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.

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

Consider the effect of public opinion on policy in the U.S. What do policymakers believe about citizens' preferences? Whose opinion matters, when does it matter, & why? Do policies always reflect the majority? How has partisan polarization affected policy-making in recent years? Examine questions through lens of some of today's most pressing issues, including immigration policy, social welfare programs, military spending, abortion, & more.

Students register for this course to complement an industry work experience. Topics focus on the application of engineering principles, analysis, methods and best practices in an industrial setting. A final report is required.

Guiding students in a 2-credit undertaking that culminates in a Public Safety Capstone project. MPS faculty support topic identification, literature review and research, and analysis/synthesis of data to demonstrate achievement of project objectives. Interactive sessions involve Q&A, progress presentations, and peer feedback. Course completes with an article-length paper and video presentation.

The DH Certificate Practicum provides principles for working with humanities materials as data, while maintaining a commitment to humanistic inquiry. Students will learn to integrate digital humanities methods into coursework and research required in their home departments. This course provides students with a broad understanding of basic technologies and approaches used by digital humanists and introduces data standards and data modeling

This course provides an opportunity for graduate students in the humanities and social sciences to reflect upon and plan for post-graduation career opportunities both in the academe and in other areas.

Teams will solve an analytics challenge from a sponsoring company. The company will provide the data and the problem. You and your team will design a solution in the form of a set of visualizations and a model and assess the business impact in conjunction with the sponsoring company. Key questions: How much money will the proposed solution save? How many new customers will the proposed solution attract? The core deliverable is a presentation.

In the second capstone course you will assess the business impact of your solution and should be done in conjunction with the sponsoring company. Key assessment questions may include: a) how much money (or other resources) will the proposed solution save? b) How many new customers will the proposed solution attract? c) how much money will current customers spend? The core deliverable is a report on the business impact your proposed solution.