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I am interested in theory and methodology for network analysis, causal inference and statistical/computational tradeoffs and in applications in the social sciences. Modern data streams frequently do not follow the traditional paradigms of n independent observations on p quantities of interest. They can include complex dependencies among the observations (e.g. interference in the study of causal effects) or among the quantities of interest (e.g. probabilities of edge formation in a network). My research is concerned with developing theory and methodological tools for approaching such modern data structures by better understanding these underlying dependence structures. My work concentrates on better understanding Kronecker covariance structures as they are related to network analysis and high dimensional unbalanced factorial designs. I work on theory and methodology for high dimensional data as it relates to network analysis, causal inference and computational and statistical tradeoffs. My primary applied interest is in the health and social sciences with past and ongoing collaborations studying friendship formation in high schools, employment outcomes for college graduates and job mobility as a function of an underlying social network.
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论文共 31 篇作者统计合作学者相似作者
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Travis Seale-Carlisle, Saksham Jain, Courtney Lee, Caroline Levenson, Swathi Ramprasad,Brandon Garrett,Sudeepa Roy,Cynthia Rudin,Alexander Volfovsky
AAAI 2024no. 20 (2024): 22331-22340
Neha R. Gupta,Vittorio Orlandi,Chia-Rui Chang,Tianyu Wang,Marco Morucci,Pritam Dey, Thomas J. Howell,Xian Sun,Angikar Ghosal,Sudeepa Roy,Cynthia Rudin,Alexander Volfovsky
arxiv(2023)
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arxiv(2023)
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STATISTICAL METHODS AND APPLICATIONSno. 4 (2023): 1141-1166
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