The Duke Science and Technology (DST) Launch Seed Grants recognize the initiation of high-impact, interdisciplinary projects by faculty from multiple disciplines across campus and the School of Medicine.

A Federated Infant Neuroimaging Analysis (FINNEAS) Platform: An Intuitive, Cloud-based Tool Facilitating Reproducible, Accessible, and Secure AI

Medicine + Engineering

PIs: Yun Wang, Assistant Professor of Psychiatry and Behavioral Sciences; Hai “Helen” Li, Professor of Electrical and Computer Engineering

This team aims to develop a user-friendly, cloud-based tool for analyzing MRI scans of developing infant brains. It will be based on artificial intelligence, but users will not be required to have any advanced computational skills to take advantage of the platform, named FINNEAS, the Federated Infant Neuroimaging Analysis Platform. The system will also accommodate patient privacy and differences in data from one scanning center to the next.


Direct-printed On-Skin Electronic Drug-delivery (DOSED) for GLP-1RA Therapy

Engineering + Medicine

PIs: Aaron Franklin, Addy Professor of Electrical and Computer Engineering; Jonathan Campbell, Associate Professor of Medicine; Fan Yuan, Professor of Biomedical Engineering

This team will be studying an electronic ‘tattoo’ device for continuously delivering drugs to treat type two diabetes through the skin. The printed device will be tested on skin samples to demonstrate its functionality.


Duke Registry for Equitable Access to Medicine (DREAM)

Global Health + Medicine + Public Policy + Social Sciences

PIs: Sara LeGrand, Associate Research Professor of Global Health; Carly E. Kelley, M.D., M.P.H., Assistant Professor of Medicine; Kathryn Whetten, Professor of Public Policy; Gabriel Rosenberg, Associate Professor of Gender, Sexuality and Feminist Studies

Expanding on an initial infrastructure built under previous funding, this multidisciplinary team is going to assess structural inequities faced by transgender and non-binary people as they seek health care, including gender affirming care. A patient population built from Duke Health and the Mayo Clinic will be regularly assessed to answer long-term mental and physical health questions about this population and the hope is that this resource can attract further funding and expand, once it has been built.


Temperature-responsive Protein Phase Separation To Drive Plant Growth

Natural Sciences + Engineering

PIs: Lucia Strader, Associate Professor of Biology; Ashutosh Chilkoti, Alan L. Kaganov Distinguished Professor of Biomedical Engineering

This team, led by a plant biologist and a biomedical engineer, is pursuing a method to engineer a key transcription factor that drives plant growth to be optimized for higher temperatures. Building on a discovery about how plants stockpile this protein to respond to environmental change, and the ability to engineer temperature-sensitive synthetic gene transcription factors, the team hopes to tune plant growth at different temperatures.


Towards Watershed Ecotoxicology: Rapid Assessment Protocols for Mapping Chemical Risk in Urban Freshwater Networks

Natural Sciences + Environment + Engineering

PIs: Emily Bernhardt, James B. Duke Distinguished Professor of Biology; Nishad Jayasundara, Assistant Professor of Environmental Toxicology and Health; Heileen Hsu-Kim, Professor of Civil and Environmental Engineering; Jonathan Behrens, University Program in Ecology Ph.D. Student

Building on preliminary work by a Bass Connections team, this project will be sampling ten different areas of the Ellerbe Creek Watershed, which drains most of Durham into Falls Lake. Rather than measuring every compound in the stream, they are looking for contaminant signals that indicate various types of human activity: Sucralose sweetener from human waste, a chemical additive found in automobile tires from road runoff, and the herbicide RoundUp and its breakdown products from landscaping. These will be used as indicators to model the mix of sources reaching the stream. Laboratory fish will be used to assess the biological effects of different mixtures.


Uncovering the Grammar of Social Interaction Using Machine Vision and Interpretable Machine Learning

Natural Sciences + Social Sciences

PIs: Hau-Tieng Wu, Associate Professor of Mathematics; Jana Schaich Borg, Associate Research Professor in the Social Science Research Institute

Using hundreds of hours of recorded video conversations, this team will use artificial intelligence to measure the growing trust and synchrony between two interacting people, as depicted by their body poses and facial expressions. They are looking for motifs of social interaction that are stereotypical and re-used in many interactions in the hope that they can begin to uncover what they call the “behavioral grammar” of social interactions. These tools might eventually be used to measure social interaction disorders.


Using Wearables for Perioperative Surgical Patient Monitoring

Engineering + Medicine

PIs: Jessilyn Dunn, Assistant Professor of Biomedical Engineering; Shelley Hwang, M.D., M.P.H., Mary and Deryl Hart Distinguished Professor of Surgery

This team will be using wearable devices to monitor up to 50 patients before and after surgery as a way to track surgical recovery. Inexpensive, unobtrusive monitoring of post-operative physiology may help to identify early complications after surgery and reduce costly hospital readmissions.


3D Photonic Structure as Catalyst Support for Plasmonic Catalysts To Enable Solar Ammonia Synthesis Under Concentrated Sunlight

Natural Sciences + Engineering

PIs: Jie Liu, George Barth Geller Distinguished Professor of Chemistry; Natalia Litchinitser, Professor of Electrical and Computer Engineering

The team is designing a 3D catalyst system that can use solar energy to enhance chemical reactions. Their seed grant is aimed at a proof-of-concept called “3-D solid fog,” a lattice of boron nitride microtubes which can be used as catalyst support for plasmonic nanoparticle to enable more efficient use of solar light in chemical synthesis. They will be using artificial intelligence to optimize the design of the microstructured fog and then testing it in solar light powered synthesis of ammonia, which is both a valuable fertilizer and a highly efficient carrier of hydrogen, storage of which will be critical to hydrogen-fueled, carbon-neutral technologies.