YM
Educator & researcher Brandeis University

Yeabin Moon

Questions worth asking. Ideas worth testing.

Explore data science, economics, and AI through questions we can investigate, ideas we can build, and evidence we can explain.

Start with prompting, evidence checks, and local models. Retrieval, agents, and routing are next.

Explore Learn

What changed in
Apple’s AI risk disclosures?

Two annual reports. A new detail, a change in emphasis, and a warning that stayed the same. Can you tell them apart—and support your interpretation?

Available now
Prompt practice, two worked Apple examples, and a four-company practice exercise.

Taking shape

  • Document retrieval
  • Bounded agents
  • Orchestration and routing
Investigate the disclosure changes

Build a pipeline.
Defend its answer.

Explore finance, practical AI, or both through a shared business investigation. Designed for MSBA; students from other programs are invited to contact me about permission.

AI Engineering with
Unstructured Business Data

Explore the course

Selected research.

Accepted for publication

Winners Revert, Losers Rebound

Rob Brown, Yeabin Moon, and Bo Wang
The Journal of Beta Investment Strategies

Research preprint 2026

The Price of Thinking

Examining how AI reasoning-effort settings affect cost and accuracy within a model-specific API contract.

Connecting data science,
business, and AI.

I am a Senior Lecturer in Data Analytics at Brandeis School of Business and Economics. My work connects data science, economics, and the practical questions raised by artificial intelligence.

My teaching spans data analytics, Python programming, data visualization, and natural language processing, with a growing focus on AI engineering and its applications in business and management.

I hold a Ph.D. from the University of Houston.

Brandeis faculty profile

Have a question or an idea?

Get in touch about a course, a research question, or a collaboration.

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