The Transdisciplinary Institute in Applied Data Sciences (TRIADS) has announced its newest crop of seed grant recipients, with eight teams of researchers receiving funding.
Featuring faculty from four different WashU schools (Arts & Sciences, Brown School, McKelvey School of Engineering, and the School of Medicine), these projects leverage data science to address pressing societal issues. Each research team includes faculty representing multiple academic disciplines, providing the knowledge base to view problems and their potential solutions from many different angles.
“We were extremely impressed with the quality of submissions for this round of seed grants,” said TRIADS co-director Bo Li. “These projects represent WashU faculty asking big, provocative questions and assembling high-quality, transdisciplinary teams to study them.”
Additional funding for the seed grant teams will be provided by WashU Here and Next, the McDonnell Center for the Space Sciences, McKelvey School of Engineering, and the Weidenbaum Center on the Economy, Government, and Public Policy.
A strategic initiative of the Arts & Sciences Strategic Plan, TRIADS provides funding, training, and resources to elevate WashU’s use of data science tools.
The projects receiving funding are:
Characterizing Patterns of Behavior Among Adolescent Cannabis Users with Co-occurring Depression Symptoms
Principal Investigators: Hannah Szylk (School of Psychiatry), Renee Thompson (Psychological & Brain Sciences), Daphne Lew (School of Medicine)
Team Members: Tammy English (Psychological & Brain Sciences), Patricia Cavazos-Rehg (School of Medicine)
Following Missouri’s legalization of recreational marijuana in 2022, cannabis-based products are more accessible than ever to adolescents. The short- and longer-term health implications of cannabis use by adolescents are many, particularly for young people who are also dealing with depression. This project will study the effects of cannabis use on adolescents who exhibit symptoms of depression by refining and then deploying a smartphone-based health tool for teenagers from two St. Louis-based treatment centers. Study participants will track their cannabis use, depression symptoms, and treatments in real time, allowing researchers insight into how these factors impact one another.
The long-term goal is to develop a mobile health tool that can serve as a supplement to in-person treatment, providing effective interventions for teens dealing with depression alongside cannabis use.
Confronting the Next Decade of Data-Intensive Astronomy Ushered by LSST
Principal Investigator: Tansu Daylan (Physics)
Team Members: Nathan Jacobs (McKelvey School of Engineering), Soumendra Lahiri (Statistics and Data Science)
Astronomers at the Vera C. Rubin Observatory in Chile are about to launch a massive, decade-long study of the night sky called the Legacy Survey of Space and Time (LSST). By regularly imaging the southern hemisphere’s skies, the LSST aims to advance our understanding of dark matter, among other scientific goals.
But LSST faces a serious challenge by the sheer number of artificial objects that orbit our planet, such as satellite constellations and space debris. These reflect sunlight and contaminate images taken by ground-based telescopes in the form of streaks, potentially interfering with the ambitious goals of the LSST. The TRIADS-funded team will simulate LSST images with streaks caused by artificial objects, assessing their expected impact on the imaging dataset and the implications for similar future studies.
In Vitro Neurotoxicity and Socio-Environmental Analysis for Mapping Alzheimer’s Disease Risk Due to Particulate Matter Exposure
Principal Investigator: Joseph Puthussery (McKelvey School of Engineering)
Team Members: Rajan Chakrabarty (McKelvey School of Engineering), John Cirrito (School of Medicine)
Can increased exposure to fine particulate matter contribute to the risk of developing Alzheimer’s disease? This team will study this potential link through a multidisciplinary approach that integrates neurotoxicological research, machine learning, socioeconomic data analysis, and more. The team plans to produce an Alzheimer’s Disease Health Risk Map for the United States, highlighting hotspots with elevated levels of particulate matter and associated Alzheimer’s disease risks, emphasizing environmental justice and socioeconomic disparities while advancing understanding of how air pollution impacts neurological health.