Valuing Diverse Stakeholder Collaborations
Student Opportunities
NYU Students & Potential Trainees External Students & Potential Trainees Workshop: GenAI & HPC Workshop: Assessing climate impacts on population health Flyers NYU Students & Potential Trainees NYU The Center for Health Data Science at NYU offers a diverse array of opportunities for students to engage in hand-on learning experiences in the field of Health Data Science. Our programs are designed to provide practical skills, foster academic growth, and prepare students for successful careers in this rapidly evolving field. Internships We support internships with our faculty and other researchers at the School of Global Public Health, allowing students to contribute ...
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Using Data To Capture and Change Structural Factors
Upstream factors are important for preventing and mitigating health disparities. We bring focus to how data can be used to capture these social and environmental factors, and how to incorporate them in models that affect change. Relevant Papers Zhao, Y., Paul, R., Reid, S., Vieira, C. C., Wolfe, C., Zhang, Y., & Chunara, R., 2024. Constructing Social Vulnerability Indexes with Increased Data and Machine Learning Highlight the Importance of Wealth Across Global Contexts. Social Indicators Research. Zhang, M., Rahman, S., Mhasawade, V., & Chunara, R., 2024. Utilizing big data without domain knowledge impacts public health decision-making. Proceedings of the National Academy of Sciences of ...
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New data in public health
Novel data sources offer opportunity for high-granularity public health. In this work we have studied many types of data and their relevance in time and space.
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Smart Community-level Targeting by Combining Artificial Intelligence and Mobile Tools
This work uses machine learning to examine how to improve the reach of public health interventions to marginalized populations.
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NSF CAREER: Learning from When, Where and by Whom Data is Generated for Advancing Public Health Studies (2019-2024)
This award is focused on developing new machine learning and data science approaches motivated by the need to improve data management and analysis in the public health domain. The project will also provide educational programs informed by best practices in research for public health practitioners, students, and community members in the context of data science and public health.
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Social Determinants and Risk Prediction
Social determinants play an important role in shaping noncommunicable disease. We are examining the role of social determinants in clinical risk prediction as well as appropriate modeling strategies for their integration.
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