Introduction to Causality – Ricardo Aguilar

Seminar
Data Science
Causal Inference
Author

Khushi Choudhary

Published

January 31, 2025

Upcoming Seminar: Introduction to Causality

Presented by Ricardo Aguilar

Join us for an engaging seminar exploring the foundations of causal inference β€” a powerful framework for identifying what truly causes what in data.

This talk will introduce key concepts in causal reasoning, blending classical statistical thinking with modern machine learning approaches.

πŸ“š Topics Covered:

  • Understanding Directed Acyclic Graphs (DAGs) as tools for representing cause-and-effect
  • The role of counterfactuals and potential outcomes in causal analysis
  • Key assumptions: exchangeability, positivity, and consistency
  • Approaches to causal structure discovery (test-based & score-based methods)
  • A conceptual walkthrough of Inverse Probability Treatment Weighting (IPTW) and its practical challenges

πŸ—“οΈ Event Details

πŸ“… Date: January 31, 2025
πŸ“ Location: Holt Hall 291
πŸ—£οΈ Speaker: Ricardo Aguilar

Whether you’re working in data science, public health, economics, or social science, this seminar will help sharpen how you approach causal questions in your field.

All majors welcome β€” no prior causal inference experience required!