interpretable machine learning, probabilistic reasoning, and explainable prediction pathways
Status: Paper submitted to ICDM 2026; result pending.
Role: Collaborated project / IHI Corporation Career Practicum / First hands-on experience with Enterprise Tech Solution
Focus: Bridge risk analysis, inspection prioritization, and business proposal
Result: Data analyst role. Team received 95/100.
Other Class Projects
| Project | Role | Focus | Result |
|---|---|---|---|
| Restaurant Review Intelligence | Class project | NLP, TF-IDF, model comparison | Built a review intelligence pipeline to detect negative reviews and extract complaint patterns. |
| Student Success Prediction | Class project | ML pipeline, feature engineering, recall-focused evaluation, business interpretation | Built an at-risk student prediction pipeline for early intervention support. |
My working approach
Every project follows the same thinking process:flowchart LR
A[Business / User Problem] --> B[Data or Knowledge Understanding]
B --> C[AI / ML Pipeline Design]
C --> D[Prototype]
D --> E[Evaluation]
E --> F[Explainability]
F --> G[Business or Social Value]
G --> H[Future Enterprise Roadmap]
Development Approach
P/s My current strengths are:
- can work and learn independently as well as in coordination
- understanding business or user problems,
- understand and design AI/ML workflows,
- researching suitable technical patterns,
- evaluating model behavior,
- documenting architecture,
- and explaining business value.
My next growth areas are:
- Improve traditional coding, maths foundation
- Improve System Design
- Improve skilsl in testing - security - cloud deployment
- practical, interpretable, production-level AI delivery.
Current Direction
My long-term goal is to become an Data scientist/ AI Researcher in Postive computing who can solve business and social problems with AI ethically and effectively.