Student engagement and enrichment in Data Science (SEEDS)
We are an interdisciplinary vision of computing research that bridges Black Studies, Chicano Studies, Statistics, Molecular and Cellular Biology, Neuroscience, Engineering and Computer Science to create a new and student-driven foundation through a data science living and learning community for understanding issues of personal significance through a diverse lens.
A Data Science Living and Learning community for UCSB students (including incoming Freshman and Transfer). This program will draw the interest of prospective and current students that prioritize professional outcomes, small cohort-based learning, and opportunities for interdisciplinary and convergent learning. This is an opportunity for UCSB student populations to deeply understand and potentially make meaningful contributions in data science with goals to study ethics, how data is conceptualized and utilized in STEM, Social Sciences and Humanities. Our focus is to approach data science through workshops, conversations, mini lectures with a goal of integrating data science towards formal instruction in diverse disciplines.
We work with partner Departments on campus to connect first year and transfer students in various majors to foster skills, training and workforce development. Beyond the obvious PSTAT and Math Departments, our student majors include Computer Science, Molecular and Cellular Developmental Biology. In the Social Sciences, key majors include: Black Studies, Chicano Studies, Sociology, Communications, and Economics.
- Knowledge building through a multifaceted and interdisciplinary intersectional process facilitated by a living and learning community.
- Knowledge and Skill Building: Development, coordination and implementation of undergraduate opportunities in computational/data science.
- Design, develop and implement training and research modules that would explain computation/data science and research potential with large scale data sets in STEM, Social Science and Humanities during the academic year through a hands-on experiential research opportunity beginning their freshman and follow up years.
- Provide professional development and curriculum integration for URM undergraduate students who are interested in the intersection involving computational/data science, African American/Black studies, Biology, Chicanx/Latinx studies, Communications, Information Science , Neuroscience and other STEM fields during the academic year.
- Conceptualize, research, coordinate and develop data management plans with a collaborative team to determine activities and plans for computational/data science, Ethnic Studies, Biodiversity and Ethics. Identify key issues and resources in the development of data management for Ethnic Studies in data science and large-scale data sets (Belle Sterman & Clark, 2017; Harron, 2017; Matteson, Sherrod & Ceyhun Cetin, 2016).
The application is now avaliable to students. If you are interested, click here to apply.
Finally, our goals focus on the illumination of sociotechnical space, harnessing the data revolution through innovative educational pathways, and leveraging convergent research using STEM and computational/data science.
Our team and partners include:
Sharon Tettegah, PhD., Black Studies
Kenneth Kosik, MA., MD., Molecular, Cellular & Developmental Biology, Neuroscience
David Low, PhD., Molecular Cellular Developmental Biology
Tim Sherwood, PhD., Computer Science
Yekaterina Kharitonova, PhD., Computer Science
Michael Ludkovski, Statistics & Applied Probability
Kathy Foltz, PhD., Molecular Cellular Developmental Biology
Jon Jablonski, Interdisciplinary Research Collaboratory, UCSB Library
Marian Bankins, MA., Interim Director, Residential & Community Living-Housing, Dining and Auxiliary Enterprises
Marcus Mathis, Admissions and Outreach
Paige Miller, PhD., Marine Science Institute
Naomi Tague, PhD., Bren School of Environmental Science and Management
Blacks in neurocomputation is the development, coordination and implementation of undergraduate opportunities in data science.