<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Teaching | CRiSS-LAB</title><link>https://criss-lab.com/teaching/</link><atom:link href="https://criss-lab.com/teaching/index.xml" rel="self" type="application/rss+xml"/><description>Teaching</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><image><url>https://criss-lab.com/media/sharing.png</url><title>Teaching</title><link>https://criss-lab.com/teaching/</link></image><item><title>Network Science and Complex Systems</title><link>https://criss-lab.com/teaching/network-science-complex-systems/</link><pubDate>Fri, 15 May 2026 00:00:00 +0000</pubDate><guid>https://criss-lab.com/teaching/network-science-complex-systems/</guid><description>&lt;p>This course introduces network science as a technical and conceptual language for studying social, technological, biological, and organizational systems. Students work with graph construction, centrality, communities, null models, diffusion, link prediction, and graph-based machine learning.&lt;/p>
&lt;p>The public course site is available at &lt;a href="https://networks.criss-lab.com/" target="_blank" rel="noopener">networks.criss-lab.com&lt;/a>.&lt;/p></description></item><item><title>Complexity Global School for Emerging Political Economies</title><link>https://criss-lab.com/teaching/complexity-global-school-2025/</link><pubDate>Tue, 09 Sep 2025 00:00:00 +0000</pubDate><guid>https://criss-lab.com/teaching/complexity-global-school-2025/</guid><description>&lt;p>Cristian Candia participated as invited faculty in the Complexity Global School for Emerging Political Economies 2025, organized by the Santa Fe Institute and Universidad de los Andes. The program brought together students and practitioners from different disciplines to study complexity approaches to political and economic challenges.&lt;/p></description></item><item><title>Causal Inference for Data Science</title><link>https://criss-lab.com/teaching/causal-inference-data-science/</link><pubDate>Fri, 01 Aug 2025 00:00:00 +0000</pubDate><guid>https://criss-lab.com/teaching/causal-inference-data-science/</guid><description>&lt;p>This teaching line focuses on moving from predictive models to causal questions: what would happen under a different intervention, policy, design, or institutional decision?&lt;/p>
&lt;p>Topics include directed acyclic graphs, confounding, matching, fixed effects, difference-in-differences, regression discontinuity, instrumental variables, sensitivity analysis, and causal machine learning.&lt;/p></description></item><item><title>Computational Social Science</title><link>https://criss-lab.com/teaching/computational-social-science/</link><pubDate>Fri, 01 Aug 2025 00:00:00 +0000</pubDate><guid>https://criss-lab.com/teaching/computational-social-science/</guid><description>&lt;p>This course area introduces computational approaches to human behavior and social systems. It connects theory with data pipelines, network thinking, experiments, digital traces, text analysis, and responsible interpretation of large-scale observational data.&lt;/p></description></item><item><title>Technological Entrepreneurship and Applied AI</title><link>https://criss-lab.com/teaching/technology-entrepreneurship/</link><pubDate>Fri, 01 Aug 2025 00:00:00 +0000</pubDate><guid>https://criss-lab.com/teaching/technology-entrepreneurship/</guid><description>&lt;p>This teaching area helps students move from research ideas and prototypes to usable products. It covers problem discovery, evidence-based product design, technical validation, impact metrics, responsible AI, and the translation of computational social science into tools for organizations, schools, and public institutions.&lt;/p></description></item></channel></rss>