Smith Faculty Receive UMD Grants for AI Research Projects

Smith School professors received a share of $1.5 million in seed grant money from the University of Maryland for their new artificial intelligence research projects. Louiqa Raschid and Eaman Jahani received a grant for their work with campus counterparts to use AI for public health. Lauren Rhue received a grant for her research looking into the legal boundaries of AI-generated content.

A total of 22 grants were awarded by the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM), a collaborative hub that the university launched last spring to conduct research, offer innovative and experiential learning opportunities for students, and focus on responsible and ethical AI technology to advance the public good. UMD and its philanthropic and industry partners plan to invest more than $100 million in the institute over the next 10 years.

"This year’s AIM research seed awards fund bold, interdisciplinary projects that embody the institute’s mission: to advance innovative artificial intelligence research through our four pillars of accessibility, social justice, sustainability and learning,” said Sheena Erete, AIM associate director of research and College of Information associate professor. “We are proud to support scholars who are expanding what’s possible through thoughtful, inclusive and impactful research.”

The grants were awarded in several categories, with funding from AIM and matching funds from campus units.

In the Cross-College Collaborative Awards category, with grants between $100,000-$300,000:

CommunityTwin: A Digital Twin for Enhanced Decision-Making in Public Health 
College of Information Associate Professor Vanessa Frías Martínez; Dean’s Professor of Information Systems and UMIACS ProfessorLouiqa Raschid; Linguistics and UMIACS Professor Philip Resnik; Decision, Operations and Information Technologies Assistant Professor Eaman Jahani; and University of Washington Associate Professor of Health Systems and Population Health Neil Sehgal plan to develop a highly detailed yet adaptable set of models of a community known as a “digital twin” to assist policymakers in designing personalized, localized interventions for pressing community challenges. The system will integrate deep learning, human mobility data and fine-tuned large language models to simulate real-world behaviors and community mental models. 

In the Individual Faculty Awards category, with grants between $5,000-$20,000:

How Far Is Fair? Measuring Legal Boundaries in AI-Generated Content 
Decision, Operations and Information Technologies Assistant Professor Lauren Rhue plans to examine an overlooked question: How different does AI-generated content need to be from original copyrighted sources to qualify as fair use rather than derivative work? Rhue plans to systematically generate AI text in the style of specific writers and their original works, acquire expert opinions on the similarity between the AI-generated and original texts, develop a comprehensive distance measure using various similarity metrics, validate this measure through experiments with IP experts and law students, and fine-tune large-language models to identify copyright violations. This work may benefit less-established writers, who can struggle to enforce their copyright due to resource constraints. 

This story was adapted from a story originally published by Maryland Today, where you can read about all of the grant-funded projects. Read more.