About

PhD technologist combining hands-on AI-powered tool development, technical communication expertise, and deep data science foundations. Experienced across enterprise cloud documentation, AI-powered tool development, and computational astrophysics research.

Resume

I tailor my resume for each role. To request a copy, please reach out via email or LinkedIn.

Education

Postdoctoral Fellow in Astrophysics

Shanghai Jiao Tong University | 2019 – 2022

Conducted independent research on cosmological simulations and weak gravitational lensing, publishing 4 first-author papers in peer-reviewed journals. Applied advanced statistical methods including MCMC sampling, Bayesian inference, and Gaussian Process Regression to analyze large-scale astronomical datasets.

Ph.D. in Physics

University of Texas at Dallas | 2014 – 2019

Specialized in computational astrophysics with focus on N-body simulations, data pipeline development, and scientific visualization. Developed Python-based analysis tools for processing terabyte-scale simulation data.

Technical Skills

Documentation & Content Strategy

  • Developer Documentation: API documentation, SDK guides, code samples, quickstarts, and tutorials
  • Information Architecture: Content modeling, taxonomy design, navigation optimization, and user journey mapping
  • Docs-as-Code: Git workflows, CI/CD pipelines, static site generators (Jekyll, Hugo), and automated publishing
  • Structured Authoring: DITA/XML, topic-based writing, content reuse, and single-sourcing strategies
  • Style & Standards: AWS Style Guide, SageMaker Developer Documentation, and terminology management
  • Documentation Metrics: Analytics-driven content strategy and documentation health scoring

AI-Powered Tools & Cloud Technologies

  • LLM Integration: Foundation model selection, prompt engineering, context management, and AI-assisted workflows
  • MCP Protocol: Model Context Protocol implementation for extending LLM capabilities
  • Workflow Design: Multi-stage AI pipelines with error handling and human-in-the-loop checkpoints
  • Python Development: Automation scripts, API integrations, and file processing for AI-powered systems
  • RAG Pipelines: Retrieval-Augmented Generation architecture, vector databases, and semantic search
  • AWS Services: SageMaker AI, HyperPod, Bedrock, Lambda, S3, CloudFormation, and IAM

Data Science & Analytics

  • Python Ecosystem: NumPy, SciPy, Pandas, scikit-learn, Matplotlib, Seaborn
  • Statistical Methods: MCMC sampling, Bayesian inference, Gaussian Process Regression, hypothesis testing
  • Data Visualization: Publication-quality figures, interactive dashboards, and data storytelling
  • Big Data Processing: Large-scale dataset analysis, data pipeline development, and ETL workflows
  • SQL & Databases: Query optimization, data modeling, and database documentation

Tools & Platforms

  • Version Control: Git, GitHub, GitLab, branching strategies, and code review workflows
  • Authoring Tools: VS Code, Oxygen XML Editor, LaTeX, Notion, and Markdown
  • Design & Prototyping: Figma, draw.io, Matplotlib, and technical diagramming

Connect

I'm currently exploring new opportunities in AI-powered tool development, technical communication, data science, and solution architecture.