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  • CAIS Seminar: Kayla de la Haye (University of Southern California) - Promoting Healthy Eating through Local and Global Social Networks

    Wed, Oct 16, 2019 @ 03:00 PM - 04:00 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Kayla de la Haye, University of Southern California

    Talk Title: Promoting Healthy Eating through Local and Global Social Networks

    Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series

    Abstract: Poor diets are a major cause of common 'lifestyle' diseases such as obesity, diabetes, and heart disease. Although eating is often conceptualized as an individual behavior, the evidence shows that it is shaped by social and environmental forces that are insufficiently addressed in many interventions. This talk describes how complex social networks of family, friends, peers, and community stakeholders influence what people eat, and how interventions and policy can target "social architecture" to promote healthy nutrition. I emphasize the important role of innovative network and data science methods, big data, and transdisciplinary team science to advance this work.

    This lecture satisfies requirements for CSCI 591: Research Colloquium


    Biography: Dr. de la Haye works to promote health and prevent disease by applying social network analysis and systems science. Her research, funded by the NIH, the NSF, and the DoD, targets family and community social networks to promote healthy eating and prevent childhood obesity, and to understand the role of social networks in group problem solving in families, teams, and coalitions. She is Treasurer of the International Network of Social Network Analysis (INSNA), and in 2018, she received the INSNA Freeman Award for significant contributions to the study of social structure.

    URL: www.kayladelahaye.com
    Twitter: @kayladelahaye


    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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