Introduces physics-aware deep learning (PADL), an emerging approach that embeds physical laws into neural networks for accurate, efficient modeling. Topics include differential equations, physics-informed neural networks, neural operators, and PyTorch implementation. Students gain both theoretical foundations and practical skills to apply PADL across disciplines.

Fundamentals of data mining and machine learning within a common statistical framework. Topics include boosting, ensembles, Support Vector Machines, model-based clustering, forecasting, neural networks, recommender systems, market basket analysis, and network centrality.

This course provides the opportunity to offer a new topic in the subject area of data science.

Investigates a selected issue in public policy or leadership.

Covers data pipeline: techniques to collect data, organize, query & apply the data, and generate products that describe the insights. Topics include Python environments, containers using Docker, data wrangling with pandas, data acquisition via flat files, APIs, JSON formats, and webscraping, relational, document, and graph databases, exploratory data analysis including static & interactive data visualization, dashboards, and cloud computing.

Combines topics in data ethics, critical data studies, public policy, governance, and regulation. Address challenges by topic (Health, Education, Culture & Entertainment, Security & Defense, Cities, Environment, Labor). Research how data-centric systems are deployed within socioeconomic ecosystems and shape the world. Interrogate connections between data science, governments, industry, civil society organizations, and communities.

This course will provide a solid foundation of insights into how Congress works, essential for aspiring public policy advocates. Topics investigated include historical precedents for policymaking, the process of Congressional decision-making, and power dynamics in Congress. We will also identify and develop the leadership skills and tactics of successful advocates, placing recent controversies and public policy issues in an historical context.

Course explores the integration of moral & ethical considerations in addressing U.S. public policy challenges. Students study & contrast major philosophical & political theories of justice & the common good, including those that are embedded in the U.S. constitutional architecture; and consider and contrast how these theories would guide public policy choices.

Introduces classic and contemporary theory and research on the social psychology of stigma, primarily from the perspective of the stigmatized. Topics include stigma's origin and nature, stigma and self-concept, stereotype threat, attributional ambiguity, stigma and social interaction, and implications of stigma for education, health, and life attainment more generally. Provides an overview of this area of psychology and its policy implications. Prerequisites: Graduate Student

What are the most pressing policy problems facing Virginia and how can they be addressed? Students will learn how the broad historical forces of Virginia's past, her current political institutions, and changing social divisions shape public policy in Virginia today. Student projects will focus on current and future challenges facing the Commonwealth and develop strategies to address them.