AI & Data Science | Responsible AI Systems | Public-Sector Technology

Hi, I’m Ryan Tang — an Information Systems graduate from the National University of Singapore with a strong interest in data science, AI systems, and the governance of deployed AI. My work focuses on building AI solutions that operate effectively within highly regulated, real-world environments, where trust, compliance, and operational resilience are as important as raw performance.

I am particularly interested in how AI can be scaled responsibly in public-sector and institutional contexts, bridging technical innovation with strategic decision-making.

• Applied AI & Data Science
• Large Language Models & Agentic Systems
• Responsible AI & AI Governance
• Public-Sector & High-Trust Systems
• Automation for Complex Institutional Workflows

• Agentic AI & LLM Systems: Designed and deployed enterprise-grade LLM workflows using LangGraph and Retrieval-Augmented Generation (RAG), emphasizing explainability, compliance, and stakeholder trust.
• Data-Driven Decision Systems: Built predictive models under severe data constraints by augmenting internal datasets with external market signals, achieving strong real-world performance.
• Public-Sector Automation: Prototyped NLP-based systems to streamline analyst workflows, demonstrating how thoughtful automation can unlock higher-value human judgment.
• Education & Communication: Served as a teaching assistant for multiple university courses, developing the ability to translate complex technical concepts for non-technical stakeholders.

Languages
Python, R, SQL, Java, JavaScript, TypeScript, HTML/CSS

AI & Machine Learning
LLMs (LangGraph, RAG), Natural Language Processing, Computer Vision,
Time-Series Forecasting (LSTM), Reinforcement Learning

Data Science & Analytics
Statistical Modeling (scikit-learn, SciPy), Geospatial Analysis,
Automated Web Scraping, Data Visualization (Matplotlib, Seaborn)

Engineering & DevOps
Full-stack Development (Next.js, React, FastAPI, NestJS),
API Design, Optimization (Linear Programming), Git, PostgreSQL

• Designing AI systems that remain reliable, interpretable, and trusted at scale
• Exploring the intersection of technical AI development and strategic governance
• Translating hands-on engineering experience into higher-level system and policy thinking

• AI & data science roles in high-impact, high-trust environments
• Research or applied work on responsible AI and AI systems management
• Conversations on deploying AI within regulated or public-sector contexts

• LinkedIn: linkedin.com/in/ryantangmj
• Portfolio: ryantangmj.github.io
• Email: ryantangmj@u.nus.edu