Teaching

Most of my teaching is in quantitative research methods for undergraduate and graduate students in Political Science and Social Data Analytics at Penn State, plus workshops for Statistical Horizons and international programs.

Ridge and lasso coefficient paths — Ridge versus lasso coefficient paths on turnout data, from the regularization day of my machine learning workshop.

Bias-variance tradeoff — The bias-variance tradeoff behind regularization.

The Social Data Stack framework used in the Social Data Analytics program.

PLSC 508: Political Network Analysis

Graduate seminar on network theory and statistical network models.

Machine Learning for Political Science

Prediction, regularization, trees and boosting, and text as data for social scientists.

SoDA 501: Approaches and Issues in Big Social Data

Core seminar in the Social Data Analytics dual-title Ph.D.

Workshops

Machine learning workshops for Statistical Horizons and İstanbul Bilgi University, with open course materials. Bilgi materials.

Syllabi and course materials remain available on the current teaching page.

Recognized with the 2026 Best Graduate Teaching Award, Penn State Department of Political Science.