Published March 23, 2016 | Version v1
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Entrofy: Participant Selection Made Easy

Authors/Creators

  • 1. New York University, Center for Data Science

Description

Selection participants for a workshop out of a much larger applicant pool can be a difficult task, especially when the goal is diversifying over a range of criteria (e.g. academic seniority, research field, skill levels, gender etc). In this talk I am presenting our tool, Entrofy, aimed at aiding organizers in this task. Entrofy is an open-source tool using a maximum entropy-based algorithm that aims to select a set of participants out of the applicant pool such that a pre-defined range of criteria are globally maximized. This approach allows for a potentially more transparent and less biased selection process while encouraging organizers to think deeply about the goals and the process of their participant selection.

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