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Keynote and Invited Speakers will deliver their lectures live through WebEx https://purdue.webex.com/meet/aselvite on the dates and times detailed below.
"Be approximately right rather than exactly wrong."
"Be approximately right rather than exactly wrong."
~ John W. Tukey, Statistician
~ John W. Tukey, Statistician
Yuguo Chen
Yuguo Chen
Title: Statistical Inference on Network Data
Department of Statistics
University of Illinois at Urbana-Champaign
Marta Blangiardo
Marta Blangiardo
Title: Spatial and spatio-temporal models in the time of COVID-19
Department of Epidemiology and Biostatistics
Imperial College London
Fotios Milienos
Fotios Milienos
Title: Cure models: re-parametrization of a flexible family
Department of Sociology
Panteion University of Social and Political Sciences
Suvra Pal
Suvra Pal
Title: Integrating Support Vector Machine with Cure Rate Model and EM-based Inference
Department of Mathematics
University of Texas at Arlington
Adit Radhakrishnan
Adit Radhakrishnan
Title: Drug Repurposing Pipeline Using Overparametrized Representation Learning and Causality
Department of Electrical Engineering and Computer Science
MIT
Louis Cammarata
Louis Cammarata
Title: Drug Repurposing Pipeline Using Overparametrized Representation Learning and Causality
Department of Statistics
Harvard University
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