Date of Award

5-1-2021

Degree Type

Thesis

Degree Name

Master of Science

Department

Computer Science

First Advisor

Amol Mali

Committee Members

Rohit Kate, Mohammad Rahman

Abstract

In 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.

Share

COinS