About

Professional bio and positioning statement.

I am an Assistant Professor of Data Science with a focus on causal inference, statistical learning, trustworthy AI systems, and decision-making from imperfect data.

This site is designed as a living public record of my work in industry-oriented causal inference and AI systems. The goal is to make my expertise legible to multiple audiences: academic collaborators, students, hiring teams, product leaders, data science managers, and organizations that need credible evidence and reliable AI-enabled workflows.

Positioning

My work sits at the intersection of:

• Causal identification: clarifying which assumptions are needed to answer a decision question.
• Applied estimation: implementing robust methods with transparent diagnostics.
• AI systems design: building RAG, agentic, multimodal, and evaluation-driven LLM workflows.
• LLMOps: monitoring hallucination risk, drift, regressions, model versions, prompts, and system behavior.
• Business translation: turning uncertainty, effect heterogeneity, and limitations into better decisions.
• Teaching: explaining technical ideas through examples, notebooks, and reusable notes.

Professional Themes

• Credible decision-making from observational, experimental, and quasi-experimental data.
• LLM-powered systems that are evaluated, monitored, and improved over time.
• Technical communication that connects methods to product, policy, and business action.
• Reproducible public artifacts: notebooks, tutorials, system designs, and case studies.

Replace With Your Bio

Use this section for a more personal biography:

• Your name and current institution.
• Your research and teaching areas.
• Selected publications, grants, or applied collaborations.
• Industry-facing strengths you want recruiters or collaborators to remember.
• A short note about what kinds of opportunities you are open to.