Six researchers using data science across different disciplines have received seed grants through the Data Science Initiative’s Seed Funding Program.
Announced in May 2019, the Data Science Initiative’s Seed Funding Program encourages new faculty partnerships and the development of innovative research and educational programs in data science.
Similar to the Resilience Initiative Seed Funding Program, the Data Science Seed Funding Program is open to tenure-related faculty members or career faculty members in the research professor, research scientist, research engineer or research associate classification who hold a UO appointment during the academic year of the research award.
The Data Science Seed Funding program provides up to $10,000 for Convening Grants to support the initial stages of project planning, and $50,000 for Piloting Grants which are meant to help projects turn into competitive proposals. The award supports expenses over a project period of up to 12 months.
The projects were chosen for alignment with the goals of the Data Science Initiative and their likelihood to successfully launch significant new data science collaborations. Awarded projects comprise faculty from the College of Arts and Sciences, the College of Education, the College of Design, and the School of Law, and support activities in UO Portland and the Eugene campus.
The project topics and grant recipients are:
- Relating learning and intelligence across artificial and human agents. Ben Hutchinson, Department of Psychology; Daniel Lowd, Department of Computer and Information Science
- Responsible Data Science: Social Impacts and Ethical Challenges. Colin Koopman, Department of Philosophy; Nicolae Morar, Department of Environmental Studies; Kristen Bell, Law School; Ramon Alvarado, Department of Philosophy; Paul Showler, Department of Philosophy
- TWEEDS: The Workshop in Environmental Economics and Data Science. Edwin Rubin, Department of Economics; Dr. Grant McDermott, Department of Economics; Dr. Eric Zhou, Department of Economics
- Integrating spatial data science and epidemiology: Bayesian spatiotemporal modeling of HIV at small-areal levels in Philadelphia, 2009-2016. Hui (Henry) Luan, Department of Geography
- 3D Anthropometric Scanning and Machine Learning to Understand Patterned Geometries of Athletes. Susan L. Sokolowski, Department of Product Design; Jake Searcy, Research Advanced Computing Services
- Community health and school readiness: Closing the gap. Daniel Anderson, Department of Behavioral Research and Teaching; Leilani Sáez, Department of Behavioral Research and Teaching; John Seeley, Department of Special Education and Clinical Sciences
“These exciting projects exemplify a wide breadth of data science and build strong new connections across the university's schools and colleges,” says Bill Cresko, executive director of the Data Science Initiative. “These awards will support great work in data science, empower new scholarship, and ultimately help our faculty use data to better society.”