TRIADS Seed Grant Program

About the Program

The mission of TRIADS is to produce impactful research using the quantitative tools of the digital age to understand important societal problems.

The TRIADS Seed Grant Program aims to create and support focused transdisciplinary teams pursuing important research in this domain. These funds will bring together researchers across Arts & Sciences and beyond to quickly advance existing research teams, develop projects in new transdisciplinary fields of inquiry, and build communities of potential collaborators around shared questions, methods, and data.

The TRIADS seed grant program will fund awards up to $100,000 in direct costs for a one-year period.  Priority will be given to new projects with high scientific merit that are not currently funded by other sources and that have high potential for eventually securing external grant funding. Smaller proposals for exploratory research, thematic conferences, workshops, and related activities are also encouraged, but will be prioritized using the same criteria. 

Successful proposals will also be given priority access to other TRIADS resources including our data science engineering team, a grants development specialist, and collaborative space.

2023 Seed Grant Recipients:

Accounting for Human Bias to Improve AI-Assisted Decision Making
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
Elizabeth Mallott (Biology), Theresa Gildner (Anthropology), Claire Masteller (Earth and Planetary Sciences)

Mobile Assessment of Daily Life Contexts Using Smartphones
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
Roman Garnett (Computer Science & Engineering), Joshua Jackson (Psychological & Brain Sciences), Jacob Montgomery (Political Science)

MOBOGEN: Data-Driven Modeling of Mobility, Borders, and Genetics
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
Brent Hickman (Olin School of Business), Jessie Sun (Psychological & Brain Sciences)

The Relationship Between State Violence, Trust in Government, and Vaccine Uptake
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
William Yeoh (Computer Science & Engineering), Dino Christenson (Political Science)

Conformal Prediction for Uncertainty Quantification in Emerging Application Areas, from Materials to Social Science
Robert Lunde (Mathematics and Statistics), Robert Wexler (Chemistry), Betsy Sinclair (Political Science)

Measuring Financial Innovation via Natural Language Processing
Ana Babus (Economics), Chenguang Wang (Computer Science & Engineering)


For additional resources or support, please email Jacob Montgomery, Tammy English, or Bhavna Hirani.

Our Team