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TDAI's inclusive communities of practice enable researchers and partners from diverse backgrounds and specialties to connect around topics of shared interests. Co-directed by OSU faculty who make up TDAI's leadership team, the communities share ideas and opportunities for interdisciplinary research via email listservs, facilitated gatherings and other activities.
Click below to learn more about and join a TDAI community of practice.
Foundations of
Data Science & AI
A community centered on the theoretical and algorithmic foundations of data science and AI, and building connections to the broader data science community in a radial manner.
Responsible Data Science
Bringing together researchers from diverse fields around collaborative research on data science’s negative externalities and the mechanisms by which society can reduce these harms.
Sensing-Driven
Collaborative Science
Convening technologists, domain specialists and stakeholders to translate data science and engineering into solutions for smart campuses, cities and communities.
Foundations of
Data Science & AI
A community centered on the theoretical and algorithmic foundations of data science and AI, and building connections to the broader data science community in a radial manner.
Responsible Data Science
Bringing together researchers from diverse fields around collaborative research on data science’s negative externalities and the mechanisms by which society can reduce these harms.
Sensing-Driven
Collaborative Science
Convening technologists, domain specialists and stakeholders to translate data science and engineering into solutions for smart campuses, cities and communities.
Computational Health and Life Sciences
Building research teams with data scientists and experts from domain areas to develop big-data analytics that have translational value in health care and life sciences.
Computational Social Sciences
Using computational techniques and big data to address concerns related to human behavior and gain insights into basic social processes that cannot be identified with conventional methods.
Computational Health and Life Sciences
Building research teams with data scientists and experts from domain areas to develop big-data analytics that have translational value in health care and life sciences.
Computational Social Sciences
Using computational techniques and big data to address concerns related to human behavior and gain insights into basic social processes that cannot be identified with conventional methods.
