Public Health Data Science and Data Equity (DSDE)

Public Health Data Science and Data Equity (DSDE) aims to strategically support and elevate data science training, education, research and collaboration efforts at the Yale School of Public Health and promote data equity as a fundamental pillar of health equity.

We aim to:

• Elevate and transform public health research via cutting-edge data science discoveries and impactful implementation, with a focus on developing a novel framework of data equity and positive social change.

• Empower and enable the next generation of public health leaders with an essential mastery of core data science and artificial intelligence (AI) techniques.

• Enhancing Education: Strengthening training and educational programs to cultivate the next generation of public health data science leaders, proficient in core data science methodology and emerging AI/ML tools.

• Guiding Responsible Innovation: Providing thoughtful guidance on the ethical/responsible development and application of data science methods, prioritizing data equity.

• Building Infrastructure: Developing a robust health data science infrastructure that ensures secure and equitable data access, and facilitates the translation of methodologies into user-friendly, open-source software, tools, and publicly available databases.

• Fostering Community: Creating a diverse and inclusive community of scholars dedicated to public health data science and data equity initiatives.

• Forming Alliances: Collaborating with other quantitative data science units at Yale and beyond to integrate and streamline access to data science resources.

• Promoting Open Knowledge: Establishing open-source knowledge portals and collaborative platforms to make data science resources accessible to communities in New Haven, Connecticut, and globally, while forging/fostering partnerships that enhance community engagement in data science.