Inaugural recipients of the AI-Informed Discovery and Inquiry Seed Grants announced

The Data Science and AI Institute, in collaboration with the Office of the Dean of the Krieger School of Arts and Sciences, has selected six teams for the inaugural AI-informed Discovery and Inquiry Seed Grants.

The inaugural grants bring together diverse, multidisciplinary teams, leveraging the integration of AI and data science to tackle pressing challenges across disciplines. These grants are jointly funded by the Data Science and AI Institute and the Office of the Dean of the Krieger School of Arts and Sciences.

The Data Science and AI Institute Research Director for Discovery, Paulette Clancy, under whose auspices the seed award competition was run said, “This program generated a lot of interest across a wide range of domain experts in humanities, social sciences, and natural sciences. The winners reflect that rich diversity of thought and scholarship. We can’t wait to see their progress featured in a colloquium in the fall.”

Chosen from a competitive pool, the selected teams presented proposals that demonstrate significant promise in AI-informed discovery and inquiry, showcasing their potential impact. They address a wide range of issues, from using AI tools to understand how religious attendance shapes the streams of socio-political information to employing machine learning to examine the selective passage of proteins through the nuclear pore complex at a proteome level. Each proposal is led by a principal investigator affiliated with the Krieger School of Arts and Sciences, with co-investigators drawn from experts across JHU, including the Whiting School of Engineering, the School of Medicine and SNF Agora Institute.

2024 AI-informed discovery and inquiry seed grant recipients

A machine learning approach to understand the selective passage of proteins through the nuclear pore complex at a proteome level
Principal Investigator: Yaijun Zhang, Assistant Professor in the Department of Physics and Astronomy and the Department of Biophysics

AI-Driven Analysis of Historical Sources
Principal Investigator: Yulia Frumer, Bo Jung and Soon Young Kim Professor of East Asian Science, Associate Professor and Chair in the Department of History of Science and Technology

AI Tools for the Study of World-Historical Patterns of Social Protest
Principal Investigator: Beverly Silver, Professor in the Department of Sociology, Director of the Arrighi Center for Global Studies

Baltimore’s Railroad History Rediscovered through AI
Principal Investigator: Louis Hyman, Dorothy Ross Professor of History and SNF Agora Institute Professor
Co-Investigators: Jeremy Greene, William H. Welch Professor of Medicine and the History of Medicine, Director of the Department of the History of Medicine, and the Center for Medical Humanities and Social Medicine; Sam Backer, Post-Doctoral Researcher, the Center for Digital Humanities

Mining Deep Visual Networks for Brain Vision Algorithms
Principal Investigator: Charles Connor, Professor of Neuroscience
Co-Investigator: Alan Yuille, Bloomberg Distinguished Professor of Cognitive Science and Computer Science

Sermons, Religion and Politics in America
Principal Investigator:  Hahrie Han, Stavros Niarchos Foundation Professor of Political Science, Inaugural Director of the SNF Agora Institute