TRIADS Seed Grant Program
2024 Seed Grant Recipients
The Transdisciplinary Institute in Applied Data Sciences (TRIADS) has announced its newest crop of seed grant recipients.
View project summaries here.
Characterizing Patterns of Behavior Among Adolescent Cannabis Users with Co-occurring Depression Symptoms
Principal Investigators: Hannah Szylk (School of Medicine), Renee Thompson (Psychological & Brain Sciences), Daphne Lew (School of Medicine)
Team Members: Tammy English (Psychological & Brain Sciences), Patricia Cavazos-Rehg (School of Medicine)
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)
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)
Integrating Geographic Information Systems and Electronic Health Records for Scalable Real-World Evidence Generation: A Case Study on Opioid Use Disorder
Principal Investigator: Linying Zhang (School of Medicine)
Team Members: Devin Banks (School of Medicine), Nan Lin (Statistics and Data Science), Min Lian (School of Medicine), Chenyang Lu (McKelvey School of Engineering)
Investigating Geographic Disparities in Social and Environmental Determinants of Hypertension in the Greater St. Louis Area
Principal Investigator: Lindsay Underhill (School of Medicine)
Team Members: Jenna Ditto (McKelvey School of Engineering), Kenan Li (Saint Louis University)
Machine Learning Using Cardiotocography and Other Intrapartum Data to Predict Birth Outcomes
Principal Investigator: Christopher Ryan King (School of Medicine)
Team Members: Chenyang Lu (McKelvey School of Engineering), Michael Dombrowski (School of Medicine)
Neighborhood Change, Student Mobility, and School Belonging: Novel Insights Using Advanced Methods and Algorithmic Data Linkages
Principal Investigator: Jason Jabbari (Brown School)
Team Members: Christopher Rozek (Education), Ted Enamorado (Political Science)
Understanding the Facets of Stakeholder Trust in AI Tools for Housing
Principal Investigator: Chien-Ju Ho (McKelvey School of Engineering)
Team Members: Patrick Fowler (Brown School), Alex DiChristofano (Computational & Data Sciences)
2023 Seed Grant Recipients
View project summaries here.
Accounting for Human Bias to Improve AI-Assisted Decision Making
Faculty: Wouter Kool (Psychological & Brain Sciences), Chien-Ju Ho (Computer Science & Engineering)
Legacy of Neglect: Linking Flood Hazards, Pathogen Exposure, and Health Inequities in Cahokia Heights, IL
Faculty: Elizabeth Mallott (Biology), Theresa Gildner (Anthropology), Claire Masteller (Earth, Environmental, and Planetary Sciences)
Mobile Assessment of Daily Life Contexts Using Smartphones
Faculty: Tammy English (Psychological & Brain Sciences), Jason Hassenstab (Neurology), Sojung Park (Brown School of Social Work), Ariela Schachter (Sociology)
A Gaussian Process Framework for Idiographic Measurement of Psychological Traits
Faculty: Roman Garnett (Computer Science & Engineering), Joshua Jackson (Psychological & Brain Sciences), Jacob Montgomery (Political Science)
MOBOGEN: Data-Driven Modeling of Mobility, Borders, and Genetics
Faculty: Michael Frachetti (Anthropology), Nathan Jacobs (Computer Science & Engineering), David Carter (Political Science)
A Field Experimental Analysis of the Process and Implications of a Diverse and Inclusive Workplace: Social Identity, Communication, and Performance
Faculty: Brent Hickman (Olin School of Business), Jessie Sun (Psychological & Brain Sciences)
The Relationship Between State Violence, Trust in Government, and Vaccine Uptake
Faculty: Caitlin McMurtry (Brown School of Social Work), Michael Esposito (Sociology), Matthew Gabel (Political Science), Darrell Hudson (Brown School of Social Work)
Study of Polarization in Social Networks through Empirical Modeling and Simulations
Faculty: William Yeoh (Computer Science & Engineering), Dino Christenson (Political Science)
Conformal Prediction for Uncertainty Quantification in Emerging Application Areas, from Materials to Social Science
Faculty: Robert Lunde (Statistics and Data Science), Robert Wexler (Chemistry), Betsy Sinclair (Political Science)
Measuring Financial Innovation via Natural Language Processing
Faculty: Ana Babus (Economics), Chenguang Wang (Computer Science & Engineering)