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dc.contributor.advisorAmol Mali
dc.creatorMadabhushi, Praneeth Keshav
dc.date.accessioned2025-01-21T23:34:10Z
dc.date.issued2021-05-01
dc.identifier.urihttp://digital.library.wisc.edu/1793/92665
dc.description.abstractIn the current era, Diversity, Equality, and Inclusion (DEI) are often not sufficiently addressed due to bias against certain people or unjust stereotypes or simply an inadequate understanding of the value of DEI. Not addressing DEI sufficiently leads to multiple problems including lawsuits, costly settlements, departure of valuable employees, reduced employee productivity, shortage of qualified workforce, and unjust hiring, compensation, and work-distribution practices. Initiatives to address DEI often fail or risk being ineffective. In this thesis, advances in modeling and search have been exploited to address DEI.
dc.relation.replaceshttps://dc.uwm.edu/etd/2696
dc.titleAddressing Diversity, Equality, Inclusion and Discrimination By Modeling, Selecting and Ordering Actions
dc.typethesis
thesis.degree.disciplineComputer Science
thesis.degree.nameMaster of Science
thesis.degree.grantorUniversity of Wisconsin-Milwaukee
dc.contributor.committeememberRohit Kate
dc.contributor.committeememberMohammad Rahman
dc.description.embargo2023-08-30
dc.embargo.liftdate2023-08-30


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